README

FEV@KEGG

FEV@KEGG allows for easy analysis of metabolic networks of organisms in KEGG (Kyoto Encyclopedia of Genes and Genomes). Read the API documentation here: https://fev-kegg.readthedocs.io

Restrictions

  • You MUST make absolutely sure to comply with the conditions of using KEGG and its API: http://www.kegg.jp/kegg/legal.html and http://www.kegg.jp/kegg/rest/.
  • If you have access to an offline copy of KEGG, you MUST NOT use the default Database and Download modules, since they cause a lot of load on KEGG servers. Instead, contact me, so we can integrate your offline copy to be used before anything is downloaded.

Features

  • convert data from KEGG PATHWAY and KEGG GENE to organism-specific graphs
  • graphs link substrates/products with reactions, genes, EC numbers, or abstract ‘enzymes’
  • cache downloads from KEGG, graphs, and any other computational result
  • build groups of organisms, allows for fusing their graphs into a common metabolism
  • gather groups from NCBI or KEGG taxonomy, using KEGG BRITE
  • gather clades from NCBI taxonomy and compare their ‘core’ metabolism
  • find paralogs/orthologs using KEGG SSDB
  • find possible gene duplications or neofunctionalisations
  • calculate robustness metrics between graphs, organisms, groups of organisms, or clades
  • … anything you can think of using graphs derived from KEGG

Install

Use pip to install FEV@KEGG and to automagically install all dependencies: pip install FEV_KEGG

If you are on Python 3.4, you will have to use pip install FEV_KEGG[python34] to pull in the backported typing package.

Where to start?

After successful installation, you might want to take a look at the “experiment” scripts in FEV_KEGG/Experiments. These scripts consecutively involve more and more functionality of this library. They were used during development, step by step adding and testing another layer of functionality or abstraction. Therefore, they might be useful to you in learning how to use this very functionality.

Also, take a look at the API documentation: https://fev-kegg.readthedocs.io

If any questions remain, feel free to report an issue: https://github.com/ryhaberecht/FEV-KEGG/issues

Dependencies

These are automatically installed by pip.

  • Python 3.4+
  • NetworkX
  • anytree
  • jsonpickle
  • tqdm
  • BeautifulSoup
  • retrying
  • appdirs
  • typing (for Python 3.4 only)

Optional Dependencies

If you want to draw a graph to an image file:

  • PyGraphviz
  • Graphviz (non-python software you will have to install manually!)

Use pip install FEV_KEGG[draw_image].


If you want to draw a graph in a pop-up window:

  • Matplotlib

Use pip install FEV_KEGG[draw_window]


Exporting to GraphML or GML works without any optional dependencies.

Included Dependencies

These have been partially copied into this project to avoid unnecessarily big dependencies and allow for minor changes.

  • Bio.KEGG from Biopython in lib.Biopython.KEGG

Recommendations

  • SSD

When handling 500 organisms from KEGG at once:

  • 64 bit operating system
  • 4 GB RAM
  • 20 GB disk space for cache

When handling all ~5000 organisms in KEGG at once:

  • 64 bit operating system
  • 12 GB RAM
  • 100 GB disk space for cache

Developer’s System

  • cPython 3.4.6
  • x86-64 Linux (OpenSUSE Leap 42.3)
  • 16 GB RAM
  • 1 CPU, 2 Cores, 4 Threads
  • SSD

Caching

  • The cache directory path is set up in the ‘settings.py’ file on the top level of the project. Per default, it points to your user’s cache directory as defined by your OS.
    • Linux/Unix: ~/.cache/FEV-KEGG
    • OS X: ~/Library/Caches/FEV-KEGG
    • Windows: C:\Users\username\AppData\Local\ryh\FEV-KEGG\Cache
  • All downloads from KEGG are cached automatically. Also, basic graphs are cached by organism. These default cachings alone can grow the cache directory to 100 GB size!
  • You can cache any function’s result using the @cache decorator, see FEV_KEGG.KEGG.File.cache. Watch out to remember the path and file name and not to overwrite any other cached files.
  • To cause a download of the newest version of data from KEGG, you have to delete the cached file manually. Have a look inside the ‘cache’ folder, file paths and names should be self-explanatory.
  • On Linux with supporting file systems, disabling atime (file access time) for the cache directory and all its contents might improve performance: sudo chattr -R +A ~/.cache/FEV-KEGG

API

FEV_KEGG package

Subpackages

FEV_KEGG.Drawing package

Submodules
FEV_KEGG.Drawing.Draw module
class FEV_KEGG.Drawing.Draw.NetworkxLayout[source]

Bases: enum.Enum

Enum of layout algorithms known to NetworkX.

fruchterman_reingold(k=None, pos=None, fixed=None, iterations=50, threshold=0.0001, weight='weight', scale=1, center=None, dim=2, random_state=None)

Position nodes using Fruchterman-Reingold force-directed algorithm.

Parameters:
  • G (NetworkX graph or list of nodes) – A position will be assigned to every node in G.
  • k (float (default=None)) – Optimal distance between nodes. If None the distance is set to 1/sqrt(n) where n is the number of nodes. Increase this value to move nodes farther apart.
  • pos (dict or None optional (default=None)) – Initial positions for nodes as a dictionary with node as keys and values as a coordinate list or tuple. If None, then use random initial positions.
  • fixed (list or None optional (default=None)) – Nodes to keep fixed at initial position.
  • iterations (int optional (default=50)) – Maximum number of iterations taken
  • threshold (float optional (default = 1e-4)) – Threshold for relative error in node position changes. The iteration stops if the error is below this threshold.
  • weight (string or None optional (default='weight')) – The edge attribute that holds the numerical value used for the edge weight. If None, then all edge weights are 1.
  • scale (number (default: 1)) – Scale factor for positions. Not used unless fixed is None.
  • center (array-like or None) – Coordinate pair around which to center the layout. Not used unless fixed is None.
  • dim (int) – Dimension of layout.
  • random_state (int, RandomState instance or None optional (default=None)) – Set the random state for deterministic node layouts. If int, random_state is the seed used by the random number generator, if numpy.random.RandomState instance, random_state is the random number generator, if None, the random number generator is the RandomState instance used by numpy.random.
Returns:

pos – A dictionary of positions keyed by node
Return type:

dict

Examples

>>> G = nx.path_graph(4)
>>> pos = nx.spring_layout(G)

# The same using longer but equivalent function name >>> pos = nx.fruchterman_reingold_layout(G)

kamada_kawai(dist=None, pos=None, weight='weight', scale=1, center=None, dim=2)

Position nodes using Kamada-Kawai path-length cost-function.

Parameters:
  • G (NetworkX graph or list of nodes) – A position will be assigned to every node in G.
  • dist (float (default=None)) – A two-level dictionary of optimal distances between nodes, indexed by source and destination node. If None, the distance is computed using shortest_path_length().
  • pos (dict or None optional (default=None)) – Initial positions for nodes as a dictionary with node as keys and values as a coordinate list or tuple. If None, then use circular_layout().
  • weight (string or None optional (default='weight')) – The edge attribute that holds the numerical value used for the edge weight. If None, then all edge weights are 1.
  • scale (number (default: 1)) – Scale factor for positions.
  • center (array-like or None) – Coordinate pair around which to center the layout.
  • dim (int) – Dimension of layout.
Returns:

pos – A dictionary of positions keyed by node
Return type:

dict

Examples

>>> G = nx.path_graph(4)
>>> pos = nx.kamada_kawai_layout(G)
random(center=None, dim=2, random_state=None)

Position nodes uniformly at random in the unit square.

For every node, a position is generated by choosing each of dim coordinates uniformly at random on the interval [0.0, 1.0).

NumPy (http://scipy.org) is required for this function.

Parameters:
  • G (NetworkX graph or list of nodes) – A position will be assigned to every node in G.
  • center (array-like or None) – Coordinate pair around which to center the layout.
  • dim (int) – Dimension of layout.
  • random_state (int, RandomState instance or None optional (default=None)) – Set the random state for deterministic node layouts. If int, random_state is the seed used by the random number generator, if numpy.random.RandomState instance, random_state is the random number generator, if None, the random number generator is the RandomState instance used by numpy.random.
Returns:

pos – A dictionary of positions keyed by node
Return type:

dict

Examples

>>> G = nx.lollipop_graph(4, 3)
>>> pos = nx.random_layout(G)
shell(nlist=None, scale=1, center=None, dim=2)

Position nodes in concentric circles.

Parameters:
  • G (NetworkX graph or list of nodes) – A position will be assigned to every node in G.
  • nlist (list of lists) – List of node lists for each shell.
  • scale (number (default: 1)) – Scale factor for positions.
  • center (array-like or None) – Coordinate pair around which to center the layout.
  • dim (int) – Dimension of layout, currently only dim=2 is supported.
Returns:

pos – A dictionary of positions keyed by node
Return type:

dict

Examples

>>> G = nx.path_graph(4)
>>> shells = [[0], [1, 2, 3]]
>>> pos = nx.shell_layout(G, shells)

Notes

This algorithm currently only works in two dimensions and does not try to minimize edge crossings.

spectral(weight='weight', scale=1, center=None, dim=2)

Position nodes using the eigenvectors of the graph Laplacian.

Parameters:
  • G (NetworkX graph or list of nodes) – A position will be assigned to every node in G.
  • weight (string or None optional (default='weight')) – The edge attribute that holds the numerical value used for the edge weight. If None, then all edge weights are 1.
  • scale (number (default: 1)) – Scale factor for positions.
  • center (array-like or None) – Coordinate pair around which to center the layout.
  • dim (int) – Dimension of layout.
Returns:

pos – A dictionary of positions keyed by node
Return type:

dict

Examples

>>> G = nx.path_graph(4)
>>> pos = nx.spectral_layout(G)

Notes

Directed graphs will be considered as undirected graphs when positioning the nodes.

For larger graphs (>500 nodes) this will use the SciPy sparse eigenvalue solver (ARPACK).

spring(k=None, pos=None, fixed=None, iterations=50, threshold=0.0001, weight='weight', scale=1, center=None, dim=2, random_state=None)

Position nodes using Fruchterman-Reingold force-directed algorithm.

Parameters:
  • G (NetworkX graph or list of nodes) – A position will be assigned to every node in G.
  • k (float (default=None)) – Optimal distance between nodes. If None the distance is set to 1/sqrt(n) where n is the number of nodes. Increase this value to move nodes farther apart.
  • pos (dict or None optional (default=None)) – Initial positions for nodes as a dictionary with node as keys and values as a coordinate list or tuple. If None, then use random initial positions.
  • fixed (list or None optional (default=None)) – Nodes to keep fixed at initial position.
  • iterations (int optional (default=50)) – Maximum number of iterations taken
  • threshold (float optional (default = 1e-4)) – Threshold for relative error in node position changes. The iteration stops if the error is below this threshold.
  • weight (string or None optional (default='weight')) – The edge attribute that holds the numerical value used for the edge weight. If None, then all edge weights are 1.
  • scale (number (default: 1)) – Scale factor for positions. Not used unless fixed is None.
  • center (array-like or None) – Coordinate pair around which to center the layout. Not used unless fixed is None.
  • dim (int) – Dimension of layout.
  • random_state (int, RandomState instance or None optional (default=None)) – Set the random state for deterministic node layouts. If int, random_state is the seed used by the random number generator, if numpy.random.RandomState instance, random_state is the random number generator, if None, the random number generator is the RandomState instance used by numpy.random.
Returns:

pos – A dictionary of positions keyed by node
Return type:

dict

Examples

>>> G = nx.path_graph(4)
>>> pos = nx.spring_layout(G)

# The same using longer but equivalent function name >>> pos = nx.fruchterman_reingold_layout(G)

FEV_KEGG.Drawing.Draw.toPNG(graph: FEV_KEGG.Graph.Models.CommonGraphApi, fileName: path/file, layout='neato')[source]

Draw graph and save it as PNG format in a file.

Drawing requires an algorithm to determine the best position für each node and the best path for each edge. This algorithm can be defined via layout.

Parameters:
  • graph (Models.CommonGraphApi) – The graph to be drawn.
  • fileName (str) – Path and name of the file, the extension ‘.png’ is automatically applied. The path is relative to the current working directory!
  • layout (str, optional) – A layout algorithm known to pygraphviz.
Raises:
  • ImportError – If pygraphviz is not installed. This is an optional dependency and not installed via pip by deault! PyGraphviz needs Graphviz to function, which is not a python program and has to be installed manually by you!
  • NotImplementedError – If graph is not of a NetworkX type.
FEV_KEGG.Drawing.Draw.toWindow(graph: FEV_KEGG.Graph.Models.CommonGraphApi, layout: FEV_KEGG.Drawing.Draw.NetworkxLayout)[source]

Draw graph and display it in a window.

Drawing requires an algorithm to determine the best position für each node and the best path for each edge. This algorithm can be defined via layout.

Parameters:
Raises:
  • ImportError – If matplotlib is not installed. This is an optional dependency and not installed via pip by deault! Matplotlib needs a working backend to function, which is not a python program and has to be installed manually by you! For a list of backends, see Matplotlib’s website.
  • NotImplementedError – If graph is not of a NetworkX type.
FEV_KEGG.Drawing.Export module
FEV_KEGG.Drawing.Export.COLOUR_NAME = 'colour'

Name of the attribute of the graph to be used for storing the colour.

class FEV_KEGG.Drawing.Export.Colour[source]

Bases: enum.Enum

An enumeration.

BLUE = '#4444FF'
GREEN = '#55FF55'
PINK = '#FF66FF'
RED = '#FF5555'
TURQUOISE = '#55FFFF'
YELLOW = '#FFFF55'
FEV_KEGG.Drawing.Export.DESCRIPTION_NAME = 'custom_description'

Name of the attribute of the graph to be used for storing the description.

FEV_KEGG.Drawing.Export.ID_NAME = 'custom_id'

Name of the attribute of the graph to be used for storing the id.

FEV_KEGG.Drawing.Export.LABEL_NAME = 'custom_label'

Name of the attribute of the graph to be used for storing the label.

FEV_KEGG.Drawing.Export.MAJORITY_NAME = 'custom_majority'

Name of the attribute of the graph to be used for storing the majority percentage.

FEV_KEGG.Drawing.Export.REACTION_NAME = 'custom_reaction'

Name of the attribute of the graph to be used for storing the reaction.

FEV_KEGG.Drawing.Export.URL_NAME = 'URL'

Name of the attribute of the graph to be used for storing the URL.

FEV_KEGG.Drawing.Export.addColourAttribute(graph: FEV_KEGG.Graph.Models.CommonGraphApi, colour: FEV_KEGG.Drawing.Export.Colour, nodes=False, edges=False)[source]

Adds the “colour” attribute to selected nodes/edges.

If both, nodes and edges are False, nothing is coloured. Adds an attribute to nodes and edges called “colour” (see module variable COLOUR_NAME) containing the string of a hex value of a colour in RGB, see Colour.

Parameters:
  • graph (Models.CommonGraphApi) – A graph object.
  • colour (Colour) – Colour to use.
  • nodes (Iterable[NodeView] or bool, optional) – Nodes to be coloured, i.e. annotated with the “colour” attribute containing colour. If True, all nodes are coloured.
  • edges (Iterable[EdgeView] or bool, optional) – Edges to be coloured, i.e. annotated with the “colour” attribute containing colour. If True, all edges are coloured.

Warning

Any operation on the resulting graph, e.g. FEV_KEGG.Graph.Models.CommonGraphApi.intersection(), removes the colouring. It actually removes all attributes.

FEV_KEGG.Drawing.Export.addDescriptionAttribute(nxGraph: networkx.classes.multigraph.MultiGraph)[source]

Adds the “custom_description” attribute to each node and edge.

Add an attribute to nodes and edges called “custom_description” (see module variable DESCRIPTION_NAME) containing the node’s or edge’s .description field, if there is any.

Parameters:nxGraph (networkx.classes.MultiGraph) – A NetworkX graph object.
FEV_KEGG.Drawing.Export.addIdAttribute(nxGraph: networkx.classes.multigraph.MultiGraph)[source]

Adds the “custom_id” attribute to each node and edge.

Add an attribute to nodes and edges called “custom_id” (see module variable ID_NAME) containing the string of the node’s id, or the edge’s key’s id, repectively.

Parameters:nxGraph (networkx.classes.MultiGraph) – A NetworkX graph object.
FEV_KEGG.Drawing.Export.addLabelAttribute(nxGraph: networkx.classes.multigraph.MultiGraph)[source]

Adds the “custom_label” attribute to each node and edge.

Add an attribute to nodes and edges called “custom_label” (see module variable LABEL_NAME) containing the string of the node’s label, or the edge’s key’s label, repectively. A label is defined as either the .name field, or if that is None, the id. This is especially useful if the tool you import this file into does not regularly read the XML’s id parameter. For example, Cytoscape does not for edges.

Parameters:nxGraph (networkx.classes.MultiGraph) – A NetworkX graph object.
FEV_KEGG.Drawing.Export.addMajorityAttribute(graph: FEV_KEGG.Graph.Models.CommonGraphApi, totalNumberOfOrganisms: int)[source]

Adds the “custom_majority” attribute to each node and edge.

Add an attribute to nodes and edges called “custom_majority” (see module variable MAJORITY_NAME). It contains each node’s or edge’s majority percentage, if the graph contains counts (graph.nodeCounts or graph.edgeCounts, see FEV_KEGG.Graph.Models.CommonGraphApi). For example, say edge A were to occur in 52 of all organisms used to create the graph, then `graph.edgeCounts[A] == 52`. Now we have also `totalNumberOfOrganisms == 76`. Then, we will write `ceil(52/76*100) = 68` into the “custom_majority” attribute.

Parameters:
  • graph (Models.CommonGraphApi) – A graph object.
  • totalNumberOfOrganisms (int) – Total number of organisms which were involved in creating the graph. This is used to calculate the percentage of counts. 100% == totalNumberOfOrganisms.
FEV_KEGG.Drawing.Export.addReactionAttribute(nxGraph: networkx.classes.multigraph.MultiGraph)[source]

Adds the “custom_reaction” attribute to each edge.

Add an attribute to edges called “custom_reaction” (see module variable REACTION_NAME) containing the edge’s .reaction field, if there is any.

Parameters:nxGraph (networkx.classes.MultiGraph) – A NetworkX graph object.
FEV_KEGG.Drawing.Export.addUrlAttribute(nxGraph: networkx.classes.multigraph.MultiGraph)[source]

Adds the “URL” attribute to each edge.

Add an attribute to edges called “URL” (see module variable URL_NAME) containing the edge’s or node’s URL to KEGG.

Parameters:nxGraph (networkx.classes.MultiGraph) – A NetworkX graph object.
FEV_KEGG.Drawing.Export.forCytoscape(graph: FEV_KEGG.Graph.Models.CommonGraphApi, file, inCacheFolder=False, addDescriptions=True, totalNumberOfOrganisms: int = None)[source]

Export graph to file in GraphML format, including some tweaks for Cytoscape.

Parameters:
  • graph (Models.CommonGraphApi) – The graph to be exported.
  • file (str) – Path and name of the exported file. See inCacheFolder.
  • inCacheFolder (bool, optional) – If True, interpret file relative to the cache folder. See FEV_KEGG.settings.cachePath. If False, interpret file relative to the current working directory.
  • addDescriptions (bool, optional) – If True, downloads additional descriptions for substance
  • totalNumberOfOrganisms (int, optional) – Total number of organisms which were involved in creating the graph. This is used to calculate the percentage of counts. 100% == totalNumberOfOrganisms. If None, no majority attribute is added. Only relevant if graph has counts, which it usually does not. See addMajorityAttribute() for more info.
Raises:

NotImplementedError – If graph is not of a NetworkX type.

Warning

Adding extra descriptions, when addDescriptions == True (default!) is a lengthy process and can take some minutes.

FEV_KEGG.Drawing.Export.toGML(graph: FEV_KEGG.Graph.Models.CommonGraphApi, file, inCacheFolder=False)[source]

Export graph to file in GML format.

Each of the graph element’s attributes is translated into a column.

Parameters:
  • graph (Models.CommonGraphApi) – The graph to be exported.
  • file (str) – Path and name of the exported file. See inCacheFolder.
  • inCacheFolder (bool, optional) – If True, interpret file relative to the cache folder. See FEV_KEGG.settings.cachePath. If False, interpret file relative to the current working directory.
Raises:

NotImplementedError – If graph is not of a NetworkX type.
FEV_KEGG.Drawing.Export.toGraphML(graph: FEV_KEGG.Graph.Models.CommonGraphApi, file, inCacheFolder=False)[source]

Export graph to file in GraphML format.

Each of the graph element’s attributes is translated into a column.

Parameters:
  • graph (Models.CommonGraphApi) – The graph to be exported.
  • file (str) – Path and name of the exported file. See inCacheFolder.
  • inCacheFolder (bool, optional) – If True, interpret file relative to the cache folder. See FEV_KEGG.settings.cachePath. If False, interpret file relative to the current working directory.
Raises:

NotImplementedError – If graph is not of a NetworkX type.
Module contents

FEV_KEGG.Evolution package

Submodules
FEV_KEGG.Evolution.Clade module
class FEV_KEGG.Evolution.Clade.Clade(ncbiNames: e.g. Enterobacter or Proteobacteria/Gammaproteobacteria. Allows list of names, e.g. ["Gammaproteobacteria", "/Archaea"], excludeUnclassified=True, oneOrganismPerSpecies=True)[source]

Bases: object

A clade in NCBI taxonomy, containing all leaf taxon’s KEGG organisms.

Parameters:
  • ncbiNames (str or Iterable[str]) – String(s) a taxon’s path must contain to be included in this clade.
  • excludeUnclassified (bool, optional) – If True, ignore taxons with a path containing the string ‘unclassified’.
  • oneOrganismPerSpecies (bool, optional) – If True, use only the first organism of each species.
Variables:
  • self.ncbiNames (Iterable[str]) – Part of the path of each leaf taxon to be included in this clade. A single string is wrapped in a list.
  • self.group – The FEV_KEGG.KEGG.Organism.Group of KEGG organisms created from the found leaf taxons.
Raises:

ValueError – If no clade with ncbiNames in its path could be found.

Warning

It is possible to include organisms of several clades in the same Clade object! For example, if you were to search for ncbiNames == ‘Donaldus Duckus’, you would get every organism within ‘/Bacteria/Donaldus Duckus’ and ‘/Archaea/Order/Donaldus Duckus’. Use the slash (/) notation to make sure you only get the taxon you want, e.g. ‘Proteobacteria/Gammaproteobacteria’ or ‘/Archaea’.

collectiveMetabolism(excludeMultifunctionalEnzymes=True, addEcDescriptions=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

The Substance-EC graph representing the collective metabolic network, occuring in any organism of the clade.

This includes each and every EC number which occurs in any organism of this clade.

Parameters:

excludeMultifunctionalEnzymes (bool, optional) – If True, ignore enzymes with more than one EC number.
Returns:

Collective metabolic network of EC numbers, including counts of occurence in each of the clade’s organisms.
Return type:

SubstanceEcGraph
Raises:
collectiveMetabolismEnzymes(excludeMultifunctionalEnzymes=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

The Substance-Enzyme graph representing the collective metabolic network, occuring in any organism of the clade.

This includes each and every enzyme of every organism of this clade.

Parameters:

excludeMultifunctionalEnzymes (bool, optional) – If True, ignore enzymes with more than one EC number.
Returns:

Collective metabolic network of enzymes.
Return type:

SubstanceEnzymeGraph
Raises:
coreMetabolism(majorityPercentageCoreMetabolism=80, excludeMultifunctionalEnzymes=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

The Substance-EC graph representing the common metabolic network, shared among all organisms of the clade.

This includes only EC numbers which occur in at least majorityPercentageCoreMetabolism % of all organisms of this clade.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – A path (substance -> EC -> product) has to occur in majorityPercentageCoreMetabolism % of the clade’s organisms to be included.
  • excludeMultifunctionalEnzymes (bool, optional) – If True, ignore enzymes with more than one EC number.
Returns:

Core metabolic network of EC numbers.
Return type:

SubstanceEcGraph
Raises:
coreMetabolismEnzymes(majorityPercentageCoreMetabolism=80, excludeMultifunctionalEnzymes=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

The Substance-Enzyme graph representing the common metabolic network, shared among all organisms of the clade.

This includes every Enzyme associated with an EC number occuring in core metabolism (see substanceEcGraph()), no matter from which organism it stems.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – A path (substance -> EC -> product) has to occur in majorityPercentageCoreMetabolism % of the clade’s organisms to be included.
  • excludeMultifunctionalEnzymes (bool, optional) – If True, ignore enzymes with more than one EC number.
Returns:

Core metabolic network of enzymes.
Return type:

SubstanceEnzymeGraph
Raises:
geneDuplicatedEnzymePairs(majorityPercentageCoreMetabolism=80) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

All gene duplicated enzymes of the core metabolism, paired with each of their duplicates.

If enzyme A is a duplicate of enzyme B and vice versa, this does not return duplicates, but returns only one pair, with the “smaller” enzyme as the first value. An enzyme is “smaller” if its gene ID string is “smaller”.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
Returns:

Set of gene-duplicated enzymes, broken down into pairs of enzymes. Can obviously create many duplicates left and right.
Return type:

Set[Tuple[Enzyme, Enzyme]]
Raises:
geneDuplicatedEnzymes(majorityPercentageCoreMetabolism=80, colour=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

The substance-Enzyme graph of all gene duplicated enzymes of the core metabolism.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
  • colour (bool, optional) – If True, colours the gene-duplicated enzyme edges in green. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured. Alternatively, you can specify a Export.Colour.
Returns:

Substance-Enzyme graph containing all gene-duplicated enzymes, and nothing else. If colour == True, returns the full core metabolism enzyme graph, colouring gene-duplicated enzymes green.
Return type:

SubstanceEnzymeGraph
Raises:
geneDuplicatedEnzymesDict(majorityPercentageCoreMetabolism=80) → Dict[FEV_KEGG.Graph.Elements.Enzyme, Set[FEV_KEGG.Graph.Elements.GeneID]][source]

All gene duplicated enzymes of the core metabolism, pointing to all their duplicates.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
Returns:

Each gene ID on the right usually has an entry of its own, as an enzyme object, on the left, because they are each others homologs.
Return type:

Dict[Enzyme, Set[GeneID]]
Raises:
neofunctionalisations(majorityPercentageCoreMetabolism=80, eValue=1e-15, considerOnlyECs=None) → Set[FEV_KEGG.Evolution.Events.Neofunctionalisation][source]

Get neofunctionalisation events of all enzymes in the core metabolism.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • considerOnlyECs (Iterable[EcNumber], optional) – If given, only enzymes with an EC number in considerOnlyECs are tested for neofunctionalisation.
Returns:

Set of possible neofunctionalisation events.
Return type:

Set[Neofunctionalisation]
Raises:
neofunctionalisationsForFunctionChange(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0, eValue=1e-15, considerOnlyECs=None) → Dict[FEV_KEGG.Evolution.Events.FunctionChange, Set[FEV_KEGG.Evolution.Events.Neofunctionalisation]][source]

Get neofunctionalisation events of all enzymes in the core metabolism, grouped by each possible function change event.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
  • majorityPercentageNeofunctionalisation (int, optional) – Every EC number considered for neofunctionalisation has to be associated with a function change of neofunctionalisations whose enzymes involve at least majorityPercentageNeofunctionalisation % of of the clade’s organisms. A high majorityPercentageNeofunctionalisation disallows us to detect neofunctionalisations which happened a long time ago, with their genes having diverged significantly; or only recently, with not all organisms of the child clade having picked up the new function, yet.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • considerOnlyECs (Iterable[EcNumber], optional) – If given, only enzymes with an EC number in considerOnlyECs are tested for neofunctionalisation.
Returns:

Dictionary of function changes, pointing to a set of neofunctionalisations which might have caused them.

Since an enzyme of a neofunctionalisation can have multiple EC numbers, all combinations of the two enzymes’ EC numbers are formed and treated as separate possible function changes. The neofunctionalisation is then saved again for each function change, which obviously leads to duplicated neofunctionalisation objects.
Return type:

Dict[FunctionChange, Set[Neofunctionalisation]]
Raises:
neofunctionalisedECs(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0, colour=False, eValue=1e-15, considerOnlyECs=None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

The substance-EC graph of EC numbers belonging to function changes of neofunctionalised enzymes of the core metabolism.

Only EC numbers which could have actually taken part in a function change are reported. This is because enzymes can have multiple EC numbers, while only some might be eligible for a function change. For example, consider enzyme A (1.2.3.4, 6.5.4.3) and enzyme B (1.2.3.4, 4.5.6.7). 1.2.3.4 can never change its function to itself, which leaves 1.2.3.4 <-> 6.5.4.3, 1.2.3.4 <-> 4.5.6.7, and 4.5.6.7 <-> 6.5.4.3 as possible function changes. This obviously requires a function to change to a single other function, without splitting or merging, which might be biologically inacurate. However, this should happen rarely, plus one could exclude all enzymes with multiple functions from the core metabolism in the first place.

The maximum expectation value (e-value) necessary for a sequence alignment to constitute a “similar sequence” can be changed via defaultEValue.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
  • majorityPercentageNeofunctionalisation (int, optional) – Every EC number considered for neofunctionalisation has to be associated with a function change of neofunctionalisations whose enzymes involve at least majorityPercentageNeofunctionalisation % of of the clade’s organisms. A high majorityPercentageNeofunctionalisation disallows us to detect neofunctionalisations which happened a long time ago, with their genes having diverged significantly; or only recently, with not all organisms of the child clade having picked up the new function, yet.
  • colour (bool, optional) – If True, colours the neofunctionalised EC edges in green. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured. Alternatively, you can specify a Export.Colour.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • considerOnlyECs (Iterable[EcNumber], optional) – If given, only enzymes with an EC number in considerOnlyECs are tested for neofunctionalisation.
Returns:

The substance-EC graph representing the metabolic network which was probably affected due to neofunctionalisations of the core metabolism of the clade. If colour == True, returns the full union of parent and child, colouring neofunctionalised ECs green.
Return type:

SubstanceEcGraph
Raises:
neofunctionalisedEnzymes(majorityPercentageCoreMetabolism=80, colour=False, eValue=1e-15, considerOnlyECs=None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

The substance-Enzyme graph of all neofunctionalised enzymes of the core metabolism.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
  • colour (bool, optional) – If True, colours the neofunctionalised enzyme edges in green. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured. Alternatively, you can specify a Export.Colour.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • considerOnlyECs (Iterable[EcNumber], optional) – If given, only enzymes with an EC number in considerOnlyECs are tested for neofunctionalisation.
Returns:

Substance-Enzyme graph containing all neofunctionalised enzymes, and nothing else. If colour == True, returns the full core metabolism enzyme graph, colouring neofunctionalised enzymes green.
Return type:

SubstanceEnzymeGraph
Raises:
organismsCount

The number of organisms (leaf taxons) in this clade.

Returns:The number of organisms (leaf taxons) in this clade.
Return type:int
redundantECsForContributingNeofunctionalisation(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0, eValue=1e-15, redundancyType: RedundancyType = None, considerOnlyECs=None) → Dict[FEV_KEGG.Evolution.Events.Neofunctionalisation, Set[FEV_KEGG.Graph.Elements.EcNumber]][source]

Get neofunctionalisation events of all enzymes in the core metabolism, which contribute to redundancy, pointing to the EC numbers their function changes’ EC numbers provides redundancy for.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism.
  • majorityPercentageNeofunctionalisation (int, optional) – Every EC number considered for neofunctionalisation has to be associated with a function change of neofunctionalisations whose enzymes involve at least majorityPercentageNeofunctionalisation % of of the clade’s organisms. A high majorityPercentageNeofunctionalisation disallows us to detect neofunctionalisations which happened a long time ago, with their genes having diverged significantly; or only recently, with not all organisms of the child clade having picked up the new function, yet.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • redundancyType (RedundancyType) – Definition of redundancy for which to check the neofunctionalisation’s contribution. Default to RedundancyType.default.
  • considerOnlyECs (Iterable[EcNumber], optional) – If given, only enzymes with an EC number in considerOnlyECs are tested for neofunctionalisation.
Returns:

Dictionary of function changes, pointing to a set of neofunctionalisations which might have caused them.

Since an enzyme of a neofunctionalisation can have multiple EC numbers, all combinations of the two enzymes’ EC numbers are formed and treated as separate possible function changes. The neofunctionalisation is then saved again for each function change, which obviously leads to duplicated neofunctionalisation objects.
Return type:

Dict[FunctionChange, Set[Neofunctionalisation]]
Raises:
class FEV_KEGG.Evolution.Clade.CladePair(parent, child, excludeUnclassified=True, oneOrganismPerSpecies=True)[source]

Bases: object

Two clades in NCBI taxonomy, ‘child’ is assumed younger than ‘parent’.

Does not check if the child taxon is actually a child of the parent taxon. Therefore, it would be possible to pass a list of NCBI names to the underlying Clade objects by instantiating parent = List[str] and/or child = List[str]. This is useful when comparing groups of organisms which are, according to NCBI, not related.

Parameters:
  • parent (str or List[str] or Clade) – Path(s) of the parent clade’s taxon, as defined by NCBI taxonomy, e.g. ‘Proteobacteria/Gammaproteobacteria’. Or a ready Clade object.
  • child (str or List[str] or Clade) – Path(s) of the child clade’s taxon, as defined by NCBI taxonomy, e.g. ‘Enterobacter’. Or a ready Clade object.
  • excludeUnclassified (bool, optional) – If True, ignore taxons with a path containing the string ‘unclassified’. Only used if one of parent and/or child is not already a Clade.
  • oneOrganismPerSpecies (bool, optional) – If True, use only the first organism of each species.
Variables:
  • self.childClade (Clade) –
  • self.parentClade (Clade) –
addedMetabolism(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of the added core metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism. This is individually true for both parent clade and child clade. The parent clade fully includes the child clade, therefore, the occurence of a substance-EC-product edge in the child clade’s core metabolism counts towards the percentage for the parent clade’s core metabolism. Meaning: if an EC number does not occur in the child clade’s core metabolism, it is unlikely that it will occur in the parent clade’s core metabolism, unless majorityPercentageCoreMetabolism is consecutively lowered towards 0.
Returns:

The substance-EC graph representing the metabolic network which was added to the core metabolism of the parent (assumed older) on the way to the core metabolism of the child (assumed younger).
Return type:

SubstanceEcGraph
Raises:
addedMetabolismEnzymes(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph derived from the added core metabolism, see addedMetabolism().

First, the added core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the child’s enzyme metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See addedMetabolism().
Returns:

Substance-Enzyme graph of enzymes from the child clade. Calculated using the added EC numbers found by addedMetabolism().
Return type:

SubstanceEnzymeGraph
Raises:
addedMetabolismGeneDuplicatedEnzymePairs(majorityPercentageCoreMetabolism=80) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

Pairs of gene-duplicated enzymes, derived from the added core metabolism.

First, the added core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the child’s enzyme metabolism. Then the gene-duplicated enzymes are calculated. Finally, the gene-duplicated enzyme pairs of the conserved core metabolism enzymes are reported.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See addedMetabolism().
Returns:

Pairs of enzymes from the child clade. Calculated using the added EC numbers found by addedMetabolism().
Return type:

Set[Tuple[Enzyme, Enzyme]]
Raises:
addedMetabolismGeneDuplicatedEnzymes(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph of gene-duplicated enzymes, derived from the added core metabolism.

First, the added core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the child’s enzyme metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See addedMetabolism().
Returns:

Substance-Enzyme graph of enzymes from the child clade. Calculated using the added EC numbers found by addedMetabolism().
Return type:

SubstanceEnzymeGraph
Raises:
addedMetabolismNeofunctionalisedECs(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of “neofunctionalised” EC numbers, derived from the added core metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See addedMetabolism().
Returns:

Substance-EC graph of ECs from the child clade. Calculated using the added EC numbers found by addedMetabolism().
Return type:

SubstanceEcGraph
Raises:
addedMetabolismNeofunctionalisedEnzymes(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph of neofunctionalised enzymes, derived from the added core metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See addedMetabolism().
Returns:

Substance-Enzyme graph of enzymes from the child clade. Calculated using the added EC numbers found by addedMetabolism().
Return type:

SubstanceEnzymeGraph
Raises:
childNCBInames

All names/paths in NCBI taxonomy used to create the child clade.

conservedMetabolism(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of the conserved core metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism. This is individually true for both parent clade and child clade. The parent clade fully includes the child clade, therefore, the occurence of a substance-EC-product edge in the child clade’s core metabolism counts towards the percentage for the parent clade’s core metabolism. Meaning: if an EC number does not occur in the child clade’s core metabolism, it is unlikely that it will occur in the parent clade’s core metabolism, unless majorityPercentageCoreMetabolism is consecutively lowered towards 0.
Returns:

The substance-EC graph representing the metabolic network which stayed the same between the core metabolism of the parent (assumed older) and the core metabolism of the child (assumed younger).
Return type:

SubstanceEcGraph
Raises:
conservedMetabolismEnzymes(majorityPercentageCoreMetabolism=80, colour=False)[source]

Two Substance-Enzyme graphs derived from the conserved core metabolism, see conservedMetabolism().

First, the conserved core metabolism is calculated. Then, the enzymes associated with the conserved EC numbers are extracted from the collective parent’s and child’s metabolism individually.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the enzyme edges from the parent in blue, and from the child in red. When doing so, a single SubstanceEnzymeGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-Enzyme graphs calculated using the conserved EC numbers found by conservedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-Enzyme graph, coloured blue for parent and red for child.
Return type:

Tuple[SubstanceEnzymeGraph, SubstanceEnzymeGraph] or SubstanceEnzymeGraph
Raises:
conservedMetabolismGeneDuplicatedEnzymePairs(majorityPercentageCoreMetabolism=80) → Tuple[Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]]][source]

Pairs of gene-duplicated enzymes, derived from the conserved core metabolism.

First, the conserved core metabolism is calculated. Then, the enzymes associated with the conserved EC numbers are extracted from the collective parent’s and child’s metabolism individually. Then, for parent and child, the gene-duplicated enzyme pairs are calculated. Finally, the gene-duplicated enzymes where both enzymes are in the conserved core metabolism are reported.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
Returns:

Tuple of two sets of tuples of gene-duplicated enzyme pairs calculated using the conserved EC numbers found by conservedMetabolism(). The first set is from the parent clade, the second set from the child clade.
Return type:

Tuple[Set[Tuple[Enzyme, Enzyme]]]
Raises:
conservedMetabolismGeneDuplicatedEnzymes(majorityPercentageCoreMetabolism=80, colour=False)[source]

Two Substance-Enzyme graphs of gene-duplicated enzymes, derived from the conserved core metabolism.

First, the conserved core metabolism is calculated. Then, the enzymes associated with the conserved EC numbers are extracted from the collective parent’s and child’s metabolism individually. Then, for parent and child, the gene-duplicated enzymes are calculated. Finally, the gene-duplicated enzymes of the conserved core metabolism enzymes are reported.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the enzyme edges from the parent in blue, and from the child in red. Gene-duplicated enzyme edges of the parent are coloured in green, the ones of the child in yellow. When doing so, a single SubstanceEnzymeGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-Enzyme graphs calculated using the conserved EC numbers found by conservedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-Enzyme graph.
Return type:

Tuple[SubstanceEnzymeGraph, SubstanceEnzymeGraph] or SubstanceEnzymeGraph
Raises:
conservedMetabolismNeofunctionalisedECs(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0, colour=False)[source]

Two Substance-EC graphs of “neofunctionalised” EC numbers, derived from the conserved core metabolism.

First, the conserved core metabolism is calculated. Then, the enzymes associated with the conserved EC numbers are extracted from the collective parent’s and child’s metabolism individually. Then, for parent and child, the gene-duplicated enzymes are calculated. Then, the gene-duplicated enzymes of the conserved core metabolism enzymes are identified. Then, the pairs of enzymes in which EC numbers differ are identified. Finally, the EC numbers which are part of these function changes are reported.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the EC edges from the parent in blue, and from the child in red. “Neofunctionalised” EC edges of the parent are coloured in green, the ones of the child in yellow. When doing so, a single SubstanceEcGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-EC graphs calculated using the conserved EC numbers found by conservedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-EC graph.
Return type:

Tuple[SubstanceEcGraph, SubstanceEcGraph] or SubstanceEcGraph
Raises:
conservedMetabolismNeofunctionalisedEnzymes(majorityPercentageCoreMetabolism=80, colour=False)[source]

Two Substance-Enzyme graphs of neofunctionalised enzymes, derived from the conserved core metabolism.

First, the conserved core metabolism is calculated. Then, the enzymes associated with the conserved EC numbers are extracted from the collective parent’s and child’s metabolism individually. Then, for parent and child, the gene-duplicated enzymes are calculated. Then, the gene-duplicated enzymes of the conserved core metabolism enzymes are identified. Finally, the pairs of enzymes in which EC numbers differ are reported.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the enzyme edges from the parent in blue, and from the child in red. Neofunctionalised enzyme edges of the parent are coloured in green, the ones of the child in yellow. When doing so, a single SubstanceEnzymeGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-Enzyme graphs calculated using the conserved EC numbers found by conservedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-Enzyme graph.
Return type:

Tuple[SubstanceEnzymeGraph, SubstanceEnzymeGraph] or SubstanceEnzymeGraph
Raises:
divergedMetabolism(majorityPercentageCoreMetabolism=80, colour=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of the diverged core metabolism.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism. This is individually true for both parent clade and child clade. The parent clade fully includes the child clade, therefore, the occurence of a substance-EC-product edge in the child clade’s core metabolism counts towards the percentage for the parent clade’s core metabolism. Meaning: if an EC number does not occur in the child clade’s core metabolism, it is unlikely that it will occur in the parent clade’s core metabolism, unless majorityPercentageCoreMetabolism is consecutively lowered towards 0.
  • colour (bool, optional) – If True, colours the lost EC edges in blue, and the added EC edges in red. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

The substance-EC graph representing the metabolic network which changed between the core metabolism of the parent (assumed older) and the core metabolism of the child (assumed younger).
Return type:

SubstanceEcGraph
Raises:
divergedMetabolismEnzymes(majorityPercentageCoreMetabolism=80, colour=False)[source]

Two Substance-Enzyme graphs derived from the diverged core metabolism, see divergedMetabolism().

First, the diverged core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the collective parent’s and child’s metabolism individually.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See divergedMetabolism().
  • colour (bool, optional) – If True, colours the lost enzyme edges in blue, and the added enzyme edges in red. When doing so, a single SubstanceEnzymeGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-Enzyme graphs calculated using the diverged EC numbers found by divergedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-Enzyme graph, coloured blue for parent and red for child.
Return type:

Tuple[SubstanceEnzymeGraph, SubstanceEnzymeGraph] or SubstanceEnzymeGraph
Raises:
divergedMetabolismGeneDuplicatedEnzymePairs(majorityPercentageCoreMetabolism=80) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

Pairs of gene-duplicated enzymes, derived from the diverged core metabolism.

First, the diverged core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the collective parent’s and child’s metabolism individually. Then, for parent and child, the gene-duplicated enzyme pairs are calculated. Finally, the gene-duplicated enzymes where both enzymes are in the conserved core metabolism are reported.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See divergedMetabolism().
  • colour (bool, optional) – If True, colours the lost enzyme edges in blue, and the added enzyme edges in red. Gene-duplicated enzyme edges of the parent are coloured in green, the ones of the child in yellow. When doing so, a single SubstanceEnzymeGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Sets of tuples of gene-duplicated enzyme pairs calculated using the diverged EC numbers found by divergedMetabolism().
Return type:

Set[Tuple[Enzyme, Enzyme]
Raises:
divergedMetabolismGeneDuplicatedEnzymes(majorityPercentageCoreMetabolism=80, colour=False)[source]

Two Substance-Enzyme graphs of gene-duplicated enzymes, derived from the diverged core metabolism.

First, the diverged core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the collective parent’s and child’s metabolism individually.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See divergedMetabolism().
  • colour (bool, optional) – If True, colours the lost enzyme edges in blue, and the added enzyme edges in red. Gene-duplicated enzyme edges of the parent are coloured in green, the ones of the child in yellow. When doing so, a single SubstanceEnzymeGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-Enzyme graphs calculated using the diverged EC numbers found by divergedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-Enzyme graph, coloured blue for parent and red for child.
Return type:

Tuple[SubstanceEnzymeGraph, SubstanceEnzymeGraph] or SubstanceEnzymeGraph
Raises:
divergedMetabolismNeofunctionalisedECs(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0, colour=False)[source]

Two Substance-EC graphs of “neofunctionalised” EC numbers, derived from the diverged core metabolism.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See divergedMetabolism().
  • colour (bool, optional) – If True, colours the lost EC edges in blue, and the added EC edges in red. “Neofunctionalised” EC edges of the parent are coloured in green, the ones of the child in yellow. When doing so, a single SubstanceEcGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-EC graphs calculated using the diverged EC numbers found by divergedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-EC graph, coloured blue for parent and red for child.
Return type:

Tuple[SubstanceEcGraph, SubstanceEcGraph] or SubstanceEcGraph
Raises:
divergedMetabolismNeofunctionalisedEnzymes(majorityPercentageCoreMetabolism=80, colour=False)[source]

Two Substance-Enzyme graphs of neofunctionalised enzymes, derived from the diverged core metabolism.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See divergedMetabolism().
  • colour (bool, optional) – If True, colours the lost enzyme edges in blue, and the added enzyme edges in red. Neofunctionalised enzyme edges of the parent are coloured in green, the ones of the child in yellow. When doing so, a single SubstanceEnzymeGraph is returned, not a Tuple. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

Tuple of two Substance-Enzyme graphs calculated using the diverged EC numbers found by divergedMetabolism(). The first graph is from the parent clade, the second graph from the child clade. If colour == True, returns a single Substance-Enzyme graph, coloured blue for parent and red for child.
Return type:

Tuple[SubstanceEnzymeGraph, SubstanceEnzymeGraph] or SubstanceEnzymeGraph
Raises:
lostMetabolism(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of the lost core metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – Every substance-EC-product edge has to occur in majorityPercentageCoreMetabolism % of organisms constituting the clade, to be included in the core metabolism. This is individually true for both parent clade and child clade. The parent clade fully includes the child clade, therefore, the occurence of a substance-EC-product edge in the child clade’s core metabolism counts towards the percentage for the parent clade’s core metabolism. Meaning: if an EC number does not occur in the child clade’s core metabolism, it is unlikely that it will occur in the parent clade’s core metabolism, unless majorityPercentageCoreMetabolism is consecutively lowered towards 0.
Returns:

The substance-EC graph representing the metabolic network which got lost from the core metabolism of the parent (assumed older) on the way to the core metabolism of the child (assumed younger).
Return type:

SubstanceEcGraph
Raises:
lostMetabolismEnzymes(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph derived from the lost core metabolism, see lostMetabolism().

First, the lost core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the parent’s enzyme metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See lostMetabolism().
Returns:

Substance-Enzyme graph of enzymes from the parent clade. Calculated using the lost EC numbers found by lostMetabolism().
Return type:

SubstanceEnzymeGraph
Raises:
lostMetabolismGeneDuplicatedEnzymePairs(majorityPercentageCoreMetabolism=80) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

Pairs of gene-duplicated enzymes, derived from the lost core metabolism.

First, the lost core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the parent’s enzyme metabolism. Then the gene-duplicated enzymes are calculated. Finally, the gene-duplicated enzyme pairs of the conserved core metabolism enzymes are reported.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See lostMetabolism().
Returns:

Pairs of enzymes from the parent clade. Calculated using the lost EC numbers found by lostMetabolism().
Return type:

Set[Tuple[Enzyme, Enzyme]]
Raises:
lostMetabolismGeneDuplicatedEnzymes(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph of gene-duplicated enzymes, derived from the lost core metabolism.

First, the lost core metabolism is calculated. Then, the enzymes associated with the added EC numbers are extracted from the parent’s enzyme metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See lostMetabolism().
Returns:

Substance-Enzyme graph of enzymes from the parent clade. Calculated using the lost EC numbers found by lostMetabolism().
Return type:

SubstanceEnzymeGraph
Raises:
lostMetabolismNeofunctionalisedECs(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of “neofunctionalised” EC numbers, derived from the lost core metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See lostMetabolism().
Returns:

Substance-EC graph of ECs from the parent clade. Calculated using the lost EC numbers found by lostMetabolism().
Return type:

SubstanceEcGraph
Raises:
lostMetabolismNeofunctionalisedEnzymes(majorityPercentageCoreMetabolism=80) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph of neofunctionalised enzymes, derived from the lost core metabolism.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See lostMetabolism().
Returns:

Substance-Enzyme graph of enzymes from the parent clade. Calculated using the lost EC numbers found by lostMetabolism().
Return type:

SubstanceEnzymeGraph
Raises:
parentNCBInames

All names/paths in NCBI taxonomy used to create the parent clade.

unifiedMetabolism(majorityPercentageCoreMetabolism=80, colour=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of the unified core metabolisms.

The lost metabolism of the parent is coloured in blue, the conserved metabolism of both in red, and the added metabolism of the child in pink. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the parent’s EC edges in blue, the child’s EC edges in red, and the shared EC edges in pink. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

The substance-EC graph representing the combined metabolic networks of both, child and parent. If colour == True, coloured differently for the lost, conserved, and added edges. Nodes are not coloured.
Return type:

SubstanceEcGraph
Raises:

See also

FEV_KEGG.Drawing.Export
Export the graph into a file, e.g. for visualisation in Cytoscape.
unifiedMetabolismEnzymes(majorityPercentageCoreMetabolism=80, colour=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph derived from the unified core metabolisms.

The lost metabolism of the parent is coloured in blue, the conserved metabolism of both in red, and the added metabolism of the child in pink. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the parent’s enzyme edges in blue, and the child’s enzyme edges in red. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

The substance-Enzyme graph representing the combined metabolic networks of both, child and parent. If colour == True, coloured differently for the lost, conserved, and added edges. Nodes are not coloured.
Return type:

SubstanceEnzymeGraph
Raises:
unifiedMetabolismGeneDuplicatedEnzymePairs(majorityPercentageCoreMetabolism=80) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

Pairs of gene-duplicated enzymes, derived from the unified core metabolisms.

Parameters:

majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
Returns:

Set of enzyme pairs representing the gene-duplicated enzymes of the combined metabolic networks of both, child and parent.
Return type:

Set[Tuple[Enzyme, Enzyme]
Raises:
unifiedMetabolismGeneDuplicatedEnzymes(majorityPercentageCoreMetabolism=80, colour=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph of gene-duplicated enzymes, derived from the unified core metabolisms.

The lost metabolism of the parent is coloured in blue, the conserved metabolism of both in red, and the added metabolism of the child in pink. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the parent’s enzyme edges in blue, and the child’s enzyme edges in red. Gene-duplicated enzyme edges of the parent are coloured in green, the ones of the child in yellow. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

The substance-Enzyme graph representing the combined metabolic networks of both, child and parent. If colour == True, coloured differently for the lost, conserved, and added edges. Nodes are not coloured.
Return type:

SubstanceEcGraph
Raises:
unifiedMetabolismNeofunctionalisedECs(majorityPercentageCoreMetabolism=80, majorityPercentageNeofunctionalisation=0, colour=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of “neofunctionalised” EC numbers, derived from the unified core metabolisms.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the parent’s EC edges in blue, and the child’s EC edges in red. “Neofunctionalised” EC edges of the parent are coloured in green, the ones of the child in yellow. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

The substance-EC graph representing the combined metabolic networks of both, child and parent. If colour == True, coloured differently for the lost, conserved, and added edges. Nodes are not coloured.
Return type:

SubstanceEcGraph
Raises:
unifiedMetabolismNeofunctionalisedEnzymes(majorityPercentageCoreMetabolism=80, colour=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph of neofunctionalised enzymes, derived from the unified core metabolisms.

Parameters:
  • majorityPercentageCoreMetabolism (int, optional) – See conservedMetabolism().
  • colour (bool, optional) – If True, colours the parent’s enzyme edges in blue, and the child’s enzyme edges in red. Neofunctionalised enzyme edges of the parent are coloured in green, the ones of the child in yellow. The colouring is realised by adding a ‘colour’ attribute to each edge. Nodes are not coloured.
Returns:

The substance-Enzyme graph representing the combined metabolic networks of both, child and parent. If colour == True, coloured differently for the lost, conserved, and added edges. Nodes are not coloured.
Return type:

SubstanceEcGraph
Raises:
class FEV_KEGG.Evolution.Clade.NestedCladePair(parent, child, excludeUnclassified=True)[source]

Bases: FEV_KEGG.Evolution.Clade.CladePair

Two clades in NCBI taxonomy, ‘child’ is assumed younger and must be nested somewhere inside ‘parent’.

This only checks nestedness for the first node found in taxonomy, by the first parent’s/child’s NCBI name, respectively. The latter being relevant if you pass a Clade, which has a list of NCBI names, or a list of NCBI names itself.

Parameters:
  • parent (str or List[str] or Clade) – Path(s) of the parent clade’s taxon, as defined by NCBI taxonomy, e.g. ‘Proteobacteria/Gammaproteobacteria’. Or a ready Clade object.
  • child (str or List[str] or Clade) – Path(s) of the child clade’s taxon, as defined by NCBI taxonomy, e.g. ‘Enterobacter’. Or a ready Clade object.
  • excludeUnclassified (bool, optional) – If True, ignore taxons with a path containing the string ‘unclassified’.
Variables:
  • self.childClade (Clade) –
  • self.parentClade (Clade) –
Raises:

ValueError – If parent or child are unknown taxons. Or if the child taxon is not actually a child of the parent taxon.
FEV_KEGG.Evolution.Clade.defaultEValue = 1e-15

Default threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.

FEV_KEGG.Evolution.Clade.defaultExcludeMultifunctionalEnzymes = True

If True, ignore enzymes with more than one EC number. This can be overridden in each relevant method’s excludeMultifunctionalEnzymes parameter in this module.

FEV_KEGG.Evolution.Clade.defaultExcludeUnclassified = True

If True, ignore taxons with a path containing the string ‘unclassified’. This can be overridden in each relevant method’s excludeUnclassified parameter in this module.

FEV_KEGG.Evolution.Clade.defaultMajorityPercentageCoreMetabolism = 80

Default percentage of organisms in the clade, which have to possess an EC number, for it to be included in the core metabolism of the clade. See FEV_KEGG.KEGG.Organism.Group.majorityEcGraph(). This can be overridden in each relevant method’s majorityPercentageCoreMetabolism parameter in this module.

FEV_KEGG.Evolution.Clade.defaultMajorityPercentageNeofunctionalisation = 0

Default percentage of organisms in the clade, which have to possess the same “neofunctionalised” EC number, for it to be included in the set of “neofunctionalised” EC numbers of the clade. See FEV_KEGG.KEGG.Evolution.Events.NeofunctionalisedECs. This can be overridden in each relevant method’s majorityPercentageNeofunctionalisation parameter in this module.

FEV_KEGG.Evolution.Clade.defaultOneOrganismPerSpecies = True

Default descision whether to use only the first organism for each species in NCBI taxonomy.

FEV_KEGG.Evolution.Comparison module
FEV_KEGG.Evolution.Comparison.getOrthologsWithinEnzymes(enzymes: Iterable[FEV_KEGG.Graph.Elements.Enzyme], eValue: float = 1e-15) → Dict[FEV_KEGG.Graph.Elements.Enzyme, Set[FEV_KEGG.Graph.Elements.Enzyme]][source]

Get orthologs within enzymes.

Parameters:
  • enzymes (Iterable[Enzyme]) – Enzymes among which to search for orthology.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

Dictionary of every enzyme in enzymes which has at least one ortholog in enzymes, pointing to a set of all its orthologs.
Return type:

Dict[Enzyme, Set[Enzyme]]
Raises:
  • ImpossiblyOrthologousError – If any gene ID in geneIDs is from comparisonOrganism.
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.

Warning

This operation has a worst-case complexity class of O(n(n+1)/2)! To make matters worse, each step involves at least one, if not several, network operations with KEGG SSDB/GENE, which are inherently slow. The best-case complexity class is still O(n-1).

FEV_KEGG.Evolution.Comparison.getOrthologsWithinGeneIDs(geneIDs: Iterable[FEV_KEGG.Graph.Elements.GeneID], eValue: float = 1e-15) → Dict[FEV_KEGG.Graph.Elements.GeneID, Set[FEV_KEGG.Graph.Elements.GeneID]][source]

Get orthologs within geneIDs.

Parameters:
  • geneIDs (Iterable[GeneID]) – Gene IDs among which to search for orthology.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

Dictionary of every gene in geneIDs which has at least one ortholog in geneIDs, pointing to a set of all its orthologs.
Return type:

Dict[GeneID, Set[GeneID]]
Raises:
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.

Warning

This operation has a worst-case complexity class of O(n(n+1)/2)! To make matters worse, each step involves at least one, if not several, network operations with KEGG SSDB/GENE, which are inherently slow. The best-case complexity class is O(n-1).

FEV_KEGG.Evolution.Events module
class FEV_KEGG.Evolution.Events.ChevronGeneDuplication(possiblyOrthologousOrganisms: Iterable[Organism] or KEGG.Organism.Group)[source]

Bases: FEV_KEGG.Evolution.Events.GeneDuplication

Evolutionary event of duplicating a gene, in dependence of a certain ancestoral bond.

The conditions for a ‘chevron’ gene duplication are:
  • The gene has at least one paralog.
  • The gene has at least one ortholog in a pre-defined set of organisms.

Chevron gene duplication extends simple gene duplication by limiting the possibly duplicated genes via a set of possibly orthologous organisms. In contrast to SimpleGeneDuplication, this class has to be instantiated, using the aforementioned set of possibly orthologous organisms.

Parameters:possiblyOrthologousOrganisms (Iterable[Organism] or Organism.Group) – Organisms which will be searched for the occurence of orthologs, i.e. are considered ancestoral.
Variables:self.possiblyOrthologousOrganisms (Iterable[Organism]) –
Raises:ValueError – If possiblyOrthologousOrganisms is of wrong type.

Warning

This takes much longer than SimpleGeneDuplication, because additionally, each found paralog is searched for an ortholog in all organisms of the other group. However, if you set returnMatches == False and ignoreDuplicatesOutsideSelf == False, the search is aborted with the very first ortholog, which is much faster than getting all orthologs. Because in this model even a single orthologous match is enough to prove gene duplication, we do not necessarily have to fully search all organisms.

filterEnzymes(substanceEnzymeGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph, eValue=1e-15, ignoreDuplicatesOutsideSelf=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Remove all enzymes from a graph which have not been gene-duplicated.

Parameters:
  • substanceEnzymeGraph (SubstanceEnzymeGraph) – Graph of enzymes to be checked for gene duplication.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • ignoreDuplicatesOutsideSelf (bool, optional) – If True, count only such enzymes as gene duplicated, which have at least one of their duplicates inside the set of enzymes searched for duplicates. This can, for example, serve to exclude duplicates in secondary metabolism.
Returns:

A copy of the substanceEnzymeGraph containing only enzymes which fulfil the conditions of this gene duplication definition.
Return type:

SubstanceEnzymeGraph
Raises:
  • ValueError – If any organism does not exist.
  • HTTPError – If any gene does not exist.
  • URLError – If connection to KEGG fails.
getEnzymePairs(enzymes: Set[FEV_KEGG.Graph.Elements.Enzyme], eValue=1e-15, ignoreDuplicatesOutsideSelf=False, geneIdToEnzyme=None) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

Get gene-duplicated enzymes, in pairs of duplicates.

If enzyme A is a duplicate of enzyme B and vice versa, this does not return duplicates, but returns only one pair, with the “smaller” enzyme as the first value. An enzyme is “smaller” if its gene ID string is “smaller”.

Parameters:
  • enzymes (Set[Enzyme] or SubstanceEnzymeGraph) – Set of enzymes to be checked for gene duplication, or a graph.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • ignoreDuplicatesOutsideSelf (bool, optional) – If True, count only such enzymes as gene duplicated, which have at least one of their duplicates inside the set of enzymes searched for duplicates. This can, for example, serve to exclude duplicates in secondary metabolism.
  • geneIdToEnzyme (Dict[GeneID, Enzyme], optional) – Dictionary for mapping each gene ID of every found duplicate to an enzyme object. If None, gets the enzyme from the database. This avoids the KeyError, but can cause a lot of network load.
Returns:

Set of pairs of gene-duplicated enzymes, realised as tuples. The order is arbitrary.
Return type:

Set[Tuple[Enzyme, Enzyme]]
Raises:

KeyError – If geneIdToEnzyme is passed, but does not contain the gene ID of every duplicate.
getEnzymes(enzymes: Set[FEV_KEGG.Graph.Elements.Enzyme], eValue=1e-15, returnMatches=False, ignoreDuplicatesOutsideSelf=False)[source]

Get gene-duplicated enzymes.

Parameters:
  • enzymes (Set[Enzyme] or SubstanceEnzymeGraph) – Set of enzymes to be checked for gene duplication, or a graph.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • returnMatches (bool, optional) – If True, return not only enzymes that have homologs, but also which homologs they have. Useful for filtering for relevant homologs afterwards.
  • ignoreDuplicatesOutsideSelf (bool, optional) – If True, count only such enzymes as gene duplicated, which have at least one of their duplicates inside the set of enzymes searched for duplicates. This can, for example, serve to exclude duplicates in secondary metabolism.
Returns:

If returnMatches == False, all enzymes in enzymes which fulfil the conditions of this gene duplication definition. If returnMatches == True, all enzymes in enzymes which fulfil the conditions of this gene duplication definition, pointing to a set of gene IDs of the found homologs.
Return type:

Set[Enzyme] or Dict[Element, Set[GeneID]]
Raises:
  • ValueError – If any organism does not exist.
  • HTTPError – If any gene does not exist.
  • URLError – If connection to KEGG fails.
class FEV_KEGG.Evolution.Events.FunctionChange(ecA: FEV_KEGG.Graph.Elements.EcNumber, ecB: FEV_KEGG.Graph.Elements.EcNumber)[source]

Bases: object

Possible evolutionary change of enzymatic function, from one EC number to another.

The direction of change, or if it really happened, can not be determined here! The order of EC numbers in this object is arbitrarily chosen to reflect their lexicographic order.

A function change resembles the possibility that the first EC number has evolutionarily changed into the second one. Or the other way around, since the direction of evolution can not be determined here. A function change can never have the same EC number twice, nor can the first be lexicographically “bigger” than the second, see the examples section.

Parameters:
  • ecA (EcNumber) –
  • ecB (EcNumber) – Must be lexicographically “bigger” than ecA. Can not be equal to ecA.
Raises:

ValueError – If ecA is lexicographically “bigger” than, or equal to, ecB.
classmethod fromNeofunctionalisation(neofunctionalisation: FEV_KEGG.Evolution.Events.Neofunctionalisation) → Set[FEV_KEGG.Evolution.Events.FunctionChange][source]

Create combinations of function changes from a neofunctionalisation.

Parameters:neofunctionalisation (Neofunctionalisation) –
Returns:Set of function changes which might have been caused by the neofunctionalisation.

Since an enzyme of a neofunctionalisation can have multiple EC numbers, all combinations of the two enzymes’ EC numbers are formed and treated as separate possible function changes.
Return type:Set[FunctionChange]

Examples

A: 1 B: 2 = (1, 2)

A: 1 B: 1, 2 = (1, 2)

A: 1, 2 B: 1, 3 = (1, 3) (1, 2) (2, 3)

A: 1, 2 B: 3, 4 = (1, 3) (1, 4) (2, 3) (2, 4)

A: 1, 2 B: 1, 2, 3 = (1, 3) (2, 3)

getDifferingEcLevels() → int[source]

Get the number of EC levels in which the EC numbers differ.

Returns:Number of differing EC levels between the two EC numbers, starting with the substrate-level. For example 1.2.3.4 and 1.2.3.7 returns 1, while 1.2.3.4 and 1.8.9.10 returns 3. However, wildcards do not match numbers: 1.2.3.4 and 1.2.3.- returns 1!
Return type:int
toHtml(short=False)[source]

Get the string representation as an HTML line.

class FEV_KEGG.Evolution.Events.GeneDuplication[source]

Bases: object

Abstract class for any type of gene duplication.

class FEV_KEGG.Evolution.Events.GeneFunctionAddition[source]

Bases: object

Evolutionary event of adding a gene function (EC number) between a pair of arbitrary ancestor and descendant.

The conditions for a gene function addition are:
  • The EC number has been added, from an unknown origin, along the way from an older group of organisms to a newer one.
static getECs(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get EC numbers which have been added between ancestor and descendant, existing only in the descendant.

Parameters:
Returns:

Set of EC numbers which occur in the descendant’s EC graph, but not in the ancestor’s, i.e. EC numbers which are new to the descendant.
Return type:

Set[EcNumber]
static getGraph(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Get graph containing EC numbers which have been added between ancestor and descendant, existing only in the descendant.

Parameters:
Returns:

Graph of EC numbers which occur in the descendant’s EC graph, but not in the ancestor’s, i.e. EC numbers which are new in the descendant. Substance-EC-product edges are only included if both graphs, ancestor and descendant, have both nodes, substrate and product.
Return type:

SubstanceEcGraph
class FEV_KEGG.Evolution.Events.GeneFunctionConservation[source]

Bases: object

Evolutionary event of conserving a gene function (EC number) between a pair of arbitrary ancestor and descendant.

The conditions for a gene function conservation are:
  • The EC number has been conserved, along the way from an older group of organisms to a newer one.
static getECs(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get EC numbers which have been conserved between ancestor and descendant, existing in both.

Parameters:
Returns:

Set of EC numbers which occur in the ancestor’s EC graph and in the decendants’s, i.e. EC numbers which are conserved in the descendant.
Return type:

Set[EcNumber]
static getGraph(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Get graph containing EC numbers which have been conserved between ancestor and descendant, existing in both.

Parameters:
Returns:

Graph of EC numbers which occur in the ancestor’s EC graph, and in the decendants’s, i.e. EC numbers which are conserved in the descendant. Substance-EC-product edges are only included if both graphs, ancestor and descendant, have both nodes, substrate and product.
Return type:

SubstanceEcGraph
class FEV_KEGG.Evolution.Events.GeneFunctionDivergence[source]

Bases: object

Evolutionary event of diverging (adding or losing) a gene function (EC number) between a pair of arbitrary ancestor and descendant.

The conditions for a gene function divergence are:
  • The EC number exists in an older group of organisms, but not in a newer one, or the other way around.
static getECs(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get EC numbers which have diverged between ancestor and descendant, existing only in either one of them.

Obviously, ancestorEcGraph and descendantEcGraph can be swapped here without changing the result.

Parameters:
Returns:

Set of EC numbers which occur in the ancestor’s EC graph, but not in the decendants’s and vice versa, i.e. EC numbers which only exist in either one of the organism groups.
Return type:

Set[EcNumber]
static getGraph(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Get graph containing EC numbers which have diverged between ancestor and descendant, existing only in either one of them.

Parameters:
Returns:

Graph of EC numbers which occur in the ancestor’s EC graph, but not in the decendants’s and vice versa, i.e. EC numbers which only exist in either one of the organism groups. Substance-EC-product edges are only included if both graphs, ancestor and descendant, have both nodes, substrate and product.
Return type:

SubstanceEcGraph
class FEV_KEGG.Evolution.Events.GeneFunctionLoss[source]

Bases: object

Evolutionary event of losing a gene function (EC number) between a pair of arbitrary ancestor and descendant.

The conditions for a gene function loss are:
  • The EC number has been lost, along the way from an older group of organisms to a newer one.
static getECs(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get EC numbers which have been lost between ancestor and descendant, existing only in the ancestor.

Parameters:
Returns:

Set of EC numbers which occur in the ancestor’s EC graph, but not in the decendants’s, i.e. EC numbers which are lost to the descendant.
Return type:

Set[EcNumber]
static getGraph(ancestorEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, descendantEcGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Get graph containing EC numbers which have been lost between ancestor and descendant, existing only in the ancestor.

Parameters:
Returns:

Graph of EC numbers which occur in the ancestor’s EC graph, but not in the decendants’s, i.e. EC numbers which are lost in the descendant. Substance-EC-product edges are only included if both graphs, ancestor and descendant, have both nodes, substrate and product.
Return type:

SubstanceEcGraph
class FEV_KEGG.Evolution.Events.Neofunctionalisation(enzymeA: FEV_KEGG.Graph.Elements.Enzyme, enzymeB: FEV_KEGG.Graph.Elements.Enzyme)[source]

Bases: object

Evolutionary event of Neofunctionalisation between a pair of enzymes.

The conditions for a neofunctionalisation are:
  • The enzyme’s gene has been duplicated, according to a certain class of GeneDuplication.
  • The duplicated enzyme is associated with a different EC number than its duplicate.

The order of the two enzymes has no meaning, it has been arbitrarily chosen to reflect the lexicographic order of their associated EC numbers. The enzyme posessing the “smallest” EC number comes first. This absolute ordering prevents duplicate events, because without an order there would have always been a second event with the exact same enzymes, but in swapped positions, because neofunctionalisation has no direction here and is, thus, symmetric.

Parameters:
  • enzymeA (Enzyme) – An enzyme, which is a gene duplicate of enzymeB. The order is arbitrary.
  • enzymeB (Enzyme) – An enzyme, which is a gene duplicate of enzymeA. The order is arbitrary.
Variables:

self.enzymePair (Tuple[Enzyme, Enzyme]) – Tuple of the two enzymes, sorted by the lexicographic order of their “smallest” EC number.
Raises:

ValueError – If the enzymes are equal, have the same set of EC numbers, or one has no EC number.
getDifferingEcLevels() → int[source]

Get the maximum number of EC levels in which the enzymes’ EC numbers differ.

Returns:Number of differing EC levels between the two enzymes’ EC numbers, starting with the substrate-level. If an enzyme has multiple EC numbers, returns the biggest difference. For example 1.2.3.4 and 1.2.3.7 returns 1, while 1.2.3.4 and 1.8.9.10 returns 3. However, wildcards do not match numbers: 1.2.3.4 and 1.2.3.- returns 1!
Return type:int
getEcNumbers() → Tuple[Set[FEV_KEGG.Graph.Elements.EcNumber], Set[FEV_KEGG.Graph.Elements.EcNumber]][source]

Get the enzymes’ EC numbers.

Returns:Same order as in getEnzymes(). Because an enzyme could have multiple EC numbers, they are given as sets.
Return type:Tuple[Set[EcNumber], Set[EcNumber]]
getEnzymes() → Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme][source]

Get the pair of enzymes.

Returns:
Return type:Tuple[Enzyme, Enzyme]
isSameEcReaction() → bool[source]

Whether the enzymes’ EC numbers describe a different reaction, or merely a different substrate

Returns:True, if the biggest difference in EC levels of the two enzymes is still on the fourth (substrate) level.
Return type:bool
toHtml(short=False)[source]

Get the string representation as an HTML line.

class FEV_KEGG.Evolution.Events.NeofunctionalisedECs(neofunctionalisedEnzymes: FEV_KEGG.Evolution.Events.NeofunctionalisedEnzymes)[source]

Bases: object

EC numbers which are affected by neofunctionalisation events.

Parameters:neofunctionalisedEnzymes (NeofunctionalisedEnzymes) – Neofunctionalisation events among certain enzymes.
colourGraph(ecGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, colour: FEV_KEGG.Drawing.Export.Colour = <Colour.GREEN: '#55FF55'>, minimumEcDifference: int = None, minimumOrganismsCount: int = None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Colour EC graph’s “neofunctionalised” EC number edges.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each EC number. If None, there is no filtering due to organism involvement. This sums the occurences of organisms across function changes, for each EC number the function changes overlap with. Hence, it is much less likely that a neofunctionalisation is filtered, compared to filtering per function change. For example, the function change 1->2 is associated with two neofunctionalisations ‘eco:12345’->’eco:69875’ and ‘obc:76535’->’abc:41356’, this involves three organisms in total (eco, obc, abc). Also, the function change 1->3 involves two organisms (‘eco:53235’->’iuf:34587’). If minimumOrganismsCount == 4, neither 1->2, nor 1->3 are reported. However, if we look at single EC numbers, 1 is involved in function changes affecting four organisms (eco, obc, abc, iuf). Thus, 1 would be reported here, but neither 2 nor 3.
Returns:

A copy of ecGraph in which edges with “neofunctionalised” ECs as key have an additional colour attribute, see FEV_KEGG.Drawing.Export.addColourAttribute().
Return type:

SubstanceEcGraph
filterGraph(ecGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph, minimumEcDifference: int = None, minimumOrganismsCount: int = None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Filter EC graph to only contain “neofunctionalised” EC numbers.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each EC number. If None, there is no filtering due to organism involvement. This sums the occurences of organisms across function changes, for each EC number the function changes overlap with. Hence, it is much less likely that a neofunctionalisation is filtered, compared to filtering per function change. For example, the function change 1->2 is associated with two neofunctionalisations ‘eco:12345’->’eco:69875’ and ‘obc:76535’->’abc:41356’, this involves three organisms in total (eco, obc, abc). Also, the function change 1->3 involves two organisms (‘eco:53235’->’iuf:34587’). If minimumOrganismsCount == 4, neither 1->2, nor 1->3 are reported. However, if we look at single EC numbers, 1 is involved in function changes affecting four organisms (eco, obc, abc, iuf). Thus, 1 would be reported here, but neither 2 nor 3.
Returns:

A copy of ecGraph, leaving only edges with a “neofunctionalised” EC as key.
Return type:

SubstanceEcGraph
getECs(minimumEcDifference: int = None, minimumOrganismsCount: int = None) → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get EC numbers participating in the change of function due to neofunctionalisations.

They could also be called “neofunctionalised” EC numbers.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each EC number. If None, there is no filtering due to organism involvement. This sums the occurences of organisms across function changes, for each EC number the function changes overlap with. Hence, it is much less likely that a neofunctionalisation is filtered, compared to filtering per function change. For example, the function change 1->2 is associated with two neofunctionalisations ‘eco:12345’->’eco:69875’ and ‘obc:76535’->’abc:41356’, this involves three organisms in total (eco, obc, abc). Also, the function change 1->3 involves two organisms (‘eco:53235’->’iuf:34587’). If minimumOrganismsCount == 4, neither 1->2, nor 1->3 are reported. However, if we look at single EC numbers, 1 is involved in function changes affecting four organisms (eco, obc, abc, iuf). Thus, 1 would be reported here, but neither 2 nor 3.
Returns:

Set of EC numbers which are part of function changes which possibly happened due to neofunctionalisations.
Return type:

Set[EcNumber]
getEnzymesForEC(minimumEcDifference: int = None, minimumOrganismsCount: int = None) → Dict[FEV_KEGG.Graph.Elements.EcNumber, Set[FEV_KEGG.Graph.Elements.Enzyme]][source]

Get enzymes of neofunctionalisations, keyed by an EC number of a possible function change.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each EC number. If None, there is no filtering due to organism involvement. This sums the occurences of organisms across function changes, for each EC number the function changes overlap with. Hence, it is much less likely that a neofunctionalisation is filtered, compared to filtering per function change. For example, the function change 1->2 is associated with two neofunctionalisations ‘eco:12345’->’eco:69875’ and ‘obc:76535’->’abc:41356’, this involves three organisms in total (eco, obc, abc). Also, the function change 1->3 involves two organisms (‘eco:53235’->’iuf:34587’). If minimumOrganismsCount == 4, neither 1->2, nor 1->3 are reported. However, if we look at single EC numbers, 1 is involved in function changes affecting four organisms (eco, obc, abc, iuf). Thus, 1 would be reported here, but neither 2 nor 3.
Returns:

Dictionary of EC numbers, pointing to a set of enzymes involved in the neofunctionalisations which might have caused the function changes the EC number is part of. This can lead to many duplicated enzymes.
Return type:

Dict[EcNumber, Set[Enzyme]]
getEnzymesForFunctionChange(minimumEcDifference: int = None, minimumOrganismsCount: int = None) → Dict[FEV_KEGG.Evolution.Events.FunctionChange, Set[FEV_KEGG.Graph.Elements.Enzyme]][source]

Get enzymes of neofunctionalisations, keyed by a possible change of function.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each function change. If None, there is no filtering due to organism involvement. For example, the function change 1->2 is associated with two neofunctionalisations ‘eco:12345’->’eco:69875’ and ‘obc:76535’->’abc:41356’, this involves three organisms in total (eco, obc, abc), finally, if minimumOrganismsCount <= 3, the function change 1->2 is returned.
Returns:

Dictionary of function changes, pointing to a set of enzymes involved in the neofunctionalisations which might have caused the function change. This can lead to many duplicated enzymes.
Return type:

Dict[FunctionChange, Set[Enzyme]]
getFunctionChanges(minimumEcDifference: int = None, minimumOrganismsCount: int = None) → Set[FEV_KEGG.Evolution.Events.FunctionChange][source]

Get all possible changes of function between the two enzymes of every neofunctionalisation.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each function change. If None, there is no filtering due to organism involvement.
Returns:

Set of all function changes, which meet the criteria.
Return type:

Set[FunctionChange]
getNeofunctionalisationsForEC(minimumEcDifference: int = None, minimumOrganismsCount: int = None) → Dict[FEV_KEGG.Graph.Elements.EcNumber, Set[FEV_KEGG.Evolution.Events.Neofunctionalisation]][source]

Get neofunctionalisation events, keyed by an EC number participating in the change of function between the two enzymes.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each EC number. If None, there is no filtering due to organism involvement. This sums the occurences of organisms across function changes, for each EC number the function changes overlap with. Hence, it is much less likely that a neofunctionalisation is filtered, compared to filtering per function change. For example, the function change 1->2 is associated with two neofunctionalisations ‘eco:12345’->’eco:69875’ and ‘obc:76535’->’abc:41356’, this involves three organisms in total (eco, obc, abc). Also, the function change 1->3 involves two organisms (‘eco:53235’->’iuf:34587’). If minimumOrganismsCount == 4, neither 1->2, nor 1->3 are reported. However, if we look at single EC numbers, 1 is involved in function changes affecting four organisms (eco, obc, abc, iuf). Thus, 1 would be reported here, but neither 2 nor 3.
Returns:

Dictionary of EC numbers which are part of function changes, pointing to a set of neofunctionalisations which might have caused them. Very likely has duplicated neofunctionalisations, because there are always at least two EC numbers involved in a neofunctionalisation.
Return type:

Dict[EcNumber, Set[Neofunctionalisation]]
getNeofunctionalisationsForFunctionChange(minimumEcDifference: int = None, minimumOrganismsCount: int = None) → Dict[FEV_KEGG.Evolution.Events.FunctionChange, Set[FEV_KEGG.Evolution.Events.Neofunctionalisation]][source]

Get neofunctionalsation events, keyed by a change of function between the two enzymes.

Parameters:
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
  • minimumOrganismsCount (int, optional) – Minimum number of organisms which have to be involved in the neofunctionalisations of each function change. If None, there is no filtering due to organism involvement. For example, the function change 1->2 is associated with two neofunctionalisations ‘eco:12345’->’eco:69875’ and ‘obc:76535’->’abc:41356’, this involves three organisms in total (eco, obc, abc), finally, if minimumOrganismsCount <= 3, the function change 1->2 is returned.
Returns:

Dictionary of function changes, pointing to a set of neofunctionalisations which might have caused them.

Since an enzyme of a neofunctionalisation can have multiple EC numbers, all combinations of the two enzymes’ EC numbers are formed and treated as separate possible function changes. The neofunctionalisation is then saved again for each function change, which obviously leads to duplicated neofunctionalisation objects.
Return type:

Dict[FunctionChange, Set[Neofunctionalisation]]

Examples

A: 1 B: 2 = (1, 2)

A: 1 B: 1, 2 = (1, 2)

A: 1, 2 B: 1, 3 = (1, 3) (1, 2) (2, 3)

A: 1, 2 B: 3, 4 = (1, 3) (1, 4) (2, 3) (2, 4)

A: 1, 2 B: 1, 2, 3 = (1, 3) (2, 3)

class FEV_KEGG.Evolution.Events.NeofunctionalisedEnzymes(enzymes: Set[FEV_KEGG.Graph.Elements.Enzyme], geneDuplicationModel: FEV_KEGG.Evolution.Events.GeneDuplication, eValue=1e-15, ignoreDuplicatesOutsideSet: bool = True)[source]

Bases: object

Neofunctionalisation events among certain enzymes.

Parameters:
  • enzymes (Set[Enzyme]) – Enzymes among which to test for neofunctionalisation. Neofunctionalisations involving enzymes outside this set are not reported.
  • geneDuplicationModel (GeneDuplication) – The model of gene duplication to use.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • ignoreDuplicatesOutsideSet (bool, optional) – If True, any neofunctionalisation involving an enzyme outside the enzymes set is not reported. This helps to exclude secondary metabolism when examining core metabolism.
Raises:

ValueError – If a gene duplication model is used which requires instantiation, but only its class was given.
colourGraph(enzymeGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph, colour: FEV_KEGG.Drawing.Export.Colour = <Colour.GREEN: '#55FF55'>, minimumEcDifference: int = None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Colour enzyme graph’s neofunctionalised enzyme edges.

Parameters:
  • enzymeGraph (SubstanceEnzymeGraph) – The enzyme graph to colour.
  • colour (Export.Colour, optional) – The colour to use for edges with neofunctionalised enzymes as key.
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
Returns:

A copy of enzymeGraph in which edges with neofunctionalised enzymes as key have an additional colour attribute, see FEV_KEGG.Drawing.Export.addColourAttribute().
Return type:

SubstanceEnzymeGraph
filterGraph(enzymeGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph, minimumEcDifference: int = None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Filter enzyme graph to only contain neofunctionalised enzymes.

Parameters:
  • enzymeGraph (SubstanceEnzymeGraph) – The enzyme graph to filter.
  • minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
Returns:

A copy of enzymeGraph, leaving only edges with a neofunctionalised enzyme as key.
Return type:

SubstanceEnzymeGraph
getEnzymes(minimumEcDifference: int = None) → Set[FEV_KEGG.Graph.Elements.Enzyme][source]

Get all neofunctionalised enzymes.

Parameters:minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
Returns:Set of all possibly neofunctionalised enzymes, regardless of the real direction of neofunctionalisation, which we can not determine here.
Return type:Set[Enzyme]
getNeofunctionalisations(minimumEcDifference: int = None) → Set[FEV_KEGG.Evolution.Events.Neofunctionalisation][source]

Get neofunctionalisation events between two enzymes each.

Parameters:minimumEcDifference (int, optional) – May only be one of [1, 2, 3, 4]. If None or 1, all neofunctionalisations are returned. If > 1, return only neofunctionalisations in which the EC numbers differ in more than the minimumEcDifference lowest levels. They then describe a different reaction, instead of only a different substrate. For example, minimumEcDifference == 2 means that 1.2.3.4/1.2.3.5 is not reported, while 1.2.3.4/1.2.5.6 is.
Returns:Set of possible neofunctionalisation events.
Return type:Set[Neofunctionalisation]
class FEV_KEGG.Evolution.Events.SimpleGeneDuplication[source]

Bases: FEV_KEGG.Evolution.Events.GeneDuplication

Evolutionary event of duplicating a gene, regardless of ancestoral bonds.

The conditions for a ‘simple’ gene duplication are:
  • The gene has at least one paralog.
classmethod filterEnzymes(substanceEnzymeGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph, eValue=1e-15, ignoreDuplicatesOutsideSet=None, preCalculatedEnzymes=None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Remove all enzymes from a graph which have not been gene-duplicated.

Parameters:
  • substanceEnzymeGraph (SubstanceEnzymeGraph) – Graph of enzymes to be checked for gene duplication.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • ignoreDuplicatesOutsideSet (Set[GeneID] or True, optional) – If None, report all found duplicates. If True, automatically restrict to all enzymes in substanceEnzymeGraph. If a set, count only such enzymes as gene duplicated, which have at least one of their duplicates inside this set. Beware, the set has to contain the enzymes’ gene ID! This can, for example, serve to exclude duplicates in secondary metabolism.
Returns:

A copy of the substanceEnzymeGraph containing only enzymes which fulfil the conditions of this gene duplication definition.
Return type:

SubstanceEnzymeGraph
Raises:
  • ValueError – If any organism does not exist.
  • HTTPError – If any gene does not exist.
  • URLError – If connection to KEGG fails.
classmethod getEnzymePairs(enzymes: Set[FEV_KEGG.Graph.Elements.Enzyme], eValue=1e-15, ignoreDuplicatesOutsideSet=None, geneIdToEnzyme=None, preCalculatedEnzymes=None) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

Get gene-duplicated enzymes, in pairs of duplicates.

If enzyme A is a duplicate of enzyme B and vice versa, this does not return duplicates, but returns only one pair, with the “smaller” enzyme as the first value. An enzyme is “smaller” if its gene ID string is “smaller”.

Parameters:
  • enzymes (Set[Enzyme] or SubstanceEnzymeGraph) – Set of enzymes to be checked for gene duplication, or a graph.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • ignoreDuplicatesOutsideSet (Set[GeneID] or True, optional) – If None, report all found duplicates. If True, automatically restrict to all enzymes in substanceEnzymeGraph. If a set, count only such enzymes as gene duplicated, which have at least one of their duplicates inside this set. Beware, the set has to contain the enzymes’ gene ID! This can, for example, serve to exclude duplicates in secondary metabolism.
  • geneIdToEnzyme (Dict[GeneID, Enzyme], optional) – Dictionary for mapping each gene ID of every found duplicate to an enzyme object. If None, gets the enzyme from the database. This avoids the KeyError, but can cause a lot of network load.
Returns:

Set of pairs of gene-duplicated enzymes, realised as tuples. The order is arbitrary.
Return type:

Set[Tuple[Enzyme, Enzyme]]
Raises:

KeyError – If geneIdToEnzyme is passed, but does not contain the gene ID of every duplicate.
static getEnzymes(enzymes: Set[FEV_KEGG.Graph.Elements.Enzyme], eValue=1e-15, returnMatches=False, ignoreDuplicatesOutsideSet=None, preCalculatedEnzymes=None)[source]

Get gene-duplicated enzymes.

Parameters:
  • enzymes (Set[Enzyme] or SubstanceEnzymeGraph) – Set of enzymes to be checked for gene duplication, or a graph.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • returnMatches (bool, optional) – If True, return not only enzymes that have homologs, but also which homologs they have. Useful for filtering for relevant homologs afterwards.
  • ignoreDuplicatesOutsideSet (Set[GeneID] or True, optional) – If None, report all found duplicates. If True, automatically restrict to all enzymes in substanceEnzymeGraph. If a set, count only such enzymes as gene duplicated, which have at least one of their duplicates inside this set. Beware, the set has to contain the enzymes’ gene ID! This can, for example, serve to exclude duplicates in secondary metabolism.
Returns:

If returnMatches == False, all enzymes in enzymes which fulfil the conditions of this gene duplication definition. If returnMatches == True, all enzymes in enzymes which fulfil the conditions of this gene duplication definition, pointing to a set of gene IDs of the found homologs.
Return type:

Set[Enzyme] or Dict[Element, Set[GeneID]]
Raises:
  • ValueError – If any organism does not exist.
  • HTTPError – If any gene does not exist.
  • URLError – If connection to KEGG fails.
class FEV_KEGG.Evolution.Events.SimpleGroupGeneDuplication(sameGroupOrganisms: Iterable[Organism] or KEGG.Organism.Group)[source]

Bases: FEV_KEGG.Evolution.Events.GeneDuplication

Evolutionary event of duplicating a gene, regardless of ancestoral bonds in the comparison group.

The conditions for a ‘simple group’ gene duplication are:
  • The gene has at least one homolog within the set of organisms its organism belongs to.

Simple group gene duplication extends simple gene duplication by expanding the term ‘paralog’ to every organism in the set of organisms the gene’s organism blongs to. In contrast to SimpleGeneDuplication, this class has to be instantiated, using the aforementioned set of organisms belonging to each other. This would usually be a FEV_KEGG.KEGG.Organism.Group of the same FEV_KEGG.Evolution.Clade.Clade.

Parameters:sameGroupOrganisms (Iterable[Organism] or Organism.Group) – Organisms which will be searched for the occurence of homologs, i.e. are considered “semi-paralogously” related.
Variables:self.sameGroupOrganisms (Iterable[Organism]) –
Raises:ValueError – If sameGroupOrganisms is of wrong type.

Warning

This takes much longer than SimpleGeneDuplication, because each sought gene is compared between all organisms of the same group, not only within its own organism.

filterEnzymes(substanceEnzymeGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph, eValue=1e-15) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Remove all enzymes from a graph which have not been gene-duplicated.

Parameters:
  • substanceEnzymeGraph (SubstanceEnzymeGraph) – Graph of enzymes to be checked for gene duplication.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

A copy of the substanceEnzymeGraph containing only enzymes which fulfil the conditions of this gene duplication definition.
Return type:

SubstanceEnzymeGraph
Raises:
  • ValueError – If any organism does not exist.
  • HTTPError – If any gene does not exist.
  • URLError – If connection to KEGG fails.
getEnzymePairs(enzymes: Set[FEV_KEGG.Graph.Elements.Enzyme], eValue=1e-15, ignoreDuplicatesOutsideSet=None, geneIdToEnzyme=None) → Set[Tuple[FEV_KEGG.Graph.Elements.Enzyme, FEV_KEGG.Graph.Elements.Enzyme]][source]

Get gene-duplicated enzymes, in pairs of duplicates.

If enzymeA is a duplicate of enzymeB and vice versa, this returns symmetric duplicates of the form (enzymeA, enzymeB) and (enzymeB, enzymeA).

Parameters:
  • enzymes (Set[Enzyme] or SubstanceEnzymeGraph) – Set of enzymes to be checked for gene duplication, or a graph.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • ignoreDuplicatesOutsideSet (Set[GeneID], optional) – If None, report all found duplicates. If not None, count only such enzymes as gene duplicated, which have at least one of their duplicates inside this set. This can, for example, serve to exclude duplicates in secondary metabolism.
  • geneIdToEnzyme (Dict[GeneID, Enzyme], optional) – Dictionary for mapping each gene ID of every found duplicate to an enzyme object. If None, gets the enzyme from the database. This avoids the KeyError, but can cause a lot of network load.
Returns:

Set of pairs of gene-duplicated enzymes, realised as tuples. The order is arbitrary and there will almost certainly be 100% duplicates.
Return type:

Set[Tuple[Enzyme, Enzyme]]
Raises:

KeyError – If geneIdToEnzyme is passed, but does not contain the gene ID of every duplicate.
getEnzymes(enzymes: Set[FEV_KEGG.Graph.Elements.Enzyme], eValue=1e-15, returnMatches=False, ignoreDuplicatesOutsideSet=None)[source]

Get gene-duplicated enzymes.

Parameters:
  • enzymes (Set[Enzyme] or SubstanceEnzymeGraph) – Set of enzymes to be checked for gene duplication, or a graph.
  • eValue (float, optional) – Threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • returnMatches (bool, optional) – If True, return not only enzymes that have homologs, but also which homologs they have. Useful for filtering for relevant homologs afterwards.
  • ignoreDuplicatesOutsideSet (Set[GeneID], optional) – If None, report all found duplicates. If not None, count only such enzymes as gene duplicated, which have at least one of their duplicates inside this set. This can, for example, serve to exclude duplicates in secondary metabolism.
Returns:

If returnMatches == False, all enzymes in enzymes which fulfil the conditions of this gene duplication definition. If returnMatches == True, all enzymes in enzymes which fulfil the conditions of this gene duplication definition, pointing to a set of gene IDs of the found homologs.
Return type:

Set[Enzyme] or Dict[Element, Set[GeneID]]
Raises:
  • ValueError – If any organism does not exist.
  • HTTPError – If any gene does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.Evolution.Events.defaultEValue = 1e-15

Default threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant. This can be overridden in each relevant method’s eValue parameter in this module.

FEV_KEGG.Evolution.LUCA module
class FEV_KEGG.Evolution.LUCA.CoreLUCA(clade: FEV_KEGG.Evolution.LUCA.CoreLUCA.CladeType)[source]

Bases: object

Last Universal Common Ancestor by intersection of many or all organisms in KEGG.

This is the Last Universal Common Ancestor, as defined by a common “core metabolism” shared among all organisms known to KEGG within a certain NCBI top-clade. This would include Bacteria, Arachaea, and Eukaryota; which is a very big data set! Alternatively, you can specify which isolated top-clade to use, using clade, e.g. yielding the Bacteria-LUCA, or Archaea-LUCA. For each species only the first organism is considered, to prevent statistical overrepresentation.

Conversion into another type of graph is not supported, because LUCA is a strictly hypothetical organism without any exactly known genes.

Parameters:

clade (CoreLUCA.CladeType) – Which clade to use for defining a LUCA. Using ‘archae’ obviously only gives an Archae-LUCA, not the “true” LUCA, etc.
Variables:
Raises:
  • HTTPError – If any underlying organism, pathway, or gene does not exist.
  • URLError – If connection to KEGG fails.

Warning

This function takes hours to days to complete, and requires several gigabytes of memory, disk space, and network traffic!

class CladeType[source]

Bases: enum.Enum

Possible types of CoreLUCA.

Each accordings to a single, or a combination of, top-clades of NCBI. Only the ‘universal’ clade gives you the “true” LUCA.

archaea = '/Archaea'
archaeaBacteria = ['/Archaea', '/Bacteria']
archaeaEukaryota = ['/Archaea', '/Eukaryota']
bacteria = '/Bacteria'
bacteriaEukaryota = ['/Bacteria', '/Eukaryota']
eukaryota = '/Eukaryota'
universal = '/'
collectiveMetabolism() → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

CoreLUCA’s collective metabolism, i.e. core metabolism with the lowest possible majorityPercentage value.

Returns:Contains all substrates/products and all EC numbers of any organism in the top-clade you chose.
Return type:SubstanceEcGraph
coreMetabolism(majorityPercentage) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

CoreLUCA’s core metabolism.

Parameters:majorityPercentage (float) – Percentage for determining how many organisms have to possess an EC edge, for it to be included in this ‘core metabolism’.
Returns:Contains all substrates/products and all EC numbers in the “core metabolism” of the top-clade you chose.
Return type:SubstanceEcGraph
class FEV_KEGG.Evolution.LUCA.GoldmanLUCA[source]

Bases: object

Last Universal Common Ancestor by Goldman et al.

This is the Last Universal Common Ancestor, as described in [1]. The original work on LUCA, however, does not specify enzyme function, but merely COGs [3]. This class already contains the list of LUCA’s enzymes from the above paper, as depicted in the first table of said paper [2]. As the most plausible minimal set of enzymatic functions, the authors chose the intersection of EC numbers found in universal sequence + structure, combined with the ones found in universal sequence + structure + function. See the original source for details.

This list is parsed and converted into a SubstanceEcGraph. Conversion is done by using the graph of a hypothetical ‘complete’ organism - NUKA - which possesses all EC numbers known to all metabolic KEGG pathways, see FEV_KEGG.KEGG.NUKA All EC numbers not present in LUCA are filtered out. Keep in mind, though, that LUCA’s EC numbers only contain three levels, to more adequately model the likely patchwork evolution in ancient times. Therefore, all EC numbers starting with the sub-class remain, regardless of substrate specificity.

Conversion into another type of graph is not supported, because LUCA is a strictly hypothetical organism without any exactly known genes.

Variables:self.nameAbbreviation (str) –

References

[1]Goldman et al. (2012), “The Enzymatic and Metabolic Capabilities of Early Life”, https://doi.org/10.1371/journal.pone.0039912
[2]Goldman et al. (2012), Table 1, https://doi.org/10.1371/journal.pone.0039912.t001
[3]Mirkin et al. (2003), “Algorithms for computing parsimonious evolutionary scenarios for genome evolution, the last universal common ancestor and dominance of horizontal gene transfer in the evolution of prokaryotes”, https://doi.org/10.1186/1471-2148-3-2
ecNumbers

GoldmanLUCA’s EC numbers.

Generalised to the first three levels. The last level is always a wildcard.

Returns:Set of the EC numbers predicted by Goldman et al. to belong to LUCA.
Return type:Set[EcNumber]
substanceEcGraph

GoldmanLUCA’s substance-EC graph.

Returns:

Contains all substrates/products and all EC numbers in FEV_KEGG.KEGG.NUKA filtered by the EC numbers predicted by Goldman et al. for LUCA.
Return type:

SubstanceEcGraph
Raises:
  • HTTPError – If any underlying organism, pathway, or gene of NUKA does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.Evolution.Taxonomy module
class FEV_KEGG.Evolution.Taxonomy.KEGG(rawLines, isNCBI)[source]

Bases: FEV_KEGG.Evolution.Taxonomy.Taxonomy

The taxonomy of organisms in KEGG, following KEGG’s own scheme: http://www.kegg.jp/kegg-bin/get_htext?br08601.keg

Generic taxonomy of organisms in KEGG.

Parameters:
  • rawLines (List[str]) – List of lines making up the raw data of a known taxonomy, either NCBI or KEGG.
  • isNCBI (bool) – If True, rawLines is parsed as NCBI taxonomy. If False, rawLines is parsed as KEGG taxonomy.
Variables:
  • self.indexOnAbbreviation (Dict[str, anytree.node.node.Node]) – Index to find a anytree.node.node.Node for an organism abbreviation, with .type == TaxonType.ORGANISM.
  • self.tree (anytree.node.node.Node) – The root node of the taxonomy, with .type == TaxonType.ROOT.
static getTaxonomy() → FEV_KEGG.Evolution.Taxonomy.Taxonomy[source]

Downloads and parses raw taxonomy from KEGG into an anytree object.

Returns:KEGG taxonomy.
Return type:Taxonomy
Raises:URLError – If connection to KEGG fails.
class FEV_KEGG.Evolution.Taxonomy.NCBI(rawLines, isNCBI)[source]

Bases: FEV_KEGG.Evolution.Taxonomy.Taxonomy

The taxonomy of organisms in KEGG, following the NCBI scheme: http://www.kegg.jp/kegg-bin/get_htext?br08610.keg

Generic taxonomy of organisms in KEGG.

Parameters:
  • rawLines (List[str]) – List of lines making up the raw data of a known taxonomy, either NCBI or KEGG.
  • isNCBI (bool) – If True, rawLines is parsed as NCBI taxonomy. If False, rawLines is parsed as KEGG taxonomy.
Variables:
  • self.indexOnAbbreviation (Dict[str, anytree.node.node.Node]) – Index to find a anytree.node.node.Node for an organism abbreviation, with .type == TaxonType.ORGANISM.
  • self.tree (anytree.node.node.Node) – The root node of the taxonomy, with .type == TaxonType.ROOT.
static getTaxonomy() → FEV_KEGG.Evolution.Taxonomy.Taxonomy[source]

Downloads and parses raw taxonomy from KEGG into an anytree object.

Returns:NCBI taxonomy.
Return type:Taxonomy
Raises:URLError – If connection to KEGG fails.
class FEV_KEGG.Evolution.Taxonomy.TaxonType[source]

Bases: enum.Enum

Type of a taxon.

ORGANISM = 1

Organism taxon, i.e. a leaf with a unique sequenced genome.

OTHER = 3

Other taxon, i.e. any other taxonomic rank in between.

ROOT = 0

Root taxon, i.e. ‘/’.

SPECIES = 2

Species taxon, e.g. ‘Escherichia Coli’.

class FEV_KEGG.Evolution.Taxonomy.Taxonomy(rawLines, isNCBI)[source]

Bases: object

Generic taxonomy of organisms in KEGG.

Parameters:
  • rawLines (List[str]) – List of lines making up the raw data of a known taxonomy, either NCBI or KEGG.
  • isNCBI (bool) – If True, rawLines is parsed as NCBI taxonomy. If False, rawLines is parsed as KEGG taxonomy.
Variables:
  • self.indexOnAbbreviation (Dict[str, anytree.node.node.Node]) – Index to find a anytree.node.node.Node for an organism abbreviation, with .type == TaxonType.ORGANISM.
  • self.tree (anytree.node.node.Node) – The root node of the taxonomy, with .type == TaxonType.ROOT.
getOrganismAbbreviations(nodes: Iterable[anytree.node.node.Node]) → List[str][source]

Get abbreviations of organisms for organism taxon nodes.

Parameters:nodes (List[anytree.node.node.Node]) – List of organism taxon nodes. These nodes are not traversed to find child nodes!
Returns:List of organism abbreviations from the nodes passed. None if no TaxonType.ORGANISM node was passed.
Return type:List[str]
getOrganismAbbreviationsByName(name: Escherichia, oneOrganismPerSpecies=True) → List[str][source]

Get abbreviations of organisms by a part of their name.

Parameters:
  • name (str) – Part of the name of the desired organism taxons. The name may be abbreviated, i.e. ‘Escherichia’ will match ‘Escherichia Coli K-12 MG1655’.
  • oneOrganismPerSpecies (bool, optional) – If True, return only the first organism node of each species node.
Returns:

List of organism abbreviations containing name in their name attribute. None if none found.
Return type:

List[str]
getOrganismAbbreviationsByPath(path: Gammaproteobacteria/Enterobacterales, exceptPaths: List[Gammaproteobacteria/unclassified] = None, oneOrganismPerSpecies=True) → List[str][source]

Get abbreviations of organisms by a part of their path.

Parameters:
  • path (str) – Part of the path of the desired organism taxons. The parts of the path specified here have to match the wording of the path nodes exactly, i.e. ‘Enterobac’ will not match ‘Enterobacterales’.
  • exceptPaths (Iterable[str] or str) – Paths which match any of these will not be returned. Accepts iterables of exceptions or a single string exception.
  • oneOrganismPerSpecies (bool, optional) – If True, return only the first organism node of each species node.
Returns:

List of organism abbreviations from the organism taxon nodes found at the end of path. None if no path leading to an TaxonType.ORGANISM node was passed.
Return type:

List[str]
getOrganismNodeByAbbreviation(abbreviation: eco) → anytree.node.node.Node[source]

Get node for an organism by its abbreviation.

Parameters:abbreviation (str) – Abbreviation of the organism in KEGG.
Returns:Node of .type == TaxonType.ORGANISM with .abbreviation == abbreviation. None if none can be found.
Return type:anytree.node.node.Node
getOrganismNodesByName(name: Escherichia, oneOrganismPerSpecies=True) → List[anytree.node.node.Node][source]

Get nodes for organisms by a part of their name.

Parameters:
  • name (str) – Part of the name of the desired organism taxons. This does not search parts of the path! The name may be abbreviated, i.e. ‘Escherichia’ will match ‘Escherichia Coli K-12 MG1655’.
  • oneOrganismPerSpecies (bool, optional) – If True, return only the first organism node of each species node.
Returns:

List of organism nodes containing name in their name attribute. None if none found.
Return type:

List[anytree.node.node.Node]
getOrganismNodesByPath(path: Gammaproteobacteria/Enterobacterales, exceptPaths: List[Gammaproteobacteria/unclassified] = None, oneOrganismPerSpecies=True) → List[anytree.node.node.Node][source]

Get nodes for organisms by a part of their path.

Parameters:
  • path (str) – Part of the path of the desired organism taxons. The parts of the path specified here have to match the wording of the path nodes exactly, i.e. ‘Enterobac’ will not match ‘Enterobacterales’.
  • exceptPaths (Iterable[str] or str) – Paths which match any of these will not be returned. Accepts iterables of exceptions or a single string exception.
  • oneOrganismPerSpecies (bool, optional) – If True, return only the first organism node of each species node.
Returns:

List of organism nodes containing path in their path. None if none found.
Return type:

List[anytree.node.node.Node]
static nodePath2String(node: anytree.node.node.Node) → str[source]
Parameters:node (anytree.node.node.Node) – Node which’ path to be expressed as a string.
Returns:Full path of node, expressed as string. Each taxon level is delimited by a slash (‘/’).
Return type:str
searchNodesByName(name: Escherichia, taxonType: FEV_KEGG.Evolution.Taxonomy.TaxonType = None) → List[anytree.node.node.Node][source]

Search taxons of a certain type by their name.

Parameters:
  • name (str) – Name of the taxon to be found. The name may be abbreviated, i.e. ‘Escherichia’ will match ‘Escherichia Coli K-12 MG1655’.
  • taxonType (TaxonType, optional) – Type of the taxons to be searched. Taxons of any other type are ignored. If None, all taxon types are searched.
Returns:

All Nodes containing name in their name attribute. None if none can be found. Only taxons of TaxonType taxonType are returned. If None, all taxon types are considered.
Return type:

List[anytree.node.node.Node]
searchNodesByPath(path: Gammaproteobacteria/Enterobacterales, taxonType: FEV_KEGG.Evolution.Taxonomy.TaxonType = None, exceptPaths: list of "Gammaproteobacteria/unclassified Bacteria" etc. = None) → List[anytree.node.node.Node][source]

Search taxons of a certain type by their path, allowing exceptions.

Parameters:
  • path (str) – Part of the path of the desired organism taxons. The parts of the path specified here have to match the wording of the path nodes exactly, i.e. ‘Enterobac’ will not match ‘Enterobacterales’.
  • taxonType (TaxonType, optional) – Type of the taxons to be searched. Taxons of any other type are ignored. If None, all taxon types are searched.
  • exceptPaths (Iterable[str] or str) – Paths which match any of these will not be returned. Accepts iterables of exceptions or a single string exception.
Returns:

All nodes containing path in their path. None if none can be found. Each path element has to be delimited by a slash (‘/’). Each path element has to match the name of the intermediate taxon exactly, i.e. ‘Enterobac’ will not match ‘Enterobacterales’.
Return type:

List[anytree.node.node.Node]
Module contents

This package contains functions full of assumptions about specific, yet simple and varying models of evolution. None of the results should be viewed as unconditional truth!

FEV_KEGG.Experiments package

Submodules
FEV_KEGG.Experiments.01 module
Question

Which reaction edges (substrate -> reaction ID -> product) are present in eco00260, but not in eco01100?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Calculate difference (eco00260 - eco01100). Do not subtract nodes, to keep all surviving edges.
  • Print reaction edges (substrate -> reaction ID -> product).
Result 
17 results
C00022 -> R00221 -> C00740
C00037 -> R00371 -> C03508
C00037 -> R03425 -> C00011
C00065 -> R01800 -> C02737
C00101 -> R04125 -> C00014
C00101 -> R04125 -> C02972
C00114 -> R01025 -> C00576
C00188 -> R01465 -> C03508
C00740 -> R00221 -> C00022
C01242 -> R04125 -> C00014
C01242 -> R04125 -> C02972
C01888 -> R02529 -> C00546
C02051 -> R03425 -> C00011
C02051 -> R03425 -> C01242
C02972 -> R03815 -> C02051
C03508 -> R00371 -> C00037
C05519 -> R10851 -> C03508
Conclusion

Global map 01100 does not necessarily contain all reaction edges for an organism.

FEV_KEGG.Experiments.02 module
Question

Which enzyme edges (substrate -> enzyme -> product) are present in eco00260, but not in eco01100?

Method
  • Download pathway definition as KGML.
  • Convert to substance-reaction graph.
  • Convert to substance-gene graph.
  • Calculate difference (eco00260 - eco01100). Do not subtract nodes, to keep all surviving edges.
  • Convert difference graph to substance-enzyme graph. Not necessary earlier, because each unique gene object ist mapped to the same unique enzyme object.
  • Print enzyme edges (substrate -> gene name, enzyme name, all associated EC numbers, enzyme long name -> product).
Result 
18 results
C00022 -> b2366 dsdA [4.3.1.18] D-serine dehydratase -> C00740
C00037 -> b2903 gcvP [1.4.4.2] glycine dehydrogenase -> C00011
C00037 -> b3617 kbl [2.3.1.29] glycine C-acetyltransferase -> C03508
C00065 -> b2585 pssA [2.7.8.8] CDP-diacylglycerol---serine O-phosphatidyltransferase -> C02737
C00101 -> b2905 gcvT [2.1.2.10] aminomethyltransferase -> C00014
C00101 -> b2905 gcvT [2.1.2.10] aminomethyltransferase -> C02972
C00168 -> b3553 ghrB [1.1.1.215, 1.1.1.81, 1.1.1.79] glyoxylate/hydroxypyruvate/2-ketogluconate reductase -> C00258
C00188 -> b3616 tdh [1.1.1.103] threonine 3-dehydrogenase -> C03508
C00258 -> b3553 ghrB [1.1.1.215, 1.1.1.81, 1.1.1.79] glyoxylate/hydroxypyruvate/2-ketogluconate reductase -> C00168
C00740 -> b2366 dsdA [4.3.1.18] D-serine dehydratase -> C00022
C01242 -> b2905 gcvT [2.1.2.10] aminomethyltransferase -> C00014
C01242 -> b2905 gcvT [2.1.2.10] aminomethyltransferase -> C02972
C01888 -> b1386 tynA [1.4.3.21] primary-amine oxidase -> C00546
C02051 -> b2903 gcvP [1.4.4.2] glycine dehydrogenase -> C00011
C02051 -> b2903 gcvP [1.4.4.2] glycine dehydrogenase -> C01242
C02972 -> b0116 lpd [1.8.1.4] dihydrolipoamide dehydrogenase -> C02051
C03508 -> b3617 kbl [2.3.1.29] glycine C-acetyltransferase -> C00037
C05519 -> b1539 ydfG [1.1.1.-, 1.1.1.381] 3-hydroxy acid dehydrogenase / malonic semialdehyde reductase -> C03508
Conclusion

Global map 01100 does not necessarily contain all enzyme edges for an organism.

FEV_KEGG.Experiments.03 module
Question

Which EC edges (substrate -> EC number -> product) are present in eco00260, but not in eco01100?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Convert to substance-gene graph.
  • Convert to substance-ec graph
  • Calculate difference (eco00260 - eco01100). Do not subtract nodes, to keep all surviving edges.
  • Print EC number edges (substrate -> EC number -> product).
Result 
19 results
C00022 -> 4.3.1.18 -> C00740
C00037 -> 1.4.4.2 -> C00011
C00037 -> 2.3.1.29 -> C03508
C00065 -> 2.7.8.8 -> C02737
C00101 -> 2.1.2.10 -> C00014
C00101 -> 2.1.2.10 -> C02972
C00168 -> 1.1.1.215 -> C00258
C00188 -> 1.1.1.103 -> C03508
C00258 -> 1.1.1.215 -> C00168
C00740 -> 4.3.1.18 -> C00022
C01242 -> 2.1.2.10 -> C00014
C01242 -> 2.1.2.10 -> C02972
C01888 -> 1.4.3.21 -> C00546
C02051 -> 1.4.4.2 -> C00011
C02051 -> 1.4.4.2 -> C01242
C02972 -> 1.8.1.4 -> C02051
C03508 -> 2.3.1.29 -> C00037
C05519 -> 1.1.1.- -> C03508
C05519 -> 1.1.1.381 -> C03508
Conclusion

Global map 01100 does not necessarily contain all EC number edges for an organism.

FEV_KEGG.Experiments.04 module
Question

Which enzymes, independent from substrate/product, are present in eco00260, but not in eco01100?

Method
  • Download pathway definition as KGML.
  • Convert to substance-reaction graph.
  • Convert to substance-gene graph.
  • Convert to substance-enzyme graph
  • Get set of enzymes for each graph.
  • Calculate difference of enzyme sets.
  • Print enzymes (gene name, enzyme name, all associated EC numbers, enzyme long name).
Result 
3 results
b2366 dsdA [4.3.1.18] D-serine dehydratase
b3616 tdh [1.1.1.103] threonine 3-dehydrogenase
b3617 kbl [2.3.1.29] glycine C-acetyltransferase
Conclusion

Global map 01100 does not necessarily contain all enzymes for an organism.

FEV_KEGG.Experiments.05 module
Question

Which EC numbers, independent from substrate/product, are present in eco00260, but not in eco01100?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Convert to substance-gene graph.
  • Convert to substance-ec graph
  • Get set of EC numbers for each graph.
  • Calculate difference of EC number sets.
  • Print EC numbers.
Result 
3 results
1.1.1.103
2.3.1.29
4.3.1.18
Conclusion

Global map 01100 does not necessarily contain all EC numbers for an organism.

FEV_KEGG.Experiments.06 module
Question

Which genes, independent from substrate/product, are present in eco00260, but not in eco01100?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Convert to substance-gene graph.
  • Get set of genes for each graph.
  • Calculate difference of gene sets.
  • Print genes (gene ID).
Result 
3 results
eco:b2366
eco:b3616
eco:b3617
Conclusion

Global map 01100 does not necessarily contain all enzyme-coding genes for an organism.

FEV_KEGG.Experiments.07 module
Question

Which reaction edges (substrate -> reaction ID -> product) are present in eco01100, but not in a combination of all non-overview metabolic pathways?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Calculate difference (eco01100 - allNonOverviewPathways). Do not subtract nodes, to keep all surviving edges.
  • Print reaction edges (substrate -> reaction ID -> product).
Result 
877 results
C00002 -> R02014 -> C00131
C00003 -> R00189 -> C00857
C00003 -> R00257 -> C00857
C00006 -> R00104 -> C00003
C00010 -> R00130 -> C00882
C00011 -> R00214 -> C00149
C00011 -> R00216 -> C00149
C00011 -> R00345 -> C00036
C00014 -> R00149 -> C00169
C00014 -> R01221 -> C00037
C00016 -> R00160 -> C00061
C00016 -> R00161 -> C00061
C00018 -> R00173 -> C00250
C00018 -> R00174 -> C00250
C00018 -> R00277 -> C00647
C00018 -> R00278 -> C00627
C00019 -> R00177 -> C00073
C00019 -> R10404 -> C00021
C00020 -> R00185 -> C00212
C00020 -> R01083 -> C03794
C00021 -> R04858 -> C00019
C00021 -> R10404 -> C00019
C00022 -> R00196 -> C00186
C00022 -> R00200 -> C00074
C00022 -> R00206 -> C00074
C00022 -> R00209 -> C00024
C00022 -> R00220 -> C00065
C00022 -> R00369 -> C00041
C00022 -> R00396 -> C00041
C00022 -> R00400 -> C00041
C00022 -> R00703 -> C00186
C00022 -> R01447 -> C00186
C00022 -> R02320 -> C00074
C00022 -> R03105 -> C00957
C00024 -> R00209 -> C00022
C00024 -> R00229 -> C00033
C00024 -> R00352 -> C00158
C00025 -> R00093 -> C00026
C00025 -> R00114 -> C00026
C00025 -> R00243 -> C00026
C00025 -> R00355 -> C00049
C00025 -> R00411 -> C05931
C00026 -> R00243 -> C00025
C00026 -> R00267 -> C00311
C00026 -> R00709 -> C00311
C00029 -> R00287 -> C00103
C00031 -> R00010 -> C01083
C00031 -> R00028 -> C00208
C00031 -> R00305 -> C00198
C00031 -> R00306 -> C00185
C00031 -> R00801 -> C00089
C00031 -> R01555 -> C00208
C00031 -> R02727 -> C01083
C00031 -> R05196 -> C00208
C00031 -> R07147 -> C00198
C00032 -> R00310 -> C02191
C00033 -> R00229 -> C00024
C00033 -> R00320 -> C00227
C00033 -> R00710 -> C00084
C00036 -> R00345 -> C00011
C00036 -> R00345 -> C00074
C00036 -> R00346 -> C00074
C00036 -> R00352 -> C00158
C00036 -> R00357 -> C00049
C00036 -> R00361 -> C00149
C00036 -> R00431 -> C00074
C00036 -> R00726 -> C00074
C00037 -> R00899 -> C01419
C00039 -> R00377 -> C00458
C00039 -> R00378 -> C00459
C00041 -> R00369 -> C00022
C00041 -> R00396 -> C00022
C00041 -> R00400 -> C00022
C00041 -> R03599 -> C05688
C00042 -> R00432 -> C00091
C00042 -> R00713 -> C00232
C00042 -> R00714 -> C00232
C00042 -> R00727 -> C00091
C00042 -> R10343 -> C00091
C00043 -> R00414 -> C00645
C00043 -> R00416 -> C04501
C00044 -> R02020 -> C00286
C00046 -> R00442 -> C00063
C00046 -> R00443 -> C00075
C00047 -> R00451 -> C00680
C00048 -> R00475 -> C00160
C00048 -> R00479 -> C00311
C00048 -> R00717 -> C00160
C00049 -> R00355 -> C00025
C00049 -> R00485 -> C00152
C00049 -> R07407 -> C05840
C00049 -> R07410 -> C05840
C00051 -> R00497 -> C00037
C00051 -> R00497 -> C00669
C00051 -> R01918 -> C05730
C00052 -> R00502 -> C00446
C00053 -> R00509 -> C00224
C00055 -> R00513 -> C00475
C00055 -> R00516 -> C00475
C00055 -> R00517 -> C00475
C00055 -> R00962 -> C00475
C00055 -> R01548 -> C00475
C00055 -> R02091 -> C00475
C00055 -> R02096 -> C00475
C00055 -> R02371 -> C00475
C00055 -> R02372 -> C00475
C00058 -> R00519 -> C00080
C00059 -> R00530 -> C00224
C00059 -> R00531 -> C00224
C00061 -> R00160 -> C00016
C00061 -> R00549 -> C00255
C00061 -> R00550 -> C00255
C00061 -> R05705 -> C01847
C00061 -> R08574 -> C00255
C00062 -> R01086 -> C03406
C00063 -> R00571 -> C00075
C00063 -> R00573 -> C00075
C00063 -> R02022 -> C00458
C00064 -> R00253 -> C00014
C00064 -> R00253 -> C00025
C00065 -> R00582 -> C01005
C00068 -> R00616 -> C03028
C00068 -> R00617 -> C01081
C00068 -> R00618 -> C03028
C00073 -> R00648 -> C01180
C00073 -> R00650 -> C00155
C00073 -> R00946 -> C00155
C00073 -> R02821 -> C00155
C00073 -> R04405 -> C00155
C00073 -> R07396 -> C01180
C00074 -> R00199 -> C00022
C00074 -> R00206 -> C00022
C00074 -> R00346 -> C00036
C00074 -> R00431 -> C00036
C00074 -> R00726 -> C00036
C00077 -> R00669 -> C00437
C00077 -> R02282 -> C00437
C00078 -> R00674 -> C00463
C00078 -> R02722 -> C00065
C00079 -> R00688 -> C00166
C00079 -> R00689 -> C00166
C00079 -> R00692 -> C00166
C00080 -> R00519 -> C00058
C00082 -> R00729 -> C01179
C00082 -> R09254 -> C01179
C00084 -> R00710 -> C00033
C00084 -> R00746 -> C00469
C00084 -> R05198 -> C00469
C00084 -> R09127 -> C00469
C00085 -> R00762 -> C00354
C00085 -> R01067 -> C00279
C00091 -> R00432 -> C00042
C00091 -> R00727 -> C00042
C00091 -> R10343 -> C00042
C00093 -> R00841 -> C00116
C00093 -> R00847 -> C00116
C00094 -> R00859 -> C00283
C00094 -> R00861 -> C00283
C00094 -> R02021 -> C00053
C00095 -> R00801 -> C00089
C00095 -> R00866 -> C01094
C00096 -> R00883 -> C00636
C00097 -> R00895 -> C00957
C00097 -> R00897 -> C00283
C00097 -> R00897 -> C00979
C00097 -> R00899 -> C01419
C00097 -> R04859 -> C00979
C00099 -> R00489 -> C00049
C00099 -> R00907 -> C00222
C00099 -> R02474 -> C00864
C00100 -> R00919 -> C00894
C00100 -> R00927 -> C03344
C00100 -> R04432 -> C00894
C00100 -> R10161 -> C00894
C00101 -> R00937 -> C00504
C00101 -> R00940 -> C00504
C00101 -> R00943 -> C00234
C00101 -> R01225 -> C00143
C00101 -> R04326 -> C00445
C00101 -> R06613 -> C00143
C00103 -> R00287 -> C00029
C00103 -> R00951 -> C00498
C00103 -> R02111 -> C00369
C00105 -> R00662 -> C00075
C00105 -> R00964 -> C00299
C00105 -> R00965 -> C01103
C00105 -> R00967 -> C00299
C00105 -> R00968 -> C00299
C00105 -> R00970 -> C00299
C00105 -> R01549 -> C00299
C00105 -> R01880 -> C00299
C00105 -> R02097 -> C00299
C00105 -> R02327 -> C00299
C00105 -> R02332 -> C00299
C00106 -> R00974 -> C00380
C00106 -> R00978 -> C00429
C00108 -> R00985 -> C00251
C00108 -> R00986 -> C00251
C00109 -> R00996 -> C00188
C00109 -> R00999 -> C01118
C00111 -> R01011 -> C00184
C00114 -> R01022 -> C00576
C00114 -> R08557 -> C00576
C00114 -> R08558 -> C00576
C00116 -> R00841 -> C00093
C00116 -> R01039 -> C00184
C00118 -> R01063 -> C00236
C00118 -> R01064 -> C01286
C00120 -> R01078 -> C01909
C00120 -> R10127 -> C20386
C00122 -> R00490 -> C00049
C00122 -> R01086 -> C03406
C00123 -> R01088 -> C00233
C00124 -> R01678 -> C00243
C00129 -> R05884 -> C11811
C00130 -> R01128 -> C00262
C00131 -> R02014 -> C00002
C00131 -> R11634 -> C00002
C00134 -> R00670 -> C00077
C00134 -> R01151 -> C00555
C00134 -> R01156 -> C02714
C00134 -> R01157 -> C00179
C00134 -> R01920 -> C00170
C00134 -> R08714 -> C00555
C00135 -> R01163 -> C01929
C00136 -> R01171 -> C00877
C00136 -> R01176 -> C00246
C00137 -> R01186 -> C03546
C00137 -> R01187 -> C04006
C00137 -> R07279 -> C04006
C00140 -> R00022 -> C01674
C00141 -> R01434 -> C00183
C00141 -> R04441 -> C04272
C00143 -> R01217 -> C00440
C00143 -> R01218 -> C00445
C00143 -> R01225 -> C00101
C00143 -> R04125 -> C01242
C00143 -> R06613 -> C00101
C00144 -> R01230 -> C00655
C00144 -> R01231 -> C00655
C00147 -> R01245 -> C00212
C00149 -> R00214 -> C00011
C00149 -> R00216 -> C00011
C00152 -> R00483 -> C00049
C00154 -> R01278 -> C05272
C00155 -> R01286 -> C02291
C00155 -> R01287 -> C01077
C00155 -> R01288 -> C01118
C00155 -> R01290 -> C02291
C00155 -> R01291 -> C03539
C00155 -> R02026 -> C01077
C00155 -> R02821 -> C00073
C00155 -> R10305 -> C02291
C00156 -> R05000 -> C05848
C00157 -> R07064 -> C01595
C00158 -> R00352 -> C00024
C00158 -> R00352 -> C00036
C00158 -> R01324 -> C00311
C00159 -> R01326 -> C00275
C00160 -> R00717 -> C00048
C00160 -> R01334 -> C00988
C00166 -> R00688 -> C00079
C00166 -> R00689 -> C00079
C00166 -> R00692 -> C00079
C00169 -> R00149 -> C00014
C00169 -> R00575 -> C00064
C00170 -> R01920 -> C00134
C00170 -> R01920 -> C01137
C00173 -> R10121 -> C19845
C00178 -> R01415 -> C21028
C00178 -> R01570 -> C00214
C00179 -> R00566 -> C00062
C00181 -> R01433 -> C02352
C00183 -> R01434 -> C00141
C00184 -> R01039 -> C00116
C00185 -> R02887 -> C01898
C00185 -> R11308 -> C01898
C00186 -> R00703 -> C00022
C00186 -> R01447 -> C00022
C00188 -> R01466 -> C01102
C00191 -> R01478 -> C03033
C00194 -> R01492 -> C00853
C00194 -> R05223 -> C05775
C00194 -> R05223 -> C06510
C00198 -> R00305 -> C00031
C00198 -> R06620 -> C00031
C00198 -> R07147 -> C00031
C00199 -> R01523 -> C01182
C00199 -> R01528 -> C00345
C00199 -> R10221 -> C00345
C00204 -> R01540 -> C00817
C00206 -> R02017 -> C00008
C00208 -> R01555 -> C00031
C00208 -> R11262 -> C01935
C00212 -> R00183 -> C00020
C00212 -> R00185 -> C00020
C00214 -> R01569 -> C00364
C00217 -> R01579 -> C00819
C00222 -> R00907 -> C00099
C00222 -> R09983 -> C20253
C00224 -> R00508 -> C00053
C00224 -> R00530 -> C00059
C00224 -> R00531 -> C00059
C00227 -> R00320 -> C00033
C00232 -> R09281 -> C00989
C00232 -> R10178 -> C00334
C00233 -> R01088 -> C00123
C00234 -> R00943 -> C00101
C00235 -> R01122 -> C04432
C00236 -> R01063 -> C00118
C00239 -> R01667 -> C00705
C00245 -> R01682 -> C00506
C00246 -> R01176 -> C00136
C00249 -> R01274 -> C00154
C00250 -> R00173 -> C00018
C00251 -> R01714 -> C01269
C00253 -> R01268 -> C00153
C00254 -> R01730 -> C01179
C00254 -> R07276 -> C00826
C00255 -> R00066 -> C04332
C00255 -> R00548 -> C00061
C00255 -> R00550 -> C00061
C00255 -> R08574 -> C00061
C00257 -> R01741 -> C06473
C00262 -> R01128 -> C00130
C00262 -> R01244 -> C00147
C00262 -> R01769 -> C00385
C00262 -> R02748 -> C05512
C00267 -> R01678 -> C00243
C00267 -> R01788 -> C00668
C00267 -> R02189 -> C00668
C00267 -> R09085 -> C00668
C00269 -> R01799 -> C00416
C00275 -> R01326 -> C00159
C00275 -> R02630 -> C00159
C00279 -> R01067 -> C00085
C00279 -> R01829 -> C00447
C00283 -> R00859 -> C00094
C00283 -> R00861 -> C00094
C00286 -> R01858 -> C00361
C00286 -> R02020 -> C00044
C00286 -> R11633 -> C00044
C00294 -> R01126 -> C00130
C00294 -> R01560 -> C00212
C00295 -> R01867 -> C00337
C00295 -> R01869 -> C00337
C00299 -> R01878 -> C00475
C00311 -> R00267 -> C00026
C00311 -> R00709 -> C00026
C00311 -> R01324 -> C00158
C00314 -> R01911 -> C00627
C00315 -> R01918 -> C05730
C00315 -> R01920 -> C00134
C00315 -> R01920 -> C01137
C00327 -> R01398 -> C00077
C00327 -> R01398 -> C00169
C00327 -> R09107 -> C15532
C00330 -> R01967 -> C00362
C00334 -> R00261 -> C00025
C00334 -> R01986 -> C00555
C00334 -> R02549 -> C00555
C00334 -> R07419 -> C15767
C00334 -> R10178 -> C00232
C00337 -> R01867 -> C00295
C00337 -> R01869 -> C00295
C00341 -> R01658 -> C00129
C00341 -> R01658 -> C00235
C00344 -> R02029 -> C03892
C00345 -> R01737 -> C00257
C00345 -> R02035 -> C01236
C00350 -> R02055 -> C02737
C00350 -> R07376 -> C02737
C00352 -> R00768 -> C05345
C00357 -> R01201 -> C00140
C00360 -> R02089 -> C00559
C00361 -> R02019 -> C00035
C00362 -> R01967 -> C00330
C00364 -> R01567 -> C00214
C00364 -> R02101 -> C00365
C00365 -> R02100 -> C00460
C00366 -> R02103 -> C00385
C00366 -> R02107 -> C00385
C00369 -> R02110 -> C00718
C00376 -> R02124 -> C00473
C00376 -> R08379 -> C00473
C00378 -> R02135 -> C01081
C00380 -> R02137 -> C00475
C00380 -> R02296 -> C00475
C00385 -> R01676 -> C00242
C00385 -> R01768 -> C00262
C00385 -> R01769 -> C00262
C00385 -> R02107 -> C00366
C00387 -> R01227 -> C00144
C00399 -> R08781 -> C17562
C00407 -> R02197 -> C00671
C00415 -> R02237 -> C00921
C00416 -> R02239 -> C00641
C00416 -> R02240 -> C00641
C00416 -> R02241 -> C00681
C00416 -> R09944 -> C00641
C00429 -> R00978 -> C00106
C00430 -> R02272 -> C03741
C00437 -> R02282 -> C00077
C00437 -> R02283 -> C01250
C00438 -> R01397 -> C00169
C00440 -> R01217 -> C00143
C00440 -> R01224 -> C00143
C00440 -> R07168 -> C00143
C00441 -> R02291 -> C03082
C00445 -> R01218 -> C00143
C00445 -> R02301 -> C03479
C00446 -> R00502 -> C00052
C00446 -> R01092 -> C00984
C00447 -> R01829 -> C00279
C00448 -> R02003 -> C00129
C00448 -> R02003 -> C00341
C00455 -> R00103 -> C00003
C00455 -> R02324 -> C03150
C00458 -> R02022 -> C00063
C00458 -> R11636 -> C00063
C00460 -> R02325 -> C00458
C00469 -> R00746 -> C00084
C00469 -> R05198 -> C00084
C00469 -> R09127 -> C00084
C00470 -> R02362 -> C00714
C00473 -> R02124 -> C00376
C00473 -> R08379 -> C00376
C00475 -> R02296 -> C00380
C00493 -> R02415 -> C02637
C00498 -> R00951 -> C00103
C00519 -> R02466 -> C00606
C00522 -> R02474 -> C00864
C00534 -> R02494 -> C00647
C00541 -> R00097 -> C00992
C00541 -> R00107 -> C00992
C00555 -> R01151 -> C00134
C00555 -> R01155 -> C00134
C00555 -> R01986 -> C00334
C00555 -> R08714 -> C00134
C00558 -> R01983 -> C00333
C00559 -> R02089 -> C00360
C00576 -> R01022 -> C00114
C00576 -> R08211 -> C00719
C00576 -> R08557 -> C00114
C00576 -> R08558 -> C00114
C00590 -> R02596 -> C15805
C00601 -> R02537 -> C07086
C00624 -> R00259 -> C00025
C00627 -> R01909 -> C00314
C00627 -> R01911 -> C00314
C00627 -> R05838 -> C11638
C00631 -> R08572 -> C00258
C00636 -> R00883 -> C00096
C00641 -> R02239 -> C00416
C00641 -> R09944 -> C00416
C00645 -> R00414 -> C00043
C00647 -> R02493 -> C00534
C00647 -> R02494 -> C00534
C00655 -> R01130 -> C00130
C00666 -> R02734 -> C04421
C00668 -> R01788 -> C00267
C00668 -> R02189 -> C00267
C00668 -> R09085 -> C00267
C00669 -> R00894 -> C00025
C00669 -> R00894 -> C00097
C00671 -> R02197 -> C00407
C00671 -> R05070 -> C06007
C00681 -> R00851 -> C00093
C00689 -> R02737 -> C00029
C00692 -> R02783 -> C01212
C00705 -> R01667 -> C00239
C00705 -> R02024 -> C00112
C00718 -> R02421 -> C00498
C00719 -> R02565 -> C00576
C00719 -> R02566 -> C00576
C00719 -> R08211 -> C00576
C00721 -> R02112 -> C00369
C00748 -> R02864 -> C05778
C00760 -> R02889 -> C00029
C00798 -> R01908 -> C00313
C00817 -> R02555 -> C00558
C00826 -> R01731 -> C00254
C00826 -> R07276 -> C00254
C00828 -> R04993 -> C05818
C00857 -> R00257 -> C00003
C00860 -> R03013 -> C01100
C00864 -> R02473 -> C00099
C00864 -> R02473 -> C00522
C00864 -> R02474 -> C00099
C00864 -> R02474 -> C00522
C00877 -> R01171 -> C00136
C00877 -> R01175 -> C00136
C00894 -> R04432 -> C00100
C00894 -> R10161 -> C00100
C00921 -> R03066 -> C00568
C00921 -> R03066 -> C01300
C00921 -> R03067 -> C00568
C00921 -> R03067 -> C04807
C00931 -> R00036 -> C00430
C00944 -> R03083 -> C04691
C00957 -> R00895 -> C00097
C00966 -> R01226 -> C00141
C00979 -> R04859 -> C00097
C00984 -> R10619 -> C00124
C00989 -> R09281 -> C00232
C00992 -> R00107 -> C00541
C00993 -> R01150 -> C00133
C01007 -> R05707 -> C00255
C01007 -> R09750 -> C00255
C01013 -> R09289 -> C00222
C01024 -> R00084 -> C00931
C01037 -> R03231 -> C01092
C01037 -> R10699 -> C01092
C01050 -> R03191 -> C04631
C01050 -> R03192 -> C04631
C01051 -> R03165 -> C01024
C01077 -> R01287 -> C00155
C01079 -> R03220 -> C03263
C01079 -> R03222 -> C02191
C01079 -> R06895 -> C03263
C01081 -> R00615 -> C00068
C01081 -> R02134 -> C00378
C01081 -> R03223 -> C04327
C01081 -> R03223 -> C04752
C01081 -> R10712 -> C04752
C01081 -> R10712 -> C20247
C01083 -> R02727 -> C00031
C01083 -> R02778 -> C00689
C01092 -> R03210 -> C01063
C01092 -> R10124 -> C19845
C01092 -> R10699 -> C01037
C01094 -> R00866 -> C00095
C01094 -> R03232 -> C00095
C01097 -> R05571 -> C06311
C01102 -> R01771 -> C00263
C01134 -> R03269 -> C04352
C01137 -> R00178 -> C00019
C01146 -> R00013 -> C00048
C01146 -> R01394 -> C00168
C01157 -> R03291 -> C04281
C01157 -> R03293 -> C04281
C01157 -> R03295 -> C04281
C01165 -> R03313 -> C03287
C01170 -> R00420 -> C00043
C01179 -> R00729 -> C00082
C01179 -> R01730 -> C00254
C01179 -> R09254 -> C00082
C01180 -> R00648 -> C00073
C01182 -> R01523 -> C00199
C01185 -> R03004 -> C00857
C01185 -> R03348 -> C03722
C01187 -> R03350 -> C04478
C01190 -> R03354 -> C01290
C01190 -> R03355 -> C01290
C01212 -> R03193 -> C01050
C01216 -> R03033 -> C00880
C01222 -> R00888 -> C00096
C01236 -> R02736 -> C01172
C01236 -> R10907 -> C01172
C01242 -> R03425 -> C00037
C01250 -> R03443 -> C04133
C01267 -> R03457 -> C04666
C01268 -> R03459 -> C01304
C01286 -> R03387 -> C01216
C01290 -> R03354 -> C01190
C01300 -> R03504 -> C04874
C01304 -> R00425 -> C00044
C01419 -> R00494 -> C00051
C01528 -> R03599 -> C05688
C01595 -> R07064 -> C00157
C01672 -> R00462 -> C00047
C01672 -> R06740 -> C12455
C01674 -> R02334 -> C00461
C01762 -> R02719 -> C00655
C01832 -> R03856 -> C03221
C01847 -> R05705 -> C00061
C01847 -> R05706 -> C00061
C01898 -> R11308 -> C00185
C01909 -> R03182 -> C01037
C01929 -> R03012 -> C00860
C01944 -> R03776 -> C05276
C02059 -> R06859 -> C13309
C02191 -> R03222 -> C01079
C02191 -> R09489 -> C01079
C02222 -> R08121 -> C16476
C02232 -> R06941 -> C14145
C02282 -> R03652 -> C00064
C02291 -> R01290 -> C00155
C02291 -> R03217 -> C01077
C02291 -> R03260 -> C01118
C02291 -> R10305 -> C00155
C02325 -> R03919 -> C15806
C02463 -> R03194 -> C01051
C02504 -> R01213 -> C00141
C02565 -> R02922 -> C00791
C02593 -> R03989 -> C05273
C02637 -> R02415 -> C00493
C02646 -> R04007 -> C15804
C02714 -> R01154 -> C00134
C02714 -> R01156 -> C00134
C02723 -> R04027 -> C06178
C02730 -> R04031 -> C05817
C02737 -> R01800 -> C00269
C02737 -> R07376 -> C00350
C02741 -> R04035 -> C02739
C02987 -> R05578 -> C00025
C03028 -> R00616 -> C00068
C03028 -> R00618 -> C00068
C03028 -> R11319 -> C00068
C03082 -> R00480 -> C00049
C03089 -> R01401 -> C00170
C03090 -> R01072 -> C00119
C03160 -> R04030 -> C02730
C03175 -> R02412 -> C00493
C03221 -> R03856 -> C01832
C03221 -> R03857 -> C01832
C03263 -> R03197 -> C01051
C03287 -> R00239 -> C00025
C03291 -> R07125 -> C14899
C03296 -> R00832 -> C00062
C03373 -> R04208 -> C04640
C03406 -> R01954 -> C00049
C03406 -> R01954 -> C00327
C03415 -> R04189 -> C03296
C03453 -> R03966 -> C02501
C03492 -> R03018 -> C00864
C03492 -> R04230 -> C04352
C03539 -> R00194 -> C00021
C03589 -> R02601 -> C00596
C03657 -> R07262 -> C15547
C03684 -> R04286 -> C04895
C03722 -> R04292 -> C05840
C03741 -> R04109 -> C02987
C03794 -> R01135 -> C00130
C03838 -> R04144 -> C03090
C03892 -> R01801 -> C00269
C03912 -> R01253 -> C00148
C03972 -> R04198 -> C20258
C03972 -> R04199 -> C20258
C04006 -> R07279 -> C00137
C04043 -> R04300 -> C03758
C04121 -> R03351 -> C01187
C04133 -> R02649 -> C00624
C04257 -> R02705 -> C00645
C04281 -> R03295 -> C01157
C04317 -> R03438 -> C05212
C04317 -> R07387 -> C05212
C04327 -> R04448 -> C04294
C04332 -> R04457 -> C04732
C04332 -> R04457 -> C15556
C04352 -> R04230 -> C03492
C04352 -> R04231 -> C03492
C04376 -> R04325 -> C03838
C04405 -> R04204 -> C03345
C04432 -> R01122 -> C00235
C04442 -> R01541 -> C00204
C04442 -> R02036 -> C00345
C04454 -> R03458 -> C01268
C04462 -> R04365 -> C03972
C04478 -> R03254 -> C01112
C04501 -> R05332 -> C06156
C04556 -> R03471 -> C01279
C04556 -> R03472 -> C03373
C04631 -> R00660 -> C00043
C04635 -> R04413 -> C04756
C04635 -> R07379 -> C04756
C04640 -> R04463 -> C04376
C04652 -> R04550 -> C06022
C04666 -> R04558 -> C04916
C04677 -> R06975 -> C04734
C04691 -> R01826 -> C00074
C04691 -> R01826 -> C00279
C04702 -> R04573 -> C05892
C04732 -> R07280 -> C04454
C04734 -> R04560 -> C04677
C04734 -> R06975 -> C04677
C04738 -> R04567 -> C00043
C04752 -> R04509 -> C04556
C04756 -> R04413 -> C04635
C04778 -> R04148 -> C03114
C04807 -> R03503 -> C01300
C04824 -> R04549 -> C04652
C04851 -> R05629 -> C04702
C04874 -> R04620 -> C04895
C04895 -> R04639 -> C06148
C04896 -> R04037 -> C02741
C04916 -> R04640 -> C04896
C04919 -> R04657 -> C04932
C04932 -> R04606 -> C04652
C04932 -> R04606 -> C04824
C05172 -> R03595 -> C01528
C05212 -> R03438 -> C04317
C05270 -> R06985 -> C05271
C05271 -> R04751 -> C05270
C05271 -> R06985 -> C05270
C05272 -> R01278 -> C00154
C05272 -> R01279 -> C00154
C05273 -> R03989 -> C02593
C05273 -> R03990 -> C02593
C05274 -> R04753 -> C05275
C05275 -> R04753 -> C05274
C05275 -> R04754 -> C05274
C05276 -> R03776 -> C01944
C05276 -> R03777 -> C01944
C05345 -> R00867 -> C00095
C05345 -> R02073 -> C05378
C05345 -> R04780 -> C05378
C05345 -> R09084 -> C05378
C05378 -> R02073 -> C05345
C05378 -> R04779 -> C05345
C05378 -> R09084 -> C05345
C05527 -> R02619 -> C00606
C05730 -> R01917 -> C00051
C05730 -> R01917 -> C00315
C05744 -> R04355 -> C01209
C05744 -> R04355 -> C03939
C05744 -> R10707 -> C01209
C05746 -> R04952 -> C01209
C05746 -> R04952 -> C05745
C05750 -> R04957 -> C01209
C05750 -> R04957 -> C05749
C05753 -> R04960 -> C01209
C05753 -> R04960 -> C05752
C05756 -> R04963 -> C01209
C05756 -> R04963 -> C05755
C05759 -> R04726 -> C01209
C05759 -> R04726 -> C05223
C05762 -> R04968 -> C01209
C05762 -> R04968 -> C05761
C05768 -> R04972 -> C05766
C05775 -> R04594 -> C04778
C05778 -> R03947 -> C02463
C05791 -> R04979 -> C05787
C05807 -> R04985 -> C05848
C05807 -> R08768 -> C17551
C05817 -> R08166 -> C16519
C05818 -> R05617 -> C03657
C05840 -> R00481 -> C00049
C05840 -> R07407 -> C00049
C05840 -> R07410 -> C00049
C05848 -> R04985 -> C05807
C05848 -> R05000 -> C00156
C05893 -> R05662 -> C04851
C05921 -> R01074 -> C00120
C05922 -> R00428 -> C00044
C05923 -> R05046 -> C05922
C05924 -> R09395 -> C18239
C05931 -> R05049 -> C05932
C05932 -> R04217 -> C03415
C05946 -> R05052 -> C05947
C05946 -> R05053 -> C05947
C05947 -> R04444 -> C04281
C05947 -> R04445 -> C04281
C05947 -> R05053 -> C05946
C05980 -> R07390 -> C00344
C05980 -> R11062 -> C00344
C06000 -> R04224 -> C03460
C06001 -> R05066 -> C06002
C06002 -> R05066 -> C06001
C06006 -> R08648 -> C00022
C06006 -> R08648 -> C00109
C06010 -> R00226 -> C00022
C06022 -> R04587 -> C04738
C06024 -> R04658 -> C04121
C06024 -> R04658 -> C04919
C06025 -> R05074 -> C04121
C06025 -> R05074 -> C06024
C06026 -> R05075 -> C06251
C06040 -> R05081 -> C06041
C06041 -> R05081 -> C06040
C06148 -> R05048 -> C05923
C06157 -> R01940 -> C00322
C06178 -> R04027 -> C02723
C06250 -> R05145 -> C05921
C06251 -> R05146 -> C06025
C06311 -> R05570 -> C01697
C06329 -> R05511 -> C04706
C06397 -> R05644 -> C07838
C06398 -> R05176 -> C06397
C06427 -> R07859 -> C00157
C06427 -> R07860 -> C00157
C06473 -> R01741 -> C00257
C06506 -> R05220 -> C06505
C06509 -> R05221 -> C06508
C06509 -> R06558 -> C06508
C06510 -> R05222 -> C06509
C06613 -> R05233 -> C06611
C07086 -> R02536 -> C00601
C07086 -> R02537 -> C00601
C07335 -> R05681 -> C06055
C07479 -> R05389 -> C07478
C07836 -> R05645 -> C05382
C07838 -> R05647 -> C11472
C11434 -> R05688 -> C11437
C11435 -> R05633 -> C11434
C11436 -> R05634 -> C11435
C11453 -> R05637 -> C11436
C11472 -> R05646 -> C07836
C11811 -> R08689 -> C11453
C11811 -> R10859 -> C11453
C12248 -> R06601 -> C11821
C12455 -> R06740 -> C01672
C12835 -> R06835 -> C12834
C13309 -> R06858 -> C03657
C14145 -> R06942 -> C14144
C14899 -> R07677 -> C16186
C15556 -> R07281 -> C00199
C15667 -> R07404 -> C03373
C15672 -> R07411 -> C00032
C15699 -> R07414 -> C00134
C15700 -> R07415 -> C15699
C15767 -> R07417 -> C15700
C15767 -> R07418 -> C15700
C15804 -> R04007 -> C02646
C15805 -> R02596 -> C00590
C15806 -> R03919 -> C02325
C15809 -> R10246 -> C00082
C15812 -> R07460 -> C00097
C15812 -> R07460 -> C15811
C15813 -> R07459 -> C15810
C15814 -> R07461 -> C15812
C15814 -> R07461 -> C15813
C15996 -> R09978 -> C20248
C16186 -> R07671 -> C00072
C16236 -> R07766 -> C05752
C16237 -> R07767 -> C16236
C16237 -> R07769 -> C16239
C16237 -> R11143 -> C16241
C16239 -> R07768 -> C05752
C16331 -> R07891 -> C16330
C16335 -> R07895 -> C16334
C16339 -> R07899 -> C16338
C16348 -> R05234 -> C06612
C16519 -> R08165 -> C00885
C16675 -> R07605 -> C15996
C17551 -> R08768 -> C05807
C17551 -> R08769 -> C17552
C17552 -> R08769 -> C17551
C17552 -> R08773 -> C17560
C17560 -> R08773 -> C17552
C17560 -> R08774 -> C17561
C17561 -> R08774 -> C17560
C17561 -> R08775 -> C17562
C17562 -> R08775 -> C17561
C17562 -> R08781 -> C00399
C18237 -> R09735 -> C19848
C18239 -> R11372 -> C21310
C19673 -> R09543 -> C01209
C19845 -> R09725 -> C19846
C19845 -> R10121 -> C00173
C19846 -> R10122 -> C20378
C19848 -> R09726 -> C05924
C19871 -> R11581 -> C18237
C20231 -> R09936 -> C00106
C20239 -> R09959 -> C04895
C20246 -> R10247 -> C11437
C20246 -> R10247 -> C15809
C20246 -> R10247 -> C15814
C20248 -> R10002 -> C20239
C20249 -> R09947 -> C20231
C20253 -> R09982 -> C20249
C20258 -> R10147 -> C00441
C20372 -> R10115 -> C01209
C20372 -> R10115 -> C19673
C20373 -> R10116 -> C20372
C20374 -> R10117 -> C20373
C20375 -> R10118 -> C20374
C20376 -> R10119 -> C01209
C20376 -> R10119 -> C20375
C20377 -> R10120 -> C20376
C21015 -> R10993 -> C02356
C21016 -> R10994 -> C21015
C21028 -> R01415 -> C00178
C21284 -> R11329 -> C05770
C21310 -> R09394 -> C00044
G09660 -> R07818 -> G13040
G13040 -> R07818 -> G09660
Conclusion

Many reactions occur in the overview map eco01100, although they exist no where in the union of all known metabolism pathways.

Further research shows the reasons for such strange results:

  • If a gene of eco produces an enzyme that can be used in multiple pathways, eco01100 automatically includes the reactions performed by that enzyme into all possible positions of the global map, even those positions inside a pathway which eco supposedly does not have. Because the reaction acts on a different substrate in this “non-existing” pathway, it stands out in this experiment. This is most likely not an error in KEGG’s data, but a corner-case where our methodology fails to handle the data. Example: G09660 -> R07818 -> G13040 (gene eco:b1617)
  • The same reaction (same substrate and product) is marked as irreversible in a single pathway, in eco01100, however, it is marked a reversible. 01100 generally seems to not support irreversible edges. Because this experiment uses a directed graph, the reverse direction stands out. Example: C21310 -> R09394 -> C00044
  • Maybe more.

The overview map 01100 is, therefore, not suitable for exact research of reactions.

FEV_KEGG.Experiments.08 module
Question

Which EC number edges (substrate -> EC number -> product) are present in eco01100, but not in a combination of all non-overview metabolic pathways?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Convert to substance-gene graph.
  • Convert to substance-ec graph.
  • Get set of EC numbers for each graph.
  • Calculate difference of EC number graphs.
  • Print EC number edges.
Result 
751 results
C00002 -> 2.7.9.2 -> C00008
C00003 -> 6.3.1.5 -> C00857
C00006 -> 2.7.1.23 -> C00003
C00008 -> 2.7.9.2 -> C00002
C00010 -> 2.7.1.24 -> C00882
C00011 -> 1.1.1.40 -> C00149
C00011 -> 4.1.1.31 -> C00036
C00011 -> 4.1.1.49 -> C00036
C00014 -> 1.4.4.2 -> C00037
C00014 -> 1.8.1.4 -> C00037
C00014 -> 2.1.2.10 -> C00037
C00015 -> 2.7.4.25 -> C00105
C00016 -> 2.7.1.26 -> C00061
C00016 -> 2.7.7.2 -> C00061
C00018 -> 1.4.3.5 -> C00627
C00018 -> 1.4.3.5 -> C00647
C00018 -> 2.7.1.35 -> C00250
C00019 -> 2.5.1.6 -> C00073
C00020 -> 4.3.2.2 -> C03794
C00021 -> 2.1.1.37 -> C00019
C00022 -> 1.1.2.3 -> C00186
C00022 -> 1.2.4.1 -> C00024
C00022 -> 1.8.1.4 -> C00024
C00022 -> 2.3.1.12 -> C00024
C00022 -> 2.7.1.40 -> C00074
C00022 -> 2.7.4.6 -> C00074
C00022 -> 2.8.1.1 -> C00957
C00022 -> 2.8.1.2 -> C00957
C00022 -> 4.3.1.17 -> C00065
C00022 -> 4.3.1.19 -> C00065
C00024 -> 1.2.4.1 -> C00022
C00024 -> 1.8.1.4 -> C00022
C00024 -> 2.3.1.12 -> C00022
C00025 -> 1.4.1.13 -> C00026
C00025 -> 1.4.1.14 -> C00026
C00025 -> 2.6.1.1 -> C00026
C00025 -> 2.6.1.1 -> C00049
C00025 -> 3.5.1.96 -> C05931
C00026 -> 1.1.1.42 -> C00311
C00029 -> 2.7.7.9 -> C00052
C00031 -> 2.4.1.25 -> C00208
C00031 -> 3.2.1.20 -> C00089
C00031 -> 3.2.1.20 -> C00208
C00031 -> 3.2.1.21 -> C00185
C00031 -> 3.2.1.28 -> C01083
C00032 -> 4.99.1.1 -> C02191
C00032 -> 4.99.1.9 -> C02191
C00036 -> 1.4.3.16 -> C00049
C00036 -> 4.1.1.31 -> C00011
C00036 -> 4.1.1.31 -> C00074
C00036 -> 4.1.1.49 -> C00011
C00037 -> 2.1.2.10 -> C00065
C00037 -> 3.4.11.1 -> C01419
C00037 -> 3.4.11.2 -> C01419
C00037 -> 3.4.11.23 -> C01419
C00037 -> 3.4.13.- -> C01419
C00039 -> 2.7.7.7 -> C00458
C00039 -> 2.7.7.7 -> C00459
C00041 -> 2.8.1.7 -> C05688
C00041 -> 4.4.1.16 -> C05688
C00042 -> 1.2.1.16 -> C00232
C00042 -> 1.2.1.20 -> C00232
C00042 -> 1.2.1.24 -> C00232
C00042 -> 1.2.1.79 -> C00232
C00043 -> 2.3.1.157 -> C04501
C00043 -> 2.7.7.23 -> C04501
C00043 -> 5.1.3.14 -> C00645
C00046 -> 2.7.7.6 -> C00063
C00046 -> 2.7.7.6 -> C00075
C00047 -> 4.1.1.20 -> C00680
C00048 -> 1.1.3.15 -> C00160
C00048 -> 4.1.3.1 -> C00311
C00049 -> 2.6.1.1 -> C00025
C00049 -> 3.5.1.1 -> C00152
C00051 -> 6.3.2.3 -> C00037
C00051 -> 6.3.2.3 -> C00669
C00052 -> 2.7.7.9 -> C00029
C00052 -> 2.7.7.9 -> C00446
C00053 -> 2.7.1.25 -> C00224
C00055 -> 2.7.1.48 -> C00475
C00058 -> 1.2.1.2 -> C00080
C00059 -> 2.7.1.25 -> C00224
C00061 -> 2.7.1.26 -> C00255
C00061 -> 2.7.7.2 -> C00255
C00062 -> 4.3.2.1 -> C03406
C00063 -> 6.3.4.2 -> C00075
C00064 -> 6.3.1.2 -> C00014
C00064 -> 6.3.1.2 -> C00025
C00065 -> 2.1.2.10 -> C00037
C00065 -> 2.1.2.10 -> C00143
C00065 -> 3.1.3.3 -> C01005
C00068 -> 2.7.4.16 -> C01081
C00073 -> 2.1.1.10 -> C00155
C00073 -> 2.1.1.13 -> C00155
C00073 -> 2.1.1.14 -> C00155
C00073 -> 2.6.1.57 -> C01180
C00074 -> 2.7.4.6 -> C00022
C00074 -> 2.7.9.2 -> C00022
C00077 -> 3.5.1.16 -> C00437
C00078 -> 4.2.1.20 -> C00065
C00078 -> 4.2.1.20 -> C00463
C00080 -> 1.2.1.2 -> C00058
C00085 -> 2.2.1.1 -> C00279
C00085 -> 3.1.3.11 -> C00354
C00093 -> 2.7.1.30 -> C00116
C00094 -> 1.8.4.10 -> C00053
C00094 -> 1.8.4.8 -> C00053
C00095 -> 3.2.1.20 -> C00089
C00097 -> 2.5.1.47 -> C00283
C00097 -> 2.5.1.47 -> C00979
C00097 -> 3.4.11.1 -> C01419
C00097 -> 3.4.11.2 -> C01419
C00097 -> 3.4.11.23 -> C01419
C00097 -> 3.4.13.- -> C01419
C00099 -> 4.1.1.11 -> C00049
C00099 -> 4.1.1.15 -> C00049
C00100 -> 1.3.1.- -> C00894
C00100 -> 2.3.1.16 -> C03344
C00101 -> 1.5.1.3 -> C00504
C00101 -> 2.1.2.2 -> C00445
C00103 -> 2.4.1.1 -> C00369
C00103 -> 2.7.7.9 -> C00446
C00103 -> 3.2.1.196 -> C00369
C00105 -> 2.7.1.48 -> C00299
C00105 -> 2.7.4.25 -> C00015
C00105 -> 3.6.1.9 -> C00075
C00105 -> 4.1.1.23 -> C01103
C00106 -> 3.5.4.1 -> C00380
C00108 -> 2.4.2.18 -> C00251
C00108 -> 4.1.3.27 -> C00251
C00109 -> 2.5.1.48 -> C01118
C00109 -> 4.3.1.19 -> C00188
C00111 -> 2.7.1.- -> C00184
C00118 -> 4.1.2.21 -> C01286
C00120 -> 1.-.-.- -> C20386
C00120 -> 2.8.1.6 -> C01909
C00122 -> 4.3.1.1 -> C00049
C00122 -> 4.3.2.1 -> C03406
C00124 -> 3.2.1.23 -> C00243
C00129 -> 1.17.7.4 -> C11811
C00131 -> 1.1.98.6 -> C00002
C00134 -> 2.5.1.16 -> C00170
C00134 -> 3.5.3.11 -> C00179
C00134 -> 4.1.1.17 -> C00077
C00135 -> 1.1.1.23 -> C01929
C00137 -> 3.1.3.25 -> C03546
C00137 -> 3.1.3.25 -> C04006
C00140 -> 3.2.1.52 -> C01674
C00141 -> 4.2.1.9 -> C04272
C00143 -> 2.1.2.1 -> C01242
C00143 -> 2.1.2.10 -> C00065
C00143 -> 2.1.2.10 -> C01242
C00144 -> 6.3.5.2 -> C00655
C00147 -> 3.2.2.8 -> C00212
C00149 -> 1.1.1.40 -> C00011
C00152 -> 6.3.1.1 -> C00049
C00155 -> 2.5.1.48 -> C01077
C00155 -> 2.5.1.48 -> C01118
C00155 -> 4.4.1.21 -> C03539
C00155 -> 4.4.1.8 -> C02291
C00156 -> 2.5.1.39 -> C05848
C00157 -> 3.1.1.32 -> C01595
C00157 -> 3.1.1.4 -> C01595
C00158 -> 4.2.1.3 -> C00311
C00158 -> 4.2.1.99 -> C00311
C00160 -> 3.1.3.18 -> C00988
C00169 -> 6.3.5.5 -> C00064
C00170 -> 2.5.1.16 -> C00134
C00170 -> 2.5.1.16 -> C01137
C00173 -> 4.2.1.59 -> C19845
C00178 -> 2.4.2.4 -> C00214
C00179 -> 4.1.1.19 -> C00062
C00181 -> 3.2.1.37 -> C02352
C00185 -> 3.2.1.21 -> C01898
C00188 -> 4.2.3.1 -> C01102
C00191 -> 3.2.1.31 -> C03033
C00194 -> 2.5.1.17 -> C00853
C00194 -> 2.7.8.26 -> C05775
C00194 -> 2.7.8.26 -> C06510
C00198 -> 1.1.5.2 -> C00031
C00199 -> 1.1.1.343 -> C00345
C00199 -> 1.1.1.44 -> C00345
C00199 -> 2.7.1.19 -> C01182
C00204 -> 4.2.1.7 -> C00817
C00206 -> 1.17.4.1 -> C00008
C00208 -> 3.2.1.1 -> C01935
C00212 -> 3.1.3.5 -> C00020
C00212 -> 3.6.1.45 -> C00020
C00214 -> 3.1.3.5 -> C00364
C00214 -> 3.1.3.89 -> C00364
C00214 -> 3.6.1.45 -> C00364
C00217 -> 3.5.1.2 -> C00819
C00222 -> 3.5.1.- -> C20253
C00224 -> 2.7.1.25 -> C00059
C00224 -> 3.1.3.7 -> C00053
C00235 -> 2.5.1.75 -> C04432
C00245 -> 4.1.1.15 -> C00506
C00251 -> 4.2.3.5 -> C01269
C00253 -> 3.5.1.- -> C00153
C00253 -> 3.5.1.19 -> C00153
C00255 -> 2.5.1.9 -> C04332
C00255 -> 3.1.3.102 -> C00061
C00255 -> 3.1.3.104 -> C00061
C00255 -> 3.1.3.2 -> C00061
C00255 -> 3.1.3.26 -> C00061
C00262 -> 2.4.2.1 -> C05512
C00262 -> 3.5.4.2 -> C00147
C00267 -> 3.2.1.23 -> C00243
C00269 -> 2.7.7.41 -> C00416
C00275 -> 2.7.1.191 -> C00159
C00279 -> 2.2.1.1 -> C00085
C00279 -> 4.1.2.13 -> C00447
C00286 -> 1.1.98.6 -> C00044
C00286 -> 2.7.1.40 -> C00361
C00294 -> 3.1.3.5 -> C00130
C00294 -> 3.5.4.4 -> C00212
C00294 -> 3.6.1.45 -> C00130
C00299 -> 3.5.4.5 -> C00475
C00311 -> 1.1.1.42 -> C00026
C00311 -> 4.2.1.3 -> C00158
C00311 -> 4.2.1.99 -> C00158
C00315 -> 2.5.1.16 -> C00134
C00315 -> 2.5.1.16 -> C01137
C00327 -> 2.1.3.3 -> C00077
C00327 -> 2.1.3.3 -> C00169
C00327 -> 3.5.1.16 -> C15532
C00334 -> 1.2.1.19 -> C00555
C00334 -> 3.5.1.94 -> C15767
C00334 -> 4.1.1.15 -> C00025
C00341 -> 2.5.1.1 -> C00129
C00341 -> 2.5.1.1 -> C00235
C00341 -> 2.5.1.10 -> C00129
C00341 -> 2.5.1.10 -> C00235
C00344 -> 3.1.3.27 -> C03892
C00344 -> 3.1.3.4 -> C03892
C00344 -> 3.1.3.81 -> C03892
C00344 -> 3.6.1.27 -> C03892
C00345 -> 2.7.1.12 -> C00257
C00345 -> 3.1.1.31 -> C01236
C00350 -> 4.1.1.65 -> C02737
C00352 -> 2.6.1.16 -> C05345
C00357 -> 2.7.1.59 -> C00140
C00361 -> 1.17.4.1 -> C00035
C00364 -> 2.1.1.45 -> C00365
C00364 -> 2.7.1.21 -> C00214
C00365 -> 3.6.1.23 -> C00460
C00366 -> 1.17.1.4 -> C00385
C00369 -> 2.4.1.18 -> C00718
C00376 -> 1.1.1.1 -> C00473
C00376 -> 1.1.1.284 -> C00473
C00378 -> 3.1.3.1 -> C01081
C00378 -> 3.1.3.100 -> C01081
C00378 -> 3.6.1.- -> C01081
C00380 -> 3.2.2.8 -> C00475
C00385 -> 1.17.1.4 -> C00262
C00385 -> 3.5.4.3 -> C00242
C00387 -> 3.1.3.5 -> C00144
C00387 -> 3.6.1.45 -> C00144
C00399 -> 2.1.1.222 -> C17562
C00399 -> 2.1.1.64 -> C17562
C00415 -> 6.3.2.12 -> C00921
C00415 -> 6.3.2.17 -> C00921
C00416 -> 2.3.1.51 -> C00681
C00416 -> 2.7.1.107 -> C00641
C00430 -> 5.4.3.8 -> C03741
C00437 -> 2.6.1.11 -> C01250
C00437 -> 2.6.1.17 -> C01250
C00438 -> 2.1.3.2 -> C00169
C00440 -> 1.5.1.20 -> C00143
C00441 -> 1.2.1.11 -> C03082
C00445 -> 6.3.3.2 -> C03479
C00446 -> 2.7.1.6 -> C00984
C00446 -> 2.7.7.9 -> C00052
C00446 -> 2.7.7.9 -> C00103
C00447 -> 4.1.2.13 -> C00279
C00448 -> 2.5.1.1 -> C00129
C00448 -> 2.5.1.1 -> C00341
C00448 -> 2.5.1.10 -> C00129
C00448 -> 2.5.1.10 -> C00341
C00455 -> 2.7.1.22 -> C03150
C00455 -> 2.7.7.1 -> C03150
C00455 -> 3.6.1.22 -> C00003
C00455 -> 3.6.1.9 -> C00003
C00458 -> 1.1.98.6 -> C00063
C00460 -> 3.5.4.13 -> C00458
C00470 -> 3.1.1.11 -> C00714
C00473 -> 1.1.1.1 -> C00376
C00473 -> 1.1.1.284 -> C00376
C00519 -> 4.1.1.15 -> C00606
C00541 -> 1.16.1.3 -> C00992
C00541 -> 1.5.1.41 -> C00992
C00555 -> 2.6.1.82 -> C00134
C00558 -> 5.3.1.12 -> C00333
C00576 -> 1.1.99.1 -> C00114
C00590 -> 1.11.1.21 -> C15805
C00624 -> 2.3.1.1 -> C00025
C00627 -> 2.6.99.2 -> C11638
C00627 -> 2.7.1.35 -> C00314
C00631 -> 2.7.1.165 -> C00258
C00645 -> 5.1.3.14 -> C00043
C00647 -> 2.7.1.35 -> C00534
C00655 -> 1.1.1.205 -> C00130
C00666 -> 3.5.1.18 -> C04421
C00669 -> 6.3.2.2 -> C00025
C00669 -> 6.3.2.2 -> C00097
C00671 -> 4.2.1.9 -> C06007
C00681 -> 2.3.1.15 -> C00093
C00689 -> 2.4.1.15 -> C00029
C00692 -> 6.3.2.9 -> C01212
C00705 -> 1.17.4.1 -> C00112
C00718 -> 2.4.1.21 -> C00498
C00719 -> 1.2.1.8 -> C00576
C00721 -> 3.2.1.1 -> C00369
C00748 -> 1.3.1.76 -> C05778
C00748 -> 2.1.1.107 -> C05778
C00748 -> 4.99.1.4 -> C05778
C00760 -> 2.4.1.12 -> C00029
C00798 -> 4.1.1.8 -> C00313
C00817 -> 1.1.1.58 -> C00558
C00826 -> 2.6.1.57 -> C00254
C00828 -> 2.1.1.163 -> C05818
C00828 -> 2.1.1.201 -> C05818
C00860 -> 3.1.3.15 -> C01100
C00860 -> 4.2.1.19 -> C01100
C00864 -> 6.3.2.1 -> C00099
C00864 -> 6.3.2.1 -> C00522
C00877 -> 1.3.99.- -> C00136
C00921 -> 2.5.1.15 -> C00568
C00921 -> 2.5.1.15 -> C01300
C00921 -> 2.5.1.15 -> C04807
C00931 -> 4.2.1.24 -> C00430
C00944 -> 4.2.3.4 -> C04691
C00966 -> 2.1.2.11 -> C00141
C00984 -> 5.1.3.3 -> C00124
C00993 -> 6.3.2.4 -> C00133
C01007 -> 1.16.1.3 -> C00255
C01007 -> 1.5.1.41 -> C00255
C01013 -> 1.1.1.- -> C00222
C01013 -> 1.1.1.381 -> C00222
C01024 -> 2.5.1.61 -> C00931
C01037 -> 2.6.1.62 -> C01092
C01050 -> 1.3.1.98 -> C04631
C01051 -> 4.2.1.75 -> C01024
C01079 -> 1.3.3.3 -> C03263
C01079 -> 1.3.98.3 -> C03263
C01081 -> 2.5.1.3 -> C04327
C01081 -> 2.5.1.3 -> C04752
C01081 -> 2.5.1.3 -> C20247
C01081 -> 2.7.1.89 -> C00378
C01081 -> 3.1.3.100 -> C00068
C01081 -> 3.6.1.- -> C00068
C01083 -> 3.1.3.12 -> C00689
C01092 -> 2.3.1.47 -> C01063
C01092 -> 2.3.1.47 -> C19845
C01094 -> 2.7.1.202 -> C00095
C01097 -> 1.1.1.251 -> C06311
C01102 -> 2.7.1.39 -> C00263
C01134 -> 4.1.1.36 -> C04352
C01134 -> 6.3.2.5 -> C04352
C01137 -> 4.1.1.50 -> C00019
C01146 -> 4.1.1.47 -> C00048
C01146 -> 5.3.1.22 -> C00168
C01157 -> 1.5.1.2 -> C04281
C01165 -> 1.2.1.41 -> C03287
C01170 -> 5.1.3.14 -> C00043
C01182 -> 2.7.1.19 -> C00199
C01185 -> 2.4.2.19 -> C03722
C01185 -> 3.6.1.22 -> C00857
C01187 -> 3.1.3.45 -> C04478
C01190 -> 3.2.1.23 -> C01290
C01212 -> 6.3.2.8 -> C01050
C01216 -> 4.2.1.6 -> C00880
C01222 -> 4.2.1.47 -> C00096
C01236 -> 1.1.1.363 -> C01172
C01236 -> 1.1.1.49 -> C01172
C01242 -> 1.4.4.2 -> C00037
C01242 -> 2.1.2.1 -> C00143
C01250 -> 1.2.1.38 -> C04133
C01267 -> 3.1.3.15 -> C04666
C01267 -> 4.2.1.19 -> C04666
C01268 -> 1.1.1.193 -> C01304
C01268 -> 3.5.4.26 -> C01304
C01286 -> 2.7.1.58 -> C01216
C01300 -> 1.13.11.81 -> C04874
C01300 -> 4.1.2.25 -> C04874
C01300 -> 5.1.99.8 -> C04874
C01304 -> 3.5.4.25 -> C00044
C01419 -> 2.3.2.2 -> C00051
C01419 -> 3.4.19.13 -> C00051
C01528 -> 2.8.1.7 -> C05688
C01528 -> 4.4.1.16 -> C05688
C01595 -> 3.1.1.32 -> C00157
C01595 -> 3.1.1.4 -> C00157
C01672 -> 1.4.3.21 -> C12455
C01672 -> 4.1.1.18 -> C00047
C01674 -> 3.2.1.14 -> C00461
C01674 -> 3.2.1.17 -> C00461
C01762 -> 3.1.3.5 -> C00655
C01762 -> 3.6.1.45 -> C00655
C01847 -> 1.5.1.38 -> C00061
C01909 -> 6.3.3.3 -> C01037
C01929 -> 1.1.1.23 -> C00860
C02059 -> 2.1.1.163 -> C13309
C02059 -> 2.1.1.201 -> C13309
C02191 -> 1.3.5.3 -> C01079
C02222 -> 3.1.1.45 -> C16476
C02232 -> 1.1.1.35 -> C14145
C02232 -> 4.2.1.17 -> C14145
C02232 -> 5.1.2.3 -> C14145
C02232 -> 5.3.3.8 -> C14145
C02282 -> 6.1.1.18 -> C00064
C02291 -> 2.5.1.48 -> C01077
C02291 -> 2.5.1.48 -> C01118
C02325 -> 1.11.1.21 -> C15806
C02463 -> 1.3.1.76 -> C01051
C02463 -> 2.1.1.107 -> C01051
C02463 -> 4.99.1.4 -> C01051
C02504 -> 2.3.3.13 -> C00141
C02565 -> 3.5.4.1 -> C00791
C02646 -> 1.11.1.21 -> C15804
C02714 -> 2.3.1.57 -> C00134
C02723 -> 1.4.3.21 -> C06178
C02730 -> 4.2.1.113 -> C05817
C02737 -> 2.7.8.8 -> C00269
C02741 -> 3.5.4.19 -> C02739
C02741 -> 3.6.1.31 -> C02739
C02987 -> 6.1.1.17 -> C00025
C03028 -> 2.7.4.3 -> C00068
C03082 -> 1.1.1.3 -> C00049
C03082 -> 2.7.2.4 -> C00049
C03089 -> 3.2.2.9 -> C00170
C03090 -> 2.4.2.14 -> C00119
C03160 -> 6.2.1.26 -> C02730
C03175 -> 2.7.1.71 -> C00493
C03221 -> 1.3.99.- -> C01832
C03263 -> 4.1.1.37 -> C01051
C03287 -> 2.7.2.11 -> C00025
C03291 -> 4.1.1.85 -> C14899
C03296 -> 2.3.1.109 -> C00062
C03373 -> 6.3.3.1 -> C04640
C03406 -> 6.3.4.5 -> C00049
C03406 -> 6.3.4.5 -> C00327
C03415 -> 3.5.3.23 -> C03296
C03453 -> 5.3.2.6 -> C02501
C03492 -> 2.7.1.33 -> C00864
C03539 -> 3.2.2.9 -> C00021
C03589 -> 4.2.1.80 -> C00596
C03657 -> 3.1.2.28 -> C15547
C03684 -> 4.1.2.50 -> C04895
C03684 -> 4.2.3.12 -> C04895
C03722 -> 2.5.1.72 -> C05840
C03741 -> 1.2.1.70 -> C02987
C03794 -> 6.3.4.4 -> C00130
C03838 -> 2.1.2.3 -> C04376
C03838 -> 3.5.4.10 -> C04376
C03838 -> 6.3.4.13 -> C03090
C03892 -> 2.7.8.5 -> C00269
C03912 -> 1.2.1.88 -> C00148
C03912 -> 1.5.5.2 -> C00148
C03972 -> 1.17.1.8 -> C20258
C04043 -> 1.4.3.21 -> C03758
C04121 -> 2.7.7.38 -> C01187
C04133 -> 2.7.2.8 -> C00624
C04257 -> 2.7.1.60 -> C00645
C04317 -> 3.1.1.32 -> C05212
C04317 -> 3.1.1.4 -> C05212
C04327 -> 2.7.1.50 -> C04294
C04332 -> 2.5.1.78 -> C04732
C04332 -> 2.5.1.78 -> C15556
C04352 -> 4.1.1.36 -> C03492
C04352 -> 6.3.2.5 -> C03492
C04376 -> 2.1.2.2 -> C03838
C04376 -> 2.1.2.3 -> C03838
C04376 -> 3.5.4.10 -> C03838
C04405 -> 1.1.1.35 -> C03345
C04405 -> 4.2.1.17 -> C03345
C04405 -> 5.1.2.3 -> C03345
C04405 -> 5.3.3.8 -> C03345
C04432 -> 2.5.1.75 -> C00235
C04442 -> 2.7.1.45 -> C00204
C04442 -> 4.2.1.12 -> C00345
C04454 -> 1.1.1.193 -> C01268
C04454 -> 3.5.4.26 -> C01268
C04462 -> 2.3.1.117 -> C03972
C04478 -> 2.5.1.55 -> C01112
C04501 -> 2.3.1.157 -> C06156
C04501 -> 2.7.7.23 -> C06156
C04556 -> 2.7.1.49 -> C01279
C04556 -> 2.7.4.7 -> C01279
C04556 -> 4.1.99.17 -> C03373
C04631 -> 2.5.1.7 -> C00043
C04635 -> 3.1.1.32 -> C04756
C04635 -> 3.1.1.4 -> C04756
C04640 -> 6.3.5.3 -> C04376
C04652 -> 2.3.1.191 -> C06022
C04666 -> 2.4.2.- -> C04916
C04666 -> 4.1.3.- -> C04916
C04677 -> 2.1.2.2 -> C04734
C04691 -> 2.5.1.54 -> C00074
C04691 -> 2.5.1.54 -> C00279
C04702 -> 6.3.2.10 -> C05892
C04732 -> 3.1.3.102 -> C04454
C04732 -> 3.1.3.104 -> C04454
C04734 -> 2.1.2.2 -> C04677
C04734 -> 2.1.2.3 -> C04677
C04734 -> 3.5.4.10 -> C04677
C04738 -> 2.3.1.129 -> C00043
C04752 -> 2.7.1.49 -> C04556
C04752 -> 2.7.4.7 -> C04556
C04778 -> 2.4.2.21 -> C03114
C04807 -> 2.7.6.3 -> C01300
C04824 -> 3.6.1.54 -> C04652
C04851 -> 2.7.8.13 -> C04702
C04874 -> 3.1.3.1 -> C04895
C04895 -> 3.5.4.16 -> C06148
C04896 -> 3.5.4.19 -> C02741
C04896 -> 3.6.1.31 -> C02741
C04916 -> 5.3.1.16 -> C04896
C04919 -> 2.7.1.130 -> C04932
C04932 -> 2.4.1.182 -> C04652
C04932 -> 2.4.1.182 -> C04824
C05172 -> 2.7.9.3 -> C01528
C05271 -> 1.3.99.- -> C05270
C05272 -> 1.3.99.- -> C00154
C05273 -> 1.3.99.- -> C02593
C05275 -> 1.3.99.- -> C05274
C05276 -> 1.3.99.- -> C01944
C05345 -> 2.7.1.4 -> C00095
C05345 -> 3.1.3.11 -> C05378
C05345 -> 3.5.99.6 -> C00352
C05378 -> 2.7.1.11 -> C05345
C05527 -> 2.6.1.1 -> C00606
C05744 -> 2.3.1.179 -> C01209
C05744 -> 2.3.1.179 -> C03939
C05744 -> 2.3.1.180 -> C01209
C05744 -> 2.3.1.41 -> C01209
C05744 -> 2.3.1.41 -> C03939
C05746 -> 2.3.1.179 -> C01209
C05746 -> 2.3.1.179 -> C05745
C05746 -> 2.3.1.41 -> C01209
C05746 -> 2.3.1.41 -> C05745
C05750 -> 2.3.1.179 -> C01209
C05750 -> 2.3.1.179 -> C05749
C05750 -> 2.3.1.41 -> C01209
C05750 -> 2.3.1.41 -> C05749
C05753 -> 2.3.1.179 -> C01209
C05753 -> 2.3.1.179 -> C05752
C05753 -> 2.3.1.41 -> C01209
C05753 -> 2.3.1.41 -> C05752
C05756 -> 2.3.1.179 -> C01209
C05756 -> 2.3.1.179 -> C05755
C05756 -> 2.3.1.41 -> C01209
C05756 -> 2.3.1.41 -> C05755
C05759 -> 2.3.1.179 -> C01209
C05759 -> 2.3.1.179 -> C05223
C05759 -> 2.3.1.41 -> C01209
C05759 -> 2.3.1.41 -> C05223
C05762 -> 2.3.1.179 -> C01209
C05762 -> 2.3.1.179 -> C05761
C05762 -> 2.3.1.41 -> C01209
C05762 -> 2.3.1.41 -> C05761
C05768 -> 4.1.1.37 -> C05766
C05775 -> 3.1.3.73 -> C04778
C05778 -> 1.3.1.76 -> C02463
C05778 -> 2.1.1.107 -> C02463
C05778 -> 4.99.1.4 -> C02463
C05791 -> 3.2.1.31 -> C05787
C05807 -> 1.14.13.- -> C17551
C05807 -> 2.5.1.129 -> C05848
C05807 -> 4.1.1.98 -> C05848
C05817 -> 4.2.99.20 -> C16519
C05818 -> 2.5.1.- -> C03657
C05818 -> 2.5.1.74 -> C03657
C05840 -> 1.4.3.16 -> C00049
C05848 -> 2.5.1.129 -> C05807
C05848 -> 2.5.1.39 -> C00156
C05848 -> 4.1.1.98 -> C05807
C05893 -> 2.4.1.227 -> C04851
C05921 -> 6.3.4.15 -> C00120
C05922 -> 3.5.4.16 -> C00044
C05923 -> 3.5.4.16 -> C05922
C05924 -> 2.8.1.12 -> C18239
C05931 -> 1.2.1.71 -> C05932
C05932 -> 2.6.1.81 -> C03415
C05946 -> 2.6.1.1 -> C05947
C05947 -> 1.2.1.88 -> C04281
C05947 -> 1.5.5.2 -> C04281
C05980 -> 2.7.8.- -> C00344
C06000 -> 1.1.1.35 -> C03460
C06000 -> 4.2.1.17 -> C03460
C06000 -> 5.1.2.3 -> C03460
C06000 -> 5.3.3.8 -> C03460
C06001 -> 1.1.1.35 -> C06002
C06001 -> 4.2.1.17 -> C06002
C06001 -> 5.1.2.3 -> C06002
C06001 -> 5.3.3.8 -> C06002
C06002 -> 1.1.1.35 -> C06001
C06002 -> 4.2.1.17 -> C06001
C06002 -> 5.1.2.3 -> C06001
C06002 -> 5.3.3.8 -> C06001
C06006 -> 2.2.1.6 -> C00022
C06006 -> 2.2.1.6 -> C00109
C06010 -> 2.2.1.6 -> C00022
C06022 -> 3.5.1.108 -> C04738
C06024 -> 2.4.99.12 -> C04121
C06024 -> 2.4.99.12 -> C04919
C06024 -> 2.4.99.13 -> C04121
C06024 -> 2.4.99.13 -> C04919
C06024 -> 2.4.99.14 -> C04121
C06024 -> 2.4.99.14 -> C04919
C06024 -> 2.4.99.15 -> C04121
C06024 -> 2.4.99.15 -> C04919
C06025 -> 2.4.99.12 -> C04121
C06025 -> 2.4.99.12 -> C06024
C06025 -> 2.4.99.13 -> C04121
C06025 -> 2.4.99.13 -> C06024
C06025 -> 2.4.99.14 -> C04121
C06025 -> 2.4.99.14 -> C06024
C06025 -> 2.4.99.15 -> C04121
C06025 -> 2.4.99.15 -> C06024
C06026 -> 2.3.1.243 -> C06251
C06040 -> 2.7.8.20 -> C06041
C06041 -> 2.7.8.20 -> C06040
C06148 -> 3.5.4.16 -> C05923
C06157 -> 1.2.4.2 -> C00322
C06178 -> 1.4.3.21 -> C02723
C06250 -> 6.3.4.15 -> C05921
C06251 -> 2.3.1.241 -> C06025
C06311 -> 2.7.1.200 -> C01697
C06329 -> 3.1.1.45 -> C04706
C06397 -> 2.7.1.167 -> C07838
C06397 -> 2.7.7.70 -> C07838
C06398 -> 5.1.3.20 -> C06397
C06427 -> 3.1.1.32 -> C00157
C06427 -> 3.1.1.4 -> C00157
C06506 -> 2.5.1.17 -> C06505
C06509 -> 2.7.1.156 -> C06508
C06509 -> 2.7.7.62 -> C06508
C06510 -> 2.7.1.156 -> C06509
C06510 -> 2.7.7.62 -> C06509
C06613 -> 1.1.1.1 -> C06611
C06613 -> 1.1.1.284 -> C06611
C06613 -> 1.2.1.10 -> C06611
C07086 -> 1.2.1.39 -> C00601
C07335 -> 1.1.1.262 -> C06055
C07479 -> 5.3.2.6 -> C07478
C07836 -> 5.3.1.28 -> C05382
C07838 -> 3.1.3.82 -> C11472
C07838 -> 3.1.3.83 -> C11472
C11434 -> 1.1.1.267 -> C11437
C11435 -> 2.7.7.60 -> C11434
C11436 -> 2.7.1.148 -> C11435
C11453 -> 4.6.1.12 -> C11436
C11472 -> 2.7.1.167 -> C07836
C11472 -> 2.7.7.70 -> C07836
C11811 -> 1.17.7.1 -> C11453
C11811 -> 1.17.7.3 -> C11453
C12248 -> 3.5.2.17 -> C11821
C12455 -> 1.4.3.21 -> C01672
C12835 -> 3.1.1.45 -> C12834
C13309 -> 2.5.1.- -> C03657
C13309 -> 2.5.1.74 -> C03657
C14145 -> 1.1.1.35 -> C14144
C14145 -> 4.2.1.17 -> C14144
C14145 -> 5.1.2.3 -> C14144
C14145 -> 5.3.3.8 -> C14144
C14899 -> 3.1.1.- -> C16186
C15556 -> 4.1.99.12 -> C00199
C15667 -> 6.3.4.18 -> C03373
C15672 -> 2.5.1.- -> C00032
C15699 -> 6.3.1.11 -> C00134
C15700 -> 1.4.3.- -> C15699
C15767 -> 1.2.1.99 -> C15700
C15804 -> 1.11.1.21 -> C02646
C15805 -> 1.11.1.21 -> C00590
C15806 -> 1.11.1.21 -> C02325
C15809 -> 4.1.99.19 -> C00082
C15812 -> 2.8.1.7 -> C00097
C15812 -> 2.8.1.7 -> C15811
C15813 -> 2.7.7.73 -> C15810
C15814 -> 2.8.1.4 -> C15812
C15814 -> 2.8.1.4 -> C15813
C15996 -> 6.3.4.20 -> C20248
C16186 -> 2.7.1.194 -> C00072
C16236 -> 2.3.1.181 -> C05752
C16237 -> 2.3.1.181 -> C16239
C16237 -> 2.8.1.8 -> C16236
C16237 -> 6.3.1.20 -> C16241
C16239 -> 2.8.1.8 -> C05752
C16331 -> 2.3.1.16 -> C16330
C16335 -> 2.3.1.16 -> C16334
C16339 -> 2.3.1.16 -> C16338
C16348 -> 1.1.1.1 -> C06612
C16348 -> 1.1.1.284 -> C06612
C16348 -> 1.2.1.10 -> C06612
C16519 -> 2.2.1.9 -> C00885
C16675 -> 1.7.1.13 -> C15996
C17551 -> 1.14.13.- -> C05807
C17551 -> 2.1.1.222 -> C17552
C17551 -> 2.1.1.64 -> C17552
C17552 -> 1.14.13.- -> C17560
C17552 -> 2.1.1.222 -> C17551
C17552 -> 2.1.1.64 -> C17551
C17560 -> 1.14.13.- -> C17552
C17560 -> 2.1.1.163 -> C17561
C17560 -> 2.1.1.201 -> C17561
C17561 -> 1.14.13.- -> C17562
C17561 -> 2.1.1.163 -> C17560
C17561 -> 2.1.1.201 -> C17560
C17562 -> 1.14.13.- -> C17561
C17562 -> 2.1.1.222 -> C00399
C17562 -> 2.1.1.64 -> C00399
C18237 -> 2.10.1.1 -> C19848
C18239 -> 4.6.1.17 -> C21310
C19673 -> 2.1.1.197 -> C01209
C19845 -> 3.1.1.85 -> C19846
C19845 -> 4.2.1.59 -> C00173
C19846 -> 1.3.1.10 -> C20378
C19846 -> 1.3.1.9 -> C20378
C19848 -> 2.7.7.75 -> C05924
C19871 -> 2.7.7.77 -> C18237
C20231 -> 1.14.99.46 -> C00106
C20231 -> 1.5.1.- -> C00106
C20239 -> 4.1.2.50 -> C04895
C20239 -> 4.2.3.12 -> C04895
C20246 -> 2.8.1.10 -> C11437
C20246 -> 2.8.1.10 -> C15809
C20246 -> 2.8.1.10 -> C15814
C20248 -> 4.3.99.3 -> C20239
C20249 -> 3.5.1.110 -> C20231
C20258 -> 4.3.3.7 -> C00441
C20372 -> 2.3.1.179 -> C01209
C20372 -> 2.3.1.179 -> C19673
C20372 -> 2.3.1.41 -> C01209
C20372 -> 2.3.1.41 -> C19673
C20373 -> 1.1.1.100 -> C20372
C20374 -> 4.2.1.59 -> C20373
C20375 -> 1.3.1.10 -> C20374
C20375 -> 1.3.1.9 -> C20374
C20376 -> 2.3.1.179 -> C01209
C20376 -> 2.3.1.179 -> C20375
C20376 -> 2.3.1.41 -> C01209
C20376 -> 2.3.1.41 -> C20375
C20377 -> 1.1.1.100 -> C20376
C21015 -> 6.3.2.2 -> C02356
C21016 -> 6.3.2.3 -> C21015
C21284 -> 4.99.1.1 -> C05770
C21284 -> 4.99.1.9 -> C05770
C21310 -> 4.1.99.22 -> C00044
G09660 -> 3.2.1.31 -> G13040
G13040 -> 3.2.1.31 -> G09660
Conclusion

The overview map eco01100 contians many more EC number edges than the single pathway maps combined. This might mostly be due to the edges in 01100 being undirected. It may, however, be that some EC numbers are themselves missing and thus also their edges.

FEV_KEGG.Experiments.09 module
Question

Which reactions, independent of substrate and product, are present in eco01100, but not in a combination of all non-overview metabolic pathways?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Get set of reactions for each graph.
  • Calculate difference of reaction sets.
  • Print reactions (reaction ID).
Result 
161 results
R00107
R00149
R00160
R00173
R00185
R00206
R00209
R00229
R00243
R00257
R00287
R00305
R00320
R00346
R00352
R00369
R00396
R00400
R00414
R00431
R00432
R00502
R00530
R00531
R00550
R00616
R00618
R00648
R00688
R00689
R00692
R00703
R00709
R00710
R00717
R00726
R00727
R00729
R00746
R00841
R00859
R00861
R00866
R00883
R00895
R00907
R00943
R00951
R00978
R01022
R01039
R01063
R01067
R01088
R01122
R01128
R01151
R01156
R01171
R01176
R01217
R01218
R01225
R01278
R01287
R01290
R01324
R01326
R01415
R01434
R01447
R01523
R01555
R01667
R01730
R01741
R01769
R01788
R01829
R01867
R01869
R01911
R01967
R01986
R02014
R02020
R02022
R02073
R02089
R02107
R02124
R02189
R02197
R02239
R02282
R02296
R02415
R02474
R02494
R02537
R02596
R02727
R02821
R03222
R03295
R03354
R03438
R03776
R03856
R03919
R03989
R04007
R04027
R04230
R04413
R04432
R04753
R04859
R04985
R05000
R05053
R05081
R05198
R05705
R06613
R06740
R06975
R06985
R07064
R07147
R07276
R07279
R07376
R07407
R07410
R07818
R08211
R08379
R08557
R08558
R08574
R08714
R08768
R08769
R08773
R08774
R08775
R08781
R09084
R09085
R09127
R09254
R09281
R09944
R10161
R10178
R10305
R10343
R10404
R10699
R11308
Conclusion

The overview map eco01100 contains reactions that are not present in any of the single metabolism pathways.

Further research shows the reasons for such strange results:

  • There seems to have been some mistake in creating eco01100, because some genes are assigned reactions which actually belong to a different enzyme function. Example: R10699. Eco01100 maps this to the gene eco:b0774, which is classified as EC:2.6.1.62, which actually only performs R03231. Under this reaction, the gene occurs in pathway 00780 and 01100, the latter just adds rn:R10699, for an unknown reason. R10699 actually performs a different enzyme function: 2.6.1.105. This function does not occur in any enzyme associated with an eco gene.
  • Some single pathway files in KGML format do not contain a “reaction tag”, even though they should, according to the “entry tags” present in the same file and the pathway image. Example: R05000 only exists in eco011000, but not in eco00130, where it should, because eco00130 contains all compound and gene entries necessary for this reaction. It simply does not contain the “reaction tag”, probably due to an error in KEGG’s algorithms for creating KGML files.
  • Maybe more.

The overview map 01100 is unreliable and should, thus, not be used for exact research of reactions. However, using only the single pathways can also be unreliable, if the graph construction was to rely upon the “reaction tag”.

One solution could be to combine all single pathways plus the overview pathway 01100. But this adds reactions unknown to any single pathway. These reactions could possibly represent enzymes not present in any single pathway, but they might not. In case no additional enzymes occur in 01100, this solution would at least work on the substance-gene level and onward.

Another solution could be not to rely upon “reaction tags”, which represent pre-computed graph data. Then, however, we would have to compute the graph data ourselves, requiring a constant factor of more downloads (EC or KO files, plus reaction files) from KEGG (factor of roughly 10) and more computation time needed.

FEV_KEGG.Experiments.10 module
Question

Which EC numbers, independent of substrate and product, are present in eco01100, but not in a combination of all non-overview metabolic pathways?

Method
  • Download pathway description as KGML.
  • Convert to substance-reaction graph.
  • Convert to substance-gene graph.
  • Convert to substance-ec graph.
  • Get set of EC numbers for each graph.
  • Calculate difference of EC number sets.
  • Print EC numbers.
Result 
8 results
1.14.13.-
2.1.1.222
2.1.1.64
2.5.1.39
2.5.1.75
2.7.1.19
2.7.8.20
4.1.1.98
Conclusion

The overview map eco01100 contains genes, leading to EC numbers, that are not present in any of the single metabolism pathways.

Further research shows the reasons for such strange results:

  • Some single pathway files in KGML format do not contain a “reaction tag”, even though they should, according to the “entry tags” present in the same file and the pathway image. Example: Reaction R05000 only exists in eco011000, but not in eco00130, where it should, because eco00130 contains all compound and gene entries necessary for this reaction. Eco00130 simply does not contain the “reaction tag”, probably due to an error in KEGG’s algorithms for creating KGML files.
  • The overview map eco01100 contains more gene entries and thus enzymes than the single pathways combined. In the above cases, this was probably not an error in eco01100, but in the respective single pathway maps. Although it may occur in different organisms, that 01100 falsly lists a non-existing gene, genes are still organism-specific and the attempt to download a non-existing gene would simply throw a download error and would, thus, not remain undetected. In reverse conclusion, all the genes (leading to the EC numbers) listed above actually do exist in eco and the error lies within the single pathway maps, not within the overview map 01100. Example: 2.7.8.20 is the function of gene eco:b4359, which occurs in eco01100, but not in eco00561, where it probably should occur, too, because 2.7.8.20 is part of the general map 00561.
  • Maybe more.

Neiter using only 01100, nor only a combination of single pathways is perfect. 01100 has the following shortcomings: - No directed edges, irreversible reactions are handled as reversible.

  • Erroneous additional reactions, which are linked to EC numbers not present in any gene of the organism. This only affects the substance-reaction graph, since the erroneous reaction will not be translated into a gene for the substance-gene graph.
  • Some EC number edges are missing. The EC number itself is present, but not between all substrate/product combinations.
  • Some EC numbers themselves are missing.

The combination of all single pathways has the following shortcomings:

  • Some EC numbers themselves are missing. Due to missing “reaction tags” (fixable without 01100) AND due to missing gene entries (not fixable without 01100).

Solution A: Use combined single pathways, ignore missing EC numbers. Solution B: Use combined single pathways, repair by comparison with overview map 01100, adding missing “reaction tags” and missing gene entries.

FEV_KEGG.Experiments.11 module
Question

Does a simple UNION operation on node sets and edge sets suffice for combining several pathways to a global metabolic network?

Method
  • Download pathway descriptions as KGML -> eco00260 and eco00270.
  • Convert to substance-reaction graphs -> eco00260_graph and eco00270_graph.
  • Combine the pathways via UNION operation -> union_graph.
  • Subtract the individual parts of the resulting network. Firstly, without subtracting nodes, to leave any surviving edges -> subtracted_graph_keeping_nodes. Secondly, with subtracting nodes -> subtracted_graph_deleting_nodes.
  • Print any edge that remains in subtracted_graph_keeping_nodes. Print any node that remains in subtracted_graph_deleting_nodes.
Result 
0 results
Conclusion

UNION is indeed correctly implemented and fit for the task of combining several pathways to a global network.

FEV_KEGG.Experiments.12 module
Question

Which EC numbers are not present in all Escherichia coli K-12 organisms?

Method
  • Get all metabolic pathways of all E. coli K-12 organisms from KEGG.
  • For each organism, combine all pathways to the metabolic network, by UNION operation.
  • Convert this metabolic network into a substance-ecNumber graph.
  • Combine all organisms’ networks to a single unified E. coli network, by UNION operation.
  • Combine all organisms’ networks to a consensus network, by INTERSECT operation, leaving only substances and EC numbers that occur in all organisms.
  • Subtract the consensus network from the E. coli network, by DIFFERENCE operation, leaving only substances and EC numbers that do not occur in all organisms.
  • Print all EC numbers that do not occur in all organisms.
Result 
69 results
1.1.1.-
1.1.1.133
1.1.1.157
1.1.1.251
1.1.1.271
1.1.1.28
1.1.1.381
1.1.1.57
1.1.1.58
1.1.1.65
1.1.1.85
1.1.3.15
1.14.11.17
1.14.13.149
1.16.3.1
1.17.1.9
1.2.1.16
1.2.1.2
1.2.1.20
1.2.1.39
1.2.1.79
1.2.1.91
1.2.7.-
1.2.7.1
1.4.3.21
1.5.1.34
2.1.1.10
2.1.2.10
2.3.1.174
2.3.1.223
2.3.3.13
2.3.3.5
2.5.1.7
2.6.1.16
2.7.1.16
2.7.1.200
2.7.1.6
2.7.7.13
2.7.8.7
2.8.3.-
2.9.1.1
3.1.2.-
3.1.3.7
3.2.1.14
3.2.1.17
3.2.1.23
3.2.1.37
3.3.2.12
3.5.1.25
3.5.4.1
4.1.3.30
4.1.3.39
4.2.1.33
4.2.1.35
4.2.1.47
4.2.1.79
4.2.1.80
4.2.1.9
4.4.1.15
4.6.1.1
5.1.3.13
5.3.1.4
5.3.2.6
5.3.3.18
5.4.2.8
5.4.99.2
5.4.99.9
6.2.1.17
6.2.1.30
Conclusion

Some EC numbers are not shared between organisms. It could make sense to ignore incomplete EC numbers, as they may represent identical reactions on identical substances and could, thus, be counted twice. For example, 1.2.7.- might merely represent incomplete data, while the associated enzyme actually performs 1.2.7.1., causing a duplicate in the result list.

FEV_KEGG.Experiments.13 module
Question

Which EC numbers are present in all Escherichia coli K-12 organisms?

Method
  • Get all metabolic pathways of all E. coli organisms from KEGG.
  • For each organisms, combine all pathways to the metabolic network, by UNION operation.
  • Convert this metabolic network into a substance-ecNumber graph.
  • Combine all organisms’ networks to a consensus network, by INTERSECT operation, leaving only substances and EC numbers that occur in all organisms.
  • Print all EC numbers that occur in all organisms.
Result 
560 results
1.-.-.-
1.1.-.-
1.1.1.-
1.1.1.1
1.1.1.100
1.1.1.103
1.1.1.127
1.1.1.130
1.1.1.140
1.1.1.169
1.1.1.17
1.1.1.205
1.1.1.22
1.1.1.23
1.1.1.25
1.1.1.262
1.1.1.267
1.1.1.282
1.1.1.290
1.1.1.336
1.1.1.350
1.1.1.37
1.1.1.38
1.1.1.380
1.1.1.40
1.1.1.42
1.1.1.6
1.1.1.60
1.1.1.77
1.1.1.86
1.1.1.94
1.1.2.3
1.1.5.12
1.1.5.2
1.1.5.3
1.1.5.4
1.1.98.6
1.1.99.1
1.11.1.21
1.11.1.6
1.11.1.9
1.12.99.6
1.13.11.16
1.14.12.19
1.14.13.127
1.14.14.5
1.14.99.46
1.17.1.4
1.17.1.8
1.17.4.1
1.17.7.4
1.18.1.3
1.2.1.-
1.2.1.11
1.2.1.12
1.2.1.19
1.2.1.38
1.2.1.41
1.2.1.70
1.2.1.71
1.2.1.72
1.2.1.8
1.2.1.99
1.2.4.1
1.2.4.2
1.2.5.1
1.3.1.-
1.3.1.1
1.3.1.28
1.3.1.87
1.3.1.98
1.3.3.3
1.3.5.2
1.3.5.3
1.3.5.4
1.3.98.3
1.3.99.-
1.4.1.4
1.4.3.-
1.4.3.16
1.4.3.5
1.4.4.2
1.4.5.1
1.5.1.-
1.5.1.2
1.5.1.20
1.5.1.3
1.5.1.38
1.6.1.1
1.6.1.2
1.6.5.2
1.7.1.13
1.7.1.15
1.7.1.7
1.7.2.2
1.7.99.-
1.7.99.1
1.8.1.2
1.8.1.4
1.8.1.7
1.8.1.9
1.8.4.14
1.8.5.3
1.97.1.9
2.1.1.13
2.1.1.14
2.1.1.197
2.1.1.37
2.1.1.45
2.1.2.1
2.1.2.11
2.1.2.2
2.1.2.9
2.1.3.2
2.1.3.3
2.10.1.1
2.2.1.1
2.2.1.2
2.2.1.6
2.2.1.7
2.2.1.9
2.3.1.-
2.3.1.1
2.3.1.109
2.3.1.117
2.3.1.12
2.3.1.129
2.3.1.15
2.3.1.16
2.3.1.179
2.3.1.180
2.3.1.181
2.3.1.183
2.3.1.191
2.3.1.241
2.3.1.243
2.3.1.29
2.3.1.30
2.3.1.39
2.3.1.41
2.3.1.46
2.3.1.47
2.3.1.51
2.3.1.54
2.3.1.57
2.3.1.61
2.3.1.8
2.3.1.9
2.3.3.1
2.3.3.9
2.4.1.1
2.4.1.12
2.4.1.15
2.4.1.18
2.4.1.182
2.4.1.21
2.4.1.227
2.4.1.25
2.4.1.7
2.4.2.-
2.4.2.1
2.4.2.10
2.4.2.14
2.4.2.17
2.4.2.19
2.4.2.21
2.4.2.22
2.4.2.3
2.4.2.4
2.4.2.53
2.4.2.7
2.4.2.8
2.4.2.9
2.5.1.-
2.5.1.129
2.5.1.15
2.5.1.16
2.5.1.17
2.5.1.18
2.5.1.19
2.5.1.3
2.5.1.31
2.5.1.47
2.5.1.48
2.5.1.54
2.5.1.55
2.5.1.6
2.5.1.61
2.5.1.72
2.5.1.78
2.5.1.9
2.5.1.90
2.6.1.1
2.6.1.19
2.6.1.42
2.6.1.52
2.6.1.57
2.6.1.62
2.6.1.66
2.6.1.81
2.6.1.82
2.6.1.85
2.6.1.87
2.6.1.9
2.6.99.2
2.7.1.-
2.7.1.107
2.7.1.11
2.7.1.12
2.7.1.130
2.7.1.148
2.7.1.15
2.7.1.165
2.7.1.17
2.7.1.191
2.7.1.192
2.7.1.193
2.7.1.194
2.7.1.197
2.7.1.198
2.7.1.199
2.7.1.2
2.7.1.201
2.7.1.202
2.7.1.21
2.7.1.23
2.7.1.24
2.7.1.25
2.7.1.30
2.7.1.33
2.7.1.35
2.7.1.39
2.7.1.4
2.7.1.40
2.7.1.45
2.7.1.48
2.7.1.5
2.7.1.50
2.7.1.51
2.7.1.53
2.7.1.55
2.7.1.56
2.7.1.58
2.7.1.59
2.7.1.60
2.7.1.71
2.7.1.73
2.7.1.83
2.7.1.89
2.7.2.1
2.7.2.11
2.7.2.15
2.7.2.2
2.7.2.3
2.7.2.4
2.7.2.8
2.7.4.16
2.7.4.22
2.7.4.23
2.7.4.25
2.7.4.3
2.7.4.6
2.7.4.8
2.7.4.9
2.7.6.1
2.7.6.3
2.7.7.12
2.7.7.18
2.7.7.24
2.7.7.27
2.7.7.3
2.7.7.38
2.7.7.4
2.7.7.41
2.7.7.6
2.7.7.60
2.7.7.7
2.7.7.73
2.7.7.75
2.7.7.76
2.7.7.77
2.7.7.8
2.7.7.9
2.7.8.-
2.7.8.13
2.7.8.26
2.7.8.37
2.7.8.5
2.7.8.8
2.7.9.2
2.7.9.3
2.8.1.1
2.8.1.10
2.8.1.12
2.8.1.4
2.8.1.6
2.8.1.7
2.8.1.8
3.1.1.-
3.1.1.11
3.1.1.31
3.1.1.45
3.1.1.5
3.1.1.85
3.1.2.-
3.1.2.12
3.1.2.28
3.1.2.6
3.1.3.1
3.1.3.10
3.1.3.11
3.1.3.12
3.1.3.18
3.1.3.2
3.1.3.25
3.1.3.27
3.1.3.3
3.1.3.45
3.1.3.5
3.1.3.70
3.1.3.73
3.1.3.89
3.1.4.14
3.1.4.46
3.1.4.53
3.1.4.55
3.1.5.1
3.1.6.1
3.2.1.1
3.2.1.196
3.2.1.20
3.2.1.21
3.2.1.22
3.2.1.23
3.2.1.28
3.2.1.31
3.2.1.52
3.2.1.86
3.2.1.93
3.2.2.4
3.2.2.8
3.2.2.9
3.4.11.1
3.4.11.2
3.4.11.23
3.4.13.-
3.5.1.-
3.5.1.1
3.5.1.10
3.5.1.108
3.5.1.110
3.5.1.16
3.5.1.18
3.5.1.2
3.5.1.25
3.5.1.42
3.5.1.94
3.5.1.96
3.5.2.17
3.5.2.2
3.5.2.3
3.5.2.5
3.5.3.11
3.5.3.23
3.5.3.26
3.5.3.9
3.5.4.13
3.5.4.16
3.5.4.2
3.5.4.25
3.5.4.3
3.5.4.4
3.5.4.5
3.5.99.6
3.6.1.-
3.6.1.13
3.6.1.22
3.6.1.23
3.6.1.26
3.6.1.27
3.6.1.41
3.6.1.54
3.6.1.63
3.6.1.66
3.6.1.67
3.6.1.7
3.6.1.9
3.7.1.14
4.1.1.11
4.1.1.15
4.1.1.17
4.1.1.18
4.1.1.19
4.1.1.20
4.1.1.23
4.1.1.31
4.1.1.37
4.1.1.41
4.1.1.47
4.1.1.49
4.1.1.50
4.1.1.65
4.1.1.8
4.1.1.85
4.1.2.13
4.1.2.17
4.1.2.19
4.1.2.20
4.1.2.21
4.1.2.4
4.1.2.40
4.1.2.48
4.1.2.53
4.1.3.-
4.1.3.1
4.1.3.27
4.1.3.3
4.1.3.36
4.1.3.38
4.1.3.40
4.1.99.1
4.1.99.12
4.1.99.17
4.1.99.19
4.1.99.22
4.2.1.1
4.2.1.10
4.2.1.104
4.2.1.11
4.2.1.113
4.2.1.12
4.2.1.126
4.2.1.2
4.2.1.20
4.2.1.24
4.2.1.3
4.2.1.32
4.2.1.40
4.2.1.42
4.2.1.46
4.2.1.59
4.2.1.6
4.2.1.7
4.2.1.70
4.2.1.75
4.2.1.8
4.2.1.90
4.2.3.1
4.2.3.3
4.2.3.4
4.2.3.5
4.2.99.20
4.3.1.1
4.3.1.17
4.3.1.18
4.3.1.19
4.3.1.7
4.3.2.1
4.3.2.2
4.3.2.3
4.3.3.7
4.3.99.3
4.4.1.21
4.4.1.5
4.4.1.8
4.6.1.12
4.6.1.17
4.7.1.1
5.1.1.1
5.1.1.3
5.1.1.7
5.1.3.-
5.1.3.1
5.1.3.14
5.1.3.15
5.1.3.2
5.1.3.20
5.1.3.22
5.1.3.3
5.1.3.4
5.1.3.9
5.1.99.7
5.3.1.-
5.3.1.1
5.3.1.12
5.3.1.13
5.3.1.14
5.3.1.16
5.3.1.17
5.3.1.22
5.3.1.28
5.3.1.5
5.3.1.6
5.3.1.8
5.3.1.9
5.3.3.2
5.4.2.10
5.4.2.11
5.4.2.12
5.4.2.2
5.4.2.6
5.4.2.7
5.4.3.8
5.4.4.2
5.4.99.18
6.1.1.1
6.1.1.10
6.1.1.11
6.1.1.12
6.1.1.14
6.1.1.15
6.1.1.16
6.1.1.17
6.1.1.18
6.1.1.19
6.1.1.2
6.1.1.20
6.1.1.21
6.1.1.22
6.1.1.3
6.1.1.4
6.1.1.5
6.1.1.6
6.1.1.7
6.1.1.9
6.2.1.1
6.2.1.26
6.2.1.3
6.2.1.5
6.3.1.1
6.3.1.11
6.3.1.2
6.3.1.20
6.3.1.5
6.3.2.1
6.3.2.10
6.3.2.13
6.3.2.14
6.3.2.2
6.3.2.3
6.3.2.4
6.3.2.6
6.3.2.8
6.3.2.9
6.3.3.1
6.3.3.2
6.3.3.3
6.3.4.13
6.3.4.15
6.3.4.18
6.3.4.2
6.3.4.20
6.3.4.21
6.3.4.4
6.3.4.5
6.3.5.2
6.3.5.3
6.3.5.4
6.3.5.5
6.4.1.2
Conclusion

Alls organisms of E. coli K-12 share a high number of EC numbers.

FEV_KEGG.Experiments.14 module
Question

Which percentage of EC numbers is shared between all organisms of Escherichia coli K-12?

Method
  • Get all metabolic pathways of all E. coli organisms from KEGG.
  • For each organisms, combine all pathways to the metabolic network, by UNION operation.
  • Convert this metabolic network into a substance-ecNumber graph.
  • Combine all organisms’ networks to a single unified E. coli network, by UNION operation.
  • Combine all organisms’ networks to a consensus network, by INTERSECT operation, leaving only substances and EC numbers that occur in all organisms.
  • Print number of EC numbers in the unified network -> numberUnified.
  • Print number of EC numbers in the consensus network -> numberConsensus.
  • Print percentage numberConsensus/numberUnified.
Result 
unified: 617
consensus: 560
90.76175040518638%
Conclusion

About 91% of all EC numbers present in all known Escherichia coli K-12 organisms occur in all organisms. Thus, 9% of EC numbers only occur in some of the organisms. This indicates that organisms evolve by acquiring new enzymatic functionalities. Whether they stem from neofunctionalisation, horizontal gene transfer, or genesis remains to be investigated.

FEV_KEGG.Experiments.15 module
Question

Which EC numbers occur in either E. coli (eco) or S. solfataricus (sso) within the Serine, Glycine, Threonine pathway (00260)?

Method
  • Get 00260 pathways of eco and sso from KEGG.
  • Convert each pathway into a substance-ecNumber graph. This is the incomplete metabolic network.
  • Combine both species’ networks to a consensus network, by INTERSECTION operation.
  • Create the networks of EC numbers that only occur in 1) eco, and 2) sso.
  • Print those EC numbers.
Result 
EC numbers occuring only in eco:
18 results
1.1.1.-
1.1.1.103
1.1.1.215
1.1.1.3
1.1.1.381
1.1.1.79
1.1.1.81
1.1.99.1
1.2.1.8
2.3.1.29
2.6.1.52
2.7.2.4
2.7.8.8
3.1.3.3
4.1.2.48
4.3.1.17
4.3.1.18
5.4.2.11
EC numbers occuring only in sso:
1 results
1.5.3.1
Conclusion

The results are consistent with the pathway image to be found on KEGG.

FEV_KEGG.Experiments.16 module
Question

Which Genes cause the occurence of EC numbers in either E. coli (eco) or S. solfataricus (sso) within the Serine, Glycine, Threonine pathway (00260)?

Method
  • Get 00260 pathways of eco and sso from KEGG.
  • Convert each pathway into a substance-ecNumber graph. Using a substance-enzyme graph as intermediate. This is the incomplete metabolic network.
  • Combine both species’ networks to a consensus network, by INTERSECTION operation.
  • Create the networks of EC numbers that only occur in 1) eco, and 2) sso.
  • Print the genes associated with those EC numbers, using the intermediate substance-enzyme graph.
Result 
EC numbers occuring only in eco (associated genes):
18 results
1.1.1.- (eco:b1539)
1.1.1.103 (eco:b3616)
1.1.1.215 (eco:b3553)
1.1.1.3 (eco:b3940, eco:b0002)
1.1.1.381 (eco:b1539)
1.1.1.79 (eco:b1033, eco:b3553)
1.1.1.81 (eco:b1033, eco:b3553)
1.1.99.1 (eco:b0311)
1.2.1.8 (eco:b0312)
2.3.1.29 (eco:b3617)
2.6.1.52 (eco:b0907)
2.7.2.4 (eco:b3940, eco:b0002, eco:b4024)
2.7.8.8 (eco:b2585)
3.1.3.3 (eco:b4388)
4.1.2.48 (eco:b0870)
4.3.1.17 (eco:b2797, eco:b4471, eco:b1814)
4.3.1.18 (eco:b2366)
5.4.2.11 (eco:b0755)
EC numbers occuring only in sso (associated genes):
1 results
1.5.3.1 (sso:SSO0186, sso:SSO0187)
Conclusion

Many unique enzyme functions are realised by multiple genes. Therefore, multiple genes have to be considered in researching enzyme function evolution. It is therefore best to usually only work on EC graphs, because redundant enzymes are not considered in the context of this work.

FEV_KEGG.Experiments.17 module
Question

Assuming eco and sso had a common ancestor, and further assuming eco has evolved into a more versatile metabolism, while sso stayed closer to the common ancestor. Surrogate the common ancestor with sso. Which functions - defined by a new EC number - occuring in eco, but not in sso, may have originated from a gene duplication with a following neofunctionalisation? Using triangle method.

Method

Similar to 16: - Get all known pathways of eco and sso from KEGG. - Convert each pathway into a substance-ecNumber graph. Using a substance-enzyme graph as intermediate. This is the (a little incomplete) metabolic network. - Remove multifunctional enzymes, meaning enzymes associated with more than one EC number. Helps to reduce false gene duplications. - Combine both species’ networks to a consensus network, by INTERSECTION operation. - Create the networks of EC numbers that only occur in eco. New steps, triangle condition: - For each eco-only EC number, gather any eco gene which encodes an enzyme associated with this EC number. - For each such gene, find homologs within eco (paralogs, threshold=200). - If there exists at least one paralog with a different function, find homologs in sso (orthologs, threshold=200) for all paralogs.

  • If two paralogs share the same ortholog, there has probably been a gene duplication. The one ortholog and two paralogs can be visualised as a triangle, nodes being genes, edges being a connection of type ortholog/paralog.
  • If one of the paralogs shares the same EC number with their ortholog, but the other does not, there has probably been a gene duplication with neofunctionalisation.
  • Report all such probable gene duplications, in the following format: [orthologous genes, all of them are possible ancestors] => paralog with the same function as the ancestor (EC number of ancestor and paralog) + new gene (new function) This may report several genes as the source (ancestor) of the gene duplication, because when there are multiple matching orthologs it is unknown which of the orthologs was duplicated. May also report other neofunctionalised genes as paralogs, because a single group of paralogs can have multiple neofunctionalisations.
  • Report percentage gene duplication and neofunctionalisations of all new functions.
Result 
63 results
[sso:SSO0004]
  => eco:b3752 (2.7.1.15) + eco:b1723 (2.7.1.11)

[sso:SSO0090]
  => eco:b2890 (6.1.1.6) + eco:b0930 (6.1.1.22)

[sso:SSO0090]
  => eco:b4129 (6.1.1.6) + eco:b0930 (6.1.1.22)

[sso:SSO0093]
  => eco:b2400 (6.1.1.17) + eco:b0680 (6.1.1.18)

[sso:SSO0166]
  => eco:b0759 (5.1.3.2) + eco:b3619 (5.1.3.20)

[sso:SSO0173]
  => eco:b1866 (6.1.1.12) + eco:b0930 (6.1.1.22)

[sso:SSO0182]
  => eco:b0154 (5.4.3.8) + eco:b0774 (2.6.1.62)

[sso:SSO0182]
  => eco:b0154 (5.4.3.8) + eco:b1748 (2.6.1.81)

[sso:SSO0182]
  => eco:b0154 (5.4.3.8) + eco:b3073 (2.6.1.82)

[sso:SSO0299]
  => eco:b2465 (2.2.1.1) + eco:b0420 (2.2.1.7)

[sso:SSO0299]
  => eco:b2935 (2.2.1.1) + eco:b0420 (2.2.1.7)

[sso:SSO0306]
  => eco:b3281 (1.1.1.25) + eco:b1692 (1.1.1.282)

[sso:SSO0366, sso:SSO2554, sso:SSO2440]
  => eco:b3870 (6.3.1.2) + eco:b1297 (6.3.1.11)

[sso:SSO0369, sso:SSO3064]
  => eco:b1805 (6.2.1.3) + eco:b0586 (6.3.2.14)

[sso:SSO0369, sso:SSO3064]
  => eco:b1805 (6.2.1.3) + eco:b2260 (6.2.1.26)

[sso:SSO0579]
  => eco:b0077 (2.2.1.6) + eco:b0507 (4.1.1.47)

[sso:SSO0579]
  => eco:b0077 (2.2.1.6) + eco:b2373 (4.1.1.8)

[sso:SSO0579]
  => eco:b3671 (2.2.1.6) + eco:b0507 (4.1.1.47)

[sso:SSO0579]
  => eco:b3671 (2.2.1.6) + eco:b2264 (2.2.1.9)

[sso:SSO0579]
  => eco:b3671 (2.2.1.6) + eco:b2373 (4.1.1.8)

[sso:SSO0810]
  => eco:b2028 (1.1.1.22) + eco:b3787 (1.1.1.336)

[sso:SSO0893]
  => eco:b1264 (4.1.3.27) + eco:b0593 (5.4.4.2)

[sso:SSO0893]
  => eco:b1264 (4.1.3.27) + eco:b1812 (2.6.1.85)

[sso:SSO0893]
  => eco:b1264 (4.1.3.27) + eco:b2265 (5.4.4.2)

[sso:SSO0997]
  => eco:b2574 (1.4.3.16) + eco:b4154 (1.3.5.4)

[sso:SSO1077]
  => eco:b1611 (4.2.1.2) + eco:b4139 (4.3.1.1)

[sso:SSO1123, sso:SSO1565]
  => eco:b0116 (1.8.1.4) + eco:b3365 (1.7.1.15)

[sso:SSO1530, sso:SSO1529]
  => eco:b0115 (2.3.1.12) + eco:b0727 (2.3.1.61)

[sso:SSO1565, sso:SSO1123, sso:SSO1524, sso:SSO2559]
  => eco:b0116 (1.8.1.4) + eco:b3500 (1.8.1.7)

[sso:SSO1565, sso:SSO1123, sso:SSO1524, sso:SSO2559]
  => eco:b0116 (1.8.1.4) + eco:b3962 (1.6.1.1)

[sso:SSO1781, sso:SSO0830]
  => eco:b2041 (4.2.1.46) + eco:b2052 (1.1.1.271)

[sso:SSO1781, sso:SSO0830]
  => eco:b2041 (4.2.1.46) + eco:b2053 (4.2.1.47)

[sso:SSO1781, sso:SSO0830]
  => eco:b3788 (4.2.1.46) + eco:b2052 (1.1.1.271)

[sso:SSO1781, sso:SSO0830]
  => eco:b3788 (4.2.1.46) + eco:b2053 (4.2.1.47)

[sso:SSO2133, sso:SSO1600]
  => eco:b3926 (2.7.1.30) + eco:b2803 (2.7.1.51)

[sso:SSO2133, sso:SSO1600]
  => eco:b3926 (2.7.1.30) + eco:b3564 (2.7.1.17)

[sso:SSO2133, sso:SSO1600]
  => eco:b3926 (2.7.1.30) + eco:b3580 (2.7.1.53)

[sso:SSO2289, sso:SSO2276, sso:SSO3114, sso:SSO0975, sso:SSO2500]
  => eco:b1093 (1.1.1.100) + eco:b2842 (1.1.1.127)

[sso:SSO2289, sso:SSO2276, sso:SSO3114, sso:SSO0975]
  => eco:b1093 (1.1.1.100) + eco:b2705 (1.1.1.140)

[sso:SSO2289, sso:SSO2276, sso:SSO3114, sso:SSO2500]
  => eco:b1093 (1.1.1.100) + eco:b0596 (1.3.1.28)

[sso:SSO2368]
  => eco:b3939 (2.5.1.48) + eco:b3008 (4.4.1.8)

[sso:SSO2451]
  => eco:b2507 (6.3.5.2) + eco:b3360 (2.6.1.85)

[sso:SSO2536, sso:SSO1220, sso:SSO1646, sso:SSO2494, sso:SSO2878]
  => eco:b1478 (1.1.1.1) + eco:b1580 (1.1.1.380)

[sso:SSO2536, sso:SSO1220, sso:SSO1646, sso:SSO2494, sso:SSO2878]
  => eco:b1478 (1.1.1.1) + eco:b2091 (1.1.1.251)

[sso:SSO2536, sso:SSO1220, sso:SSO1646, sso:SSO2494, sso:SSO2878]
  => eco:b1478 (1.1.1.1) + eco:b3616 (1.1.1.103)

[sso:SSO2589]
  => eco:b0720 (2.3.3.1) + eco:b0333 (2.3.3.5)

[sso:SSO2665]
  => eco:b4478 (4.2.1.6) + eco:b1581 (4.2.1.8)

[sso:SSO2665]
  => eco:b4478 (4.2.1.6) + eco:b2247 (4.2.1.90)

[sso:SSO2863, sso:SSO2059, sso:SSO2041, sso:SSO1903, sso:SSO2216, sso:SSO1342, sso:SSO2070, sso:SSO1340]
  => eco:b4069 (6.2.1.1) + eco:b0335 (6.2.1.17)

[sso:SSO2863, sso:SSO2059, sso:SSO2041, sso:SSO1903, sso:SSO2216, sso:SSO2070]
  => eco:b4069 (6.2.1.1) + eco:b0586 (6.3.2.14)

[sso:SSO2869]
  => eco:b1479 (1.1.1.38) + eco:b2463 (1.1.1.40)

[sso:SSO2962, sso:SSO1012]
  => eco:b0871 (1.2.5.1) + eco:b0507 (4.1.1.47)

[sso:SSO2962, sso:SSO1012]
  => eco:b0871 (1.2.5.1) + eco:b2373 (4.1.1.8)

[sso:SSO3035, sso:SSO3072, sso:SSO2274]
  => eco:b0268 (4.3.3.7) + eco:b3225 (4.1.3.3)

[sso:SSO3035, sso:SSO3072, sso:SSO2274]
  => eco:b2478 (4.3.3.7) + eco:b3225 (4.1.3.3)

[sso:SSO3035, sso:SSO3072, sso:SSO2274]
  => eco:b4298 (4.3.3.7) + eco:b3225 (4.1.3.3)

[sso:SSO3036]
  => eco:b1617 (3.2.1.31) + eco:b0344 (3.2.1.23)

[sso:SSO3036]
  => eco:b1617 (3.2.1.31) + eco:b3076 (3.2.1.23)

[sso:SSO3064]
  => eco:b1805 (6.2.1.3) + eco:b0335 (6.2.1.17)

[sso:SSO3107]
  => eco:b3771 (4.2.1.9) + eco:b1851 (4.2.1.12)

[sso:SSO3211, sso:SSO2727]
  => eco:b1302 (2.6.1.19) + eco:b0774 (2.6.1.62)

[sso:SSO3211, sso:SSO2727]
  => eco:b1302 (2.6.1.19) + eco:b1748 (2.6.1.81)

[sso:SSO3211, sso:SSO2727]
  => eco:b1302 (2.6.1.19) + eco:b3073 (2.6.1.82)

42/413 -> 10.2 percent gene duplicated and neofunctionalised of all new functions.
Conclusion

Many gene duplication events can be identified using the triangle method. However, a) the triangle assumes that sso is the ancestor of eco, which it is not. Using groups of species could alleviate this problem: form consensus between Gammaproteobacteria, form consensus between all Proteobacteria, replace sso with Proteobacteria and eco with Gammaproteobacteria. This approach resembles a simple simulation of reconstructing a common ancestor, but without the need to reconstruct ancestral genes. b) searching for paralogs with differing function only, might suffice for finding gene duplications. Because if there is a paralog with a new function, there surely has been a gene duplication somewhere in the tree of life. Nevertheless, a change in function for the second paralog does not tell us that the gene duplication happened in the examined part of the tree of life, it merely states that a new function was developed within this part of the tree. But the interesting event here is the neofunctionalisation, not the gene duplication, which renders this method valid.

FEV_KEGG.Experiments.18 module
Question

Assuming eco and sso had a common ancestor, and further assuming eco has evolved into a more versatile metabolism. Which functions - defined by a new EC number - occuring in eco, but not in sso, may have originated from a neofunctionalisation?

Method

Similar to 17: - Get all known pathways of eco and sso from KEGG. - Convert each pathway into a substance-ecNumber graph. Using a substance-enzyme graph as intermediate. This is the (a little incomplete) metabolic network. - Remove multifunctional enzymes, meaning enzymes associated with more than one EC number. Helps to reduce false gene duplications. - Combine both species’ networks to a consensus network, by INTERSECTION operation. - Create the networks of EC numbers that only occur in eco. Similar to 17, without triangle condition: - For each eco-only EC number, gather any eco gene which encodes an enzyme associated with this EC number. - For each such gene, find homologs within eco (paralogs, threshold=200).

  • If there exists at least one paralog with a different function, report a neofunctionalisation, in the following format: paralog with different EC number (EC number) + neofunctionalised gene (new function) This may report different paralog groups per neofunctionalised gene, when the group of paralogs contains multiple functions. May also report other neofunctionalised genes as paralogs, because a single group of paralogs can have multiple neofunctionalisations.
  • Report percentage neofunctionalisations of all new functions.
Result 
323 results
eco:b0063 (2.7.1.16) + eco:b3564 (2.7.1.17)
eco:b0077 (2.2.1.6) + eco:b0507 (4.1.1.47)
eco:b0077 (2.2.1.6) + eco:b2373 (4.1.1.8)
eco:b0085 (6.3.2.13) + eco:b0086 (6.3.2.10)
eco:b0086 (6.3.2.10) + eco:b0085 (6.3.2.13)
eco:b0086 (6.3.2.10) + eco:b0088 (6.3.2.9)
eco:b0086 (6.3.2.10) + eco:b0091 (6.3.2.8)
eco:b0088 (6.3.2.9) + eco:b0086 (6.3.2.10)
eco:b0088 (6.3.2.9) + eco:b0091 (6.3.2.8)
eco:b0091 (6.3.2.8) + eco:b0086 (6.3.2.10)
eco:b0091 (6.3.2.8) + eco:b0088 (6.3.2.9)
eco:b0104 (1.7.1.7) + eco:b2508 (1.1.1.205)
eco:b0115 (2.3.1.12) + eco:b0727 (2.3.1.61)
eco:b0116 (1.8.1.4) + eco:b3365 (1.7.1.15)
eco:b0116 (1.8.1.4) + eco:b3500 (1.8.1.7)
eco:b0116 (1.8.1.4) + eco:b3962 (1.6.1.1)
eco:b0154 (5.4.3.8) + eco:b0774 (2.6.1.62)
eco:b0154 (5.4.3.8) + eco:b1748 (2.6.1.81)
eco:b0154 (5.4.3.8) + eco:b3073 (2.6.1.82)
eco:b0179 (2.3.1.191) + eco:b0181 (2.3.1.129)
eco:b0181 (2.3.1.129) + eco:b0179 (2.3.1.191)
eco:b0186 (4.1.1.18) + eco:b0693 (4.1.1.17)
eco:b0186 (4.1.1.18) + eco:b2965 (4.1.1.17)
eco:b0186 (4.1.1.18) + eco:b4117 (4.1.1.19)
eco:b0261 (2.1.1.10) + eco:b4019 (2.1.1.13)
eco:b0268 (4.3.3.7) + eco:b3225 (4.1.3.3)
eco:b0312 (1.2.1.8) + eco:b1300 (1.2.1.99)
eco:b0312 (1.2.1.8) + eco:b1385 (1.2.1.39)
eco:b0312 (1.2.1.8) + eco:b1444 (1.2.1.19)
eco:b0312 (1.2.1.8) + eco:b1746 (1.2.1.71)
eco:b0312 (1.2.1.8) + eco:b3588 (1.2.1.-)
eco:b0335 (6.2.1.17) + eco:b0586 (6.3.2.14)
eco:b0394 (2.7.1.4) + eco:b1119 (2.7.1.59)
eco:b0394 (2.7.1.4) + eco:b3222 (2.7.1.60)
eco:b0394 (2.7.1.4) + eco:b4084 (2.7.1.55)
eco:b0403 (3.2.1.20) + eco:b4239 (3.2.1.93)
eco:b0507 (4.1.1.47) + eco:b2373 (4.1.1.8)
eco:b0512 (3.5.2.5) + eco:b2873 (3.5.2.2)
eco:b0517 (1.1.1.350) + eco:b3575 (1.1.1.130)
eco:b0586 (6.3.2.14) + eco:b0335 (6.2.1.17)
eco:b0586 (6.3.2.14) + eco:b2260 (6.2.1.26)
eco:b0593 (5.4.4.2) + eco:b1812 (2.6.1.85)
eco:b0596 (1.3.1.28) + eco:b2842 (1.1.1.127)
eco:b0678 (3.5.99.6) + eco:b3141 (5.3.1.-)
eco:b0679 (2.7.1.193) + eco:b1101 (2.7.1.199)
eco:b0679 (2.7.1.193) + eco:b2417 (2.7.1.-)
eco:b0688 (5.4.2.2) + eco:b3176 (5.4.2.10)
eco:b0693 (4.1.1.17) + eco:b0186 (4.1.1.18)
eco:b0693 (4.1.1.17) + eco:b4117 (4.1.1.19)
eco:b0693 (4.1.1.17) + eco:b4131 (4.1.1.18)
eco:b0720 (2.3.3.1) + eco:b0333 (2.3.3.5)
eco:b0759 (5.1.3.2) + eco:b2053 (4.2.1.47)
eco:b0759 (5.1.3.2) + eco:b3619 (5.1.3.20)
eco:b0774 (2.6.1.62) + eco:b1748 (2.6.1.81)
eco:b0774 (2.6.1.62) + eco:b3073 (2.6.1.82)
eco:b0776 (2.3.1.47) + eco:b3617 (2.3.1.29)
eco:b0871 (1.2.5.1) + eco:b0507 (4.1.1.47)
eco:b0871 (1.2.5.1) + eco:b2373 (4.1.1.8)
eco:b0894 (1.8.5.3) + eco:b1587 (1.97.1.9)
eco:b0894 (1.8.5.3) + eco:b1588 (1.97.1.9)
eco:b0894 (1.8.5.3) + eco:b2206 (1.7.99.-)
eco:b0894 (1.8.5.3) + eco:b3551 (1.-.-.-)
eco:b0894 (1.8.5.3) + eco:b3894 (1.2.1.2)
eco:b0908 (2.5.1.19) + eco:b3189 (2.5.1.7)
eco:b0928 (2.6.1.1) + eco:b4054 (2.6.1.57)
eco:b0935 (1.14.14.5) + eco:b1012 (1.14.99.46)
eco:b1012 (1.14.99.46) + eco:b0935 (1.14.14.5)
eco:b1054 (2.3.1.241) + eco:b1855 (2.3.1.243)
eco:b1093 (1.1.1.100) + eco:b0596 (1.3.1.28)
eco:b1093 (1.1.1.100) + eco:b2705 (1.1.1.140)
eco:b1093 (1.1.1.100) + eco:b2842 (1.1.1.127)
eco:b1095 (2.3.1.179) + eco:b2323 (2.3.1.41)
eco:b1101 (2.7.1.199) + eco:b0679 (2.7.1.193)
eco:b1119 (2.7.1.59) + eco:b0394 (2.7.1.4)
eco:b1119 (2.7.1.59) + eco:b3222 (2.7.1.60)
eco:b1119 (2.7.1.59) + eco:b4084 (2.7.1.55)
eco:b1264 (4.1.3.27) + eco:b0593 (5.4.4.2)
eco:b1264 (4.1.3.27) + eco:b1812 (2.6.1.85)
eco:b1264 (4.1.3.27) + eco:b2265 (5.4.4.2)
eco:b1300 (1.2.1.99) + eco:b0312 (1.2.1.8)
eco:b1300 (1.2.1.99) + eco:b1385 (1.2.1.39)
eco:b1300 (1.2.1.99) + eco:b1444 (1.2.1.19)
eco:b1300 (1.2.1.99) + eco:b1746 (1.2.1.71)
eco:b1300 (1.2.1.99) + eco:b3588 (1.2.1.-)
eco:b1302 (2.6.1.19) + eco:b0774 (2.6.1.62)
eco:b1302 (2.6.1.19) + eco:b1748 (2.6.1.81)
eco:b1302 (2.6.1.19) + eco:b3073 (2.6.1.82)
eco:b1309 (2.4.1.7) + eco:b4239 (3.2.1.93)
eco:b1380 (1.1.1.28) + eco:b2320 (1.1.1.290)
eco:b1385 (1.2.1.39) + eco:b0312 (1.2.1.8)
eco:b1385 (1.2.1.39) + eco:b1300 (1.2.1.99)
eco:b1385 (1.2.1.39) + eco:b1444 (1.2.1.19)
eco:b1385 (1.2.1.39) + eco:b1746 (1.2.1.71)
eco:b1385 (1.2.1.39) + eco:b3588 (1.2.1.-)
eco:b1393 (4.2.1.17) + eco:b1394 (5.3.3.18)
eco:b1393 (4.2.1.17) + eco:b2262 (4.1.3.36)
eco:b1393 (4.2.1.17) + eco:b2919 (4.1.1.41)
eco:b1394 (5.3.3.18) + eco:b1393 (4.2.1.17)
eco:b1394 (5.3.3.18) + eco:b2262 (4.1.3.36)
eco:b1394 (5.3.3.18) + eco:b2919 (4.1.1.41)
eco:b1406 (1.1.1.65) + eco:b1771 (1.1.1.-)
eco:b1444 (1.2.1.19) + eco:b0312 (1.2.1.8)
eco:b1444 (1.2.1.19) + eco:b1300 (1.2.1.99)
eco:b1444 (1.2.1.19) + eco:b1385 (1.2.1.39)
eco:b1444 (1.2.1.19) + eco:b1746 (1.2.1.71)
eco:b1444 (1.2.1.19) + eco:b3588 (1.2.1.-)
eco:b1478 (1.1.1.1) + eco:b1580 (1.1.1.380)
eco:b1478 (1.1.1.1) + eco:b2091 (1.1.1.251)
eco:b1478 (1.1.1.1) + eco:b3616 (1.1.1.103)
eco:b1479 (1.1.1.38) + eco:b2463 (1.1.1.40)
eco:b1521 (1.1.1.58) + eco:b4323 (1.1.1.57)
eco:b1580 (1.1.1.380) + eco:b2091 (1.1.1.251)
eco:b1580 (1.1.1.380) + eco:b3616 (1.1.1.103)
eco:b1581 (4.2.1.8) + eco:b2247 (4.2.1.90)
eco:b1587 (1.97.1.9) + eco:b0894 (1.8.5.3)
eco:b1587 (1.97.1.9) + eco:b2206 (1.7.99.-)
eco:b1587 (1.97.1.9) + eco:b3551 (1.-.-.-)
eco:b1587 (1.97.1.9) + eco:b3894 (1.2.1.2)
eco:b1588 (1.97.1.9) + eco:b0894 (1.8.5.3)
eco:b1588 (1.97.1.9) + eco:b2206 (1.7.99.-)
eco:b1588 (1.97.1.9) + eco:b3551 (1.-.-.-)
eco:b1588 (1.97.1.9) + eco:b3894 (1.2.1.2)
eco:b1611 (4.2.1.2) + eco:b4139 (4.3.1.1)
eco:b1612 (4.2.1.2) + eco:b3061 (4.2.1.32)
eco:b1612 (4.2.1.2) + eco:b3062 (4.2.1.32)
eco:b1617 (3.2.1.31) + eco:b0344 (3.2.1.23)
eco:b1617 (3.2.1.31) + eco:b3076 (3.2.1.23)
eco:b1723 (2.7.1.11) + eco:b2168 (2.7.1.56)
eco:b1734 (3.2.1.86) + eco:b4119 (3.2.1.22)
eco:b1746 (1.2.1.71) + eco:b0312 (1.2.1.8)
eco:b1746 (1.2.1.71) + eco:b1300 (1.2.1.99)
eco:b1746 (1.2.1.71) + eco:b1385 (1.2.1.39)
eco:b1746 (1.2.1.71) + eco:b1444 (1.2.1.19)
eco:b1746 (1.2.1.71) + eco:b3588 (1.2.1.-)
eco:b1748 (2.6.1.81) + eco:b0774 (2.6.1.62)
eco:b1748 (2.6.1.81) + eco:b3073 (2.6.1.82)
eco:b1771 (1.1.1.-) + eco:b1406 (1.1.1.65)
eco:b1779 (1.2.1.12) + eco:b2927 (1.2.1.72)
eco:b1805 (6.2.1.3) + eco:b0335 (6.2.1.17)
eco:b1805 (6.2.1.3) + eco:b0586 (6.3.2.14)
eco:b1805 (6.2.1.3) + eco:b2260 (6.2.1.26)
eco:b1812 (2.6.1.85) + eco:b0593 (5.4.4.2)
eco:b1812 (2.6.1.85) + eco:b2265 (5.4.4.2)
eco:b1817 (2.7.1.191) + eco:b3133 (2.7.1.-)
eco:b1817 (2.7.1.191) + eco:b3138 (2.7.1.-)
eco:b1855 (2.3.1.243) + eco:b1054 (2.3.1.241)
eco:b2028 (1.1.1.22) + eco:b3787 (1.1.1.336)
eco:b2041 (4.2.1.46) + eco:b2052 (1.1.1.271)
eco:b2041 (4.2.1.46) + eco:b2053 (4.2.1.47)
eco:b2048 (5.4.2.8) + eco:b3176 (5.4.2.10)
eco:b2091 (1.1.1.251) + eco:b1580 (1.1.1.380)
eco:b2091 (1.1.1.251) + eco:b3616 (1.1.1.103)
eco:b2146 (1.3.1.1) + eco:b2878 (1.97.1.9)
eco:b2166 (2.7.1.83) + eco:b2168 (2.7.1.56)
eco:b2168 (2.7.1.56) + eco:b1723 (2.7.1.11)
eco:b2168 (2.7.1.56) + eco:b2166 (2.7.1.83)
eco:b2169 (2.7.1.202) + eco:b3599 (2.7.1.197)
eco:b2206 (1.7.99.-) + eco:b0894 (1.8.5.3)
eco:b2206 (1.7.99.-) + eco:b1587 (1.97.1.9)
eco:b2206 (1.7.99.-) + eco:b1588 (1.97.1.9)
eco:b2206 (1.7.99.-) + eco:b3551 (1.-.-.-)
eco:b2206 (1.7.99.-) + eco:b3894 (1.2.1.2)
eco:b2245 (4.1.2.53) + eco:b3126 (4.1.2.20)
eco:b2247 (4.2.1.90) + eco:b1581 (4.2.1.8)
eco:b2260 (6.2.1.26) + eco:b0586 (6.3.2.14)
eco:b2262 (4.1.3.36) + eco:b1393 (4.2.1.17)
eco:b2262 (4.1.3.36) + eco:b1394 (5.3.3.18)
eco:b2262 (4.1.3.36) + eco:b2919 (4.1.1.41)
eco:b2265 (5.4.4.2) + eco:b1812 (2.6.1.85)
eco:b2296 (2.7.2.1) + eco:b3115 (2.7.2.15)
eco:b2297 (2.3.1.8) + eco:b2463 (1.1.1.40)
eco:b2320 (1.1.1.290) + eco:b1380 (1.1.1.28)
eco:b2323 (2.3.1.41) + eco:b1095 (2.3.1.179)
eco:b2373 (4.1.1.8) + eco:b0507 (4.1.1.47)
eco:b2417 (2.7.1.-) + eco:b0679 (2.7.1.193)
eco:b2429 (2.7.1.192) + eco:b2715 (2.7.1.-)
eco:b2429 (2.7.1.192) + eco:b4240 (2.7.1.201)
eco:b2463 (1.1.1.40) + eco:b2297 (2.3.1.8)
eco:b2465 (2.2.1.1) + eco:b0420 (2.2.1.7)
eco:b2478 (4.3.3.7) + eco:b3225 (4.1.3.3)
eco:b2500 (2.1.2.2) + eco:b1232 (3.5.1.10)
eco:b2507 (6.3.5.2) + eco:b3360 (2.6.1.85)
eco:b2508 (1.1.1.205) + eco:b0104 (1.7.1.7)
eco:b2523 (3.4.11.23) + eco:b4260 (3.4.11.1)
eco:b2533 (3.1.3.25) + eco:b4214 (3.1.3.7)
eco:b2541 (1.3.1.87) + eco:b2842 (1.1.1.127)
eco:b2542 (1.18.1.3) + eco:b3365 (1.7.1.15)
eco:b2574 (1.4.3.16) + eco:b4154 (1.3.5.4)
eco:b2705 (1.1.1.140) + eco:b2842 (1.1.1.127)
eco:b2715 (2.7.1.-) + eco:b2429 (2.7.1.192)
eco:b2715 (2.7.1.-) + eco:b3599 (2.7.1.197)
eco:b2715 (2.7.1.-) + eco:b4240 (2.7.1.201)
eco:b2799 (1.1.1.77) + eco:b3011 (1.1.-.-)
eco:b2800 (4.1.2.17) + eco:b4198 (5.1.3.4)
eco:b2803 (2.7.1.51) + eco:b3564 (2.7.1.17)
eco:b2803 (2.7.1.51) + eco:b3580 (2.7.1.53)
eco:b2803 (2.7.1.51) + eco:b3904 (2.7.1.5)
eco:b2842 (1.1.1.127) + eco:b0596 (1.3.1.28)
eco:b2842 (1.1.1.127) + eco:b2541 (1.3.1.87)
eco:b2842 (1.1.1.127) + eco:b2705 (1.1.1.140)
eco:b2873 (3.5.2.2) + eco:b0512 (3.5.2.5)
eco:b2878 (1.97.1.9) + eco:b2146 (1.3.1.1)
eco:b2919 (4.1.1.41) + eco:b1393 (4.2.1.17)
eco:b2919 (4.1.1.41) + eco:b1394 (5.3.3.18)
eco:b2919 (4.1.1.41) + eco:b2262 (4.1.3.36)
eco:b2925 (4.1.2.13) + eco:b2096 (4.1.2.40)
eco:b2925 (4.1.2.13) + eco:b3137 (4.1.2.40)
eco:b2927 (1.2.1.72) + eco:b1779 (1.2.1.12)
eco:b2934 (2.7.1.197) + eco:b4195 (2.7.1.194)
eco:b2934 (2.7.1.197) + eco:b4302 (2.7.1.200)
eco:b2935 (2.2.1.1) + eco:b0420 (2.2.1.7)
eco:b2965 (4.1.1.17) + eco:b0186 (4.1.1.18)
eco:b2965 (4.1.1.17) + eco:b4117 (4.1.1.19)
eco:b2965 (4.1.1.17) + eco:b4131 (4.1.1.18)
eco:b3011 (1.1.-.-) + eco:b2799 (1.1.1.77)
eco:b3073 (2.6.1.82) + eco:b0774 (2.6.1.62)
eco:b3073 (2.6.1.82) + eco:b1748 (2.6.1.81)
eco:b3091 (4.2.1.7) + eco:b3128 (4.2.1.42)
eco:b3115 (2.7.2.15) + eco:b2296 (2.7.2.1)
eco:b3126 (4.1.2.20) + eco:b2245 (4.1.2.53)
eco:b3128 (4.2.1.42) + eco:b3091 (4.2.1.7)
eco:b3133 (2.7.1.-) + eco:b1817 (2.7.1.191)
eco:b3138 (2.7.1.-) + eco:b1817 (2.7.1.191)
eco:b3141 (5.3.1.-) + eco:b0678 (3.5.99.6)
eco:b3176 (5.4.2.10) + eco:b0688 (5.4.2.2)
eco:b3176 (5.4.2.10) + eco:b2048 (5.4.2.8)
eco:b3222 (2.7.1.60) + eco:b0394 (2.7.1.4)
eco:b3222 (2.7.1.60) + eco:b1119 (2.7.1.59)
eco:b3281 (1.1.1.25) + eco:b1692 (1.1.1.282)
eco:b3365 (1.7.1.15) + eco:b2542 (1.18.1.3)
eco:b3365 (1.7.1.15) + eco:b3500 (1.8.1.7)
eco:b3365 (1.7.1.15) + eco:b3962 (1.6.1.1)
eco:b3385 (3.1.3.18) + eco:b1317 (5.4.2.6)
eco:b3386 (5.1.3.1) + eco:b4085 (5.1.3.-)
eco:b3431 (3.2.1.196) + eco:b3432 (2.4.1.18)
eco:b3432 (2.4.1.18) + eco:b3431 (3.2.1.196)
eco:b3500 (1.8.1.7) + eco:b3365 (1.7.1.15)
eco:b3500 (1.8.1.7) + eco:b3962 (1.6.1.1)
eco:b3551 (1.-.-.-) + eco:b0894 (1.8.5.3)
eco:b3551 (1.-.-.-) + eco:b1587 (1.97.1.9)
eco:b3551 (1.-.-.-) + eco:b1588 (1.97.1.9)
eco:b3551 (1.-.-.-) + eco:b2206 (1.7.99.-)
eco:b3564 (2.7.1.17) + eco:b0063 (2.7.1.16)
eco:b3564 (2.7.1.17) + eco:b2803 (2.7.1.51)
eco:b3564 (2.7.1.17) + eco:b3580 (2.7.1.53)
eco:b3564 (2.7.1.17) + eco:b3904 (2.7.1.5)
eco:b3571 (3.2.1.1) + eco:b4239 (3.2.1.93)
eco:b3575 (1.1.1.130) + eco:b0517 (1.1.1.350)
eco:b3580 (2.7.1.53) + eco:b2803 (2.7.1.51)
eco:b3580 (2.7.1.53) + eco:b3564 (2.7.1.17)
eco:b3580 (2.7.1.53) + eco:b3904 (2.7.1.5)
eco:b3588 (1.2.1.-) + eco:b0312 (1.2.1.8)
eco:b3588 (1.2.1.-) + eco:b1300 (1.2.1.99)
eco:b3588 (1.2.1.-) + eco:b1385 (1.2.1.39)
eco:b3588 (1.2.1.-) + eco:b1444 (1.2.1.19)
eco:b3588 (1.2.1.-) + eco:b1746 (1.2.1.71)
eco:b3589 (1.1.1.1) + eco:b2799 (1.1.1.77)
eco:b3589 (1.1.1.1) + eco:b3011 (1.1.-.-)
eco:b3599 (2.7.1.197) + eco:b2169 (2.7.1.202)
eco:b3599 (2.7.1.197) + eco:b2715 (2.7.1.-)
eco:b3599 (2.7.1.197) + eco:b4195 (2.7.1.194)
eco:b3600 (1.1.1.17) + eco:b4323 (1.1.1.57)
eco:b3616 (1.1.1.103) + eco:b1580 (1.1.1.380)
eco:b3616 (1.1.1.103) + eco:b2091 (1.1.1.251)
eco:b3617 (2.3.1.29) + eco:b0776 (2.3.1.47)
eco:b3671 (2.2.1.6) + eco:b0507 (4.1.1.47)
eco:b3671 (2.2.1.6) + eco:b2264 (2.2.1.9)
eco:b3671 (2.2.1.6) + eco:b2373 (4.1.1.8)
eco:b3752 (2.7.1.15) + eco:b1723 (2.7.1.11)
eco:b3752 (2.7.1.15) + eco:b2166 (2.7.1.83)
eco:b3752 (2.7.1.15) + eco:b2168 (2.7.1.56)
eco:b3771 (4.2.1.9) + eco:b1851 (4.2.1.12)
eco:b3788 (4.2.1.46) + eco:b2052 (1.1.1.271)
eco:b3788 (4.2.1.46) + eco:b2053 (4.2.1.47)
eco:b3831 (2.4.2.3) + eco:b4384 (2.4.2.1)
eco:b3870 (6.3.1.2) + eco:b1297 (6.3.1.11)
eco:b3894 (1.2.1.2) + eco:b0894 (1.8.5.3)
eco:b3894 (1.2.1.2) + eco:b1587 (1.97.1.9)
eco:b3894 (1.2.1.2) + eco:b1588 (1.97.1.9)
eco:b3894 (1.2.1.2) + eco:b2206 (1.7.99.-)
eco:b3904 (2.7.1.5) + eco:b2803 (2.7.1.51)
eco:b3904 (2.7.1.5) + eco:b3564 (2.7.1.17)
eco:b3904 (2.7.1.5) + eco:b3580 (2.7.1.53)
eco:b3926 (2.7.1.30) + eco:b2803 (2.7.1.51)
eco:b3926 (2.7.1.30) + eco:b3564 (2.7.1.17)
eco:b3926 (2.7.1.30) + eco:b3580 (2.7.1.53)
eco:b3939 (2.5.1.48) + eco:b3008 (4.4.1.8)
eco:b3960 (4.3.2.1) + eco:b4139 (4.3.1.1)
eco:b3962 (1.6.1.1) + eco:b3365 (1.7.1.15)
eco:b3962 (1.6.1.1) + eco:b3500 (1.8.1.7)
eco:b4019 (2.1.1.13) + eco:b0261 (2.1.1.10)
eco:b4069 (6.2.1.1) + eco:b0335 (6.2.1.17)
eco:b4069 (6.2.1.1) + eco:b0586 (6.3.2.14)
eco:b4084 (2.7.1.55) + eco:b0394 (2.7.1.4)
eco:b4084 (2.7.1.55) + eco:b1119 (2.7.1.59)
eco:b4085 (5.1.3.-) + eco:b3386 (5.1.3.1)
eco:b4117 (4.1.1.19) + eco:b0186 (4.1.1.18)
eco:b4117 (4.1.1.19) + eco:b0693 (4.1.1.17)
eco:b4117 (4.1.1.19) + eco:b2965 (4.1.1.17)
eco:b4117 (4.1.1.19) + eco:b4131 (4.1.1.18)
eco:b4119 (3.2.1.22) + eco:b1734 (3.2.1.86)
eco:b4122 (4.2.1.2) + eco:b3061 (4.2.1.32)
eco:b4122 (4.2.1.2) + eco:b3062 (4.2.1.32)
eco:b4131 (4.1.1.18) + eco:b0693 (4.1.1.17)
eco:b4131 (4.1.1.18) + eco:b2965 (4.1.1.17)
eco:b4131 (4.1.1.18) + eco:b4117 (4.1.1.19)
eco:b4195 (2.7.1.194) + eco:b2934 (2.7.1.197)
eco:b4195 (2.7.1.194) + eco:b3599 (2.7.1.197)
eco:b4195 (2.7.1.194) + eco:b4302 (2.7.1.200)
eco:b4198 (5.1.3.4) + eco:b2800 (4.1.2.17)
eco:b4239 (3.2.1.93) + eco:b1309 (2.4.1.7)
eco:b4240 (2.7.1.201) + eco:b2429 (2.7.1.192)
eco:b4240 (2.7.1.201) + eco:b2715 (2.7.1.-)
eco:b4260 (3.4.11.1) + eco:b2523 (3.4.11.23)
eco:b4298 (4.3.3.7) + eco:b3225 (4.1.3.3)
eco:b4302 (2.7.1.200) + eco:b2934 (2.7.1.197)
eco:b4302 (2.7.1.200) + eco:b4195 (2.7.1.194)
eco:b4323 (1.1.1.57) + eco:b1521 (1.1.1.58)
eco:b4323 (1.1.1.57) + eco:b3600 (1.1.1.17)
eco:b4384 (2.4.2.1) + eco:b3831 (2.4.2.3)
eco:b4395 (5.4.2.12) + eco:b0638 (3.1.3.73)
eco:b4478 (4.2.1.6) + eco:b1581 (4.2.1.8)
eco:b4478 (4.2.1.6) + eco:b2247 (4.2.1.90)

148/413 -> 35.8 percent neofunctionalisation of all new functions.
Conclusion

Many more neofunctionalisations are reported when no gene duplication ‘triangle’ has to be proven: 35% instead of 10% of all new EC numbers. In reverse, this means that for about 20% of new functions, which do have paralogs, no ortholog in sso could be found. This might be due to: a) gene duplications that happened before the common ancestor parted into sso and eco, and have since been lost/mutated in sso. Keep in mind that, in this experiment, the common ancestor ist surrogated by sso, which is a questionable assumption. b) gene duplications that happened after the common ancestor parted into sso and eco, and only happened in eco. This seems to be the better explanation, because there have presumably been many evolutionary events between the last common ancestor and eco. Therefore, this method is not suitable for comparison of two individual species, because the ‘older one’ has to surrogate the common ancestor, because reconstructing a common ancestor’s genes is a non-trivial task. Shifting the scope from individual species, surrogating one for the common ancestor, to a group of species, comparing it to a super-group, might solve the problem.

FEV_KEGG.Experiments.19 module
Question

Taking an incomplete set of example organisms, forming a group (Enterobacteriales) and a super group (Gammaproteobacteria) of organisms, which functions occur in the consensus network of the group, but not in the consensus network of the super group?

Method
  • Create a group of example organisms of Order Enterobacteriales.
  • Create a group of example organisms of Class Gammaproteobacteria, including the same organsims as the group of Enterobacteriales.
  • Calculate consensus substance-ec graphs for both groups. Leaving only EC numbers which occur in all organisms of the group.
  • Calculate the difference of the two sets of consensus EC numbers, leaving only the EC numbers which occur in Enterobacteriales consensus, but not in Gammaproteobacteria consensus.
  • Print these EC numbers and their percentage of all EC numbers in Enterobacteriales, ie. how many of the EC numbers in Enterobacteriales do not exist in Gammaproteobacteria consensus.
Result 
108 results
1.1.1.100
1.1.1.17
1.1.1.193
1.1.1.23
1.1.1.267
1.1.1.3
1.1.1.343
1.1.1.363
1.1.1.44
1.1.1.49
1.1.1.85
1.1.1.86
1.17.1.8
1.17.7.1
1.17.7.3
1.17.7.4
1.2.1.38
1.3.1.76
1.5.1.20
1.7.1.7
1.8.1.2
2.1.1.107
2.1.1.14
2.1.2.11
2.1.2.3
2.1.3.2
2.1.3.3
2.2.1.2
2.2.1.6
2.2.1.7
2.3.1.1
2.3.1.117
2.3.1.157
2.3.1.30
2.3.1.41
2.3.1.8
2.3.3.13
2.4.2.-
2.4.2.1
2.4.2.17
2.4.2.18
2.4.2.22
2.4.2.8
2.5.1.16
2.5.1.19
2.5.1.47
2.5.1.61
2.6.1.9
2.7.1.-
2.7.1.11
2.7.1.148
2.7.1.197
2.7.1.199
2.7.1.25
2.7.1.26
2.7.1.39
2.7.1.40
2.7.2.1
2.7.2.4
2.7.2.8
2.7.4.16
2.7.6.1
2.7.7.18
2.7.7.2
2.7.7.23
2.7.7.4
2.7.7.60
2.7.7.8
2.7.8.7
2.8.1.7
3.1.1.31
3.1.2.-
3.1.3.15
3.1.3.7
3.2.2.9
3.5.1.16
3.5.1.18
3.5.2.3
3.5.4.10
3.5.4.13
3.5.4.19
3.5.4.26
3.6.1.23
3.6.1.27
3.6.1.31
4.1.1.50
4.1.3.-
4.2.1.19
4.2.1.33
4.2.1.35
4.2.1.9
4.3.2.1
4.3.3.7
4.6.1.12
4.99.1.4
5.1.1.3
5.1.1.7
5.3.1.16
5.3.1.28
5.4.2.11
5.4.2.7
5.4.99.5
6.1.1.17
6.3.2.1
6.3.2.3
6.3.4.21
6.3.4.5
6.3.5.5
108/190 -> 56.8% of EC numbers in Enterobacteriales are new, compared to Gammaproteobacteria consensus
Conclusion

57% is a very high percentage. Maybe the example set of Gammaproteobacteria contained an organism with limited metabolic capabilities, eg. a parasite. Next step is to limit ‘consensus’ to x percent of all organisms, ie. 1-x percent of organisms in a group may not contain an EC number, and it would still be added to the ‘consensus’, or rather majority.

FEV_KEGG.Experiments.19.enterobacterialesEcGraph()[source]
FEV_KEGG.Experiments.19.gammaproteobacteriaEcGraph()[source]
FEV_KEGG.Experiments.20 module
Question

Same as 19, only majority instead of consensus. Taking an incomplete set of example organisms, forming a group (Enterobacteriales, Order) and a super group (Gammaproteobacteria, Class) of organisms, which functions occur in the majority network of the group, but not in the majority network of the super group?

Method

Same as 19, only majority instead of consensus. - Create a group of example organisms of Order Enterobacteriales. - Create a group of example organisms of Class Gammaproteobacteria, including the same organsims as the group of Enterobacteriales. - Calculate majority substance-ec graphs for both groups. Leaving only EC numbers which occur in all organisms of the group. - Calculate the difference of the two sets of majority EC numbers, leaving only the EC numbers which occur in Enterobacteriales majority, but not in Gammaproteobacteria majority. - Print these EC numbers and their percentage of all EC numbers in Enterobacteriales, ie. how many of the EC numbers in Enterobacteriales do not exist in Gammaproteobacteria majority.

Result 
222 results @ 80%
1.1.-.-
1.1.1.-
1.1.1.103
1.1.1.127
1.1.1.169
1.1.1.17
1.1.1.215
1.1.1.22
1.1.1.262
1.1.1.28
1.1.1.284
1.1.1.290
1.1.1.336
1.1.1.343
1.1.1.381
1.1.1.44
1.1.1.57
1.1.1.79
1.1.1.81
1.1.2.3
1.1.5.12
1.1.98.6
1.11.1.21
1.11.1.9
1.14.11.17
1.14.14.5
1.16.1.3
1.2.1.-
1.2.1.10
1.2.1.19
1.2.1.71
1.2.1.72
1.2.5.1
1.2.7.-
1.2.7.1
1.3.1.-
1.3.1.10
1.3.1.28
1.3.5.3
1.3.98.3
1.4.1.13
1.4.1.14
1.4.1.4
1.4.3.16
1.4.4.2
1.4.5.1
1.5.1.38
1.5.1.41
1.6.1.1
1.6.5.2
1.7.1.15
1.7.1.7
1.7.5.1
1.7.99.-
1.7.99.1
1.8.4.10
1.8.4.14
1.8.4.8
2.1.1.37
2.1.2.10
2.2.1.9
2.3.1.109
2.3.1.183
2.3.1.243
2.3.1.29
2.3.1.40
2.3.1.46
2.3.1.54
2.3.1.57
2.3.3.9
2.4.1.1
2.4.1.18
2.4.2.1
2.4.2.22
2.4.2.3
2.4.2.4
2.5.1.-
2.5.1.129
2.5.1.16
2.5.1.17
2.5.1.48
2.5.1.74
2.6.1.19
2.6.1.57
2.6.1.81
2.7.1.-
2.7.1.11
2.7.1.12
2.7.1.15
2.7.1.16
2.7.1.167
2.7.1.17
2.7.1.191
2.7.1.193
2.7.1.194
2.7.1.196
2.7.1.197
2.7.1.199
2.7.1.2
2.7.1.201
2.7.1.202
2.7.1.205
2.7.1.208
2.7.1.22
2.7.1.25
2.7.1.35
2.7.1.45
2.7.1.5
2.7.1.50
2.7.1.56
2.7.1.59
2.7.1.6
2.7.1.73
2.7.1.89
2.7.7.1
2.7.7.12
2.7.7.13
2.7.7.24
2.7.7.27
2.7.7.58
2.7.7.70
2.7.7.73
2.7.7.75
2.7.8.-
2.7.8.37
2.7.8.7
2.7.9.3
2.8.1.2
2.8.1.4
2.9.1.1
3.1.1.11
3.1.1.32
3.1.1.4
3.1.1.45
3.1.1.5
3.1.2.12
3.1.2.28
3.1.3.10
3.1.3.102
3.1.3.104
3.1.3.2
3.1.3.4
3.1.3.6
3.1.3.81
3.1.3.82
3.1.3.83
3.1.3.89
3.1.4.14
3.1.4.16
3.2.1.1
3.2.1.196
3.2.1.20
3.2.1.21
3.2.1.22
3.2.1.23
3.2.1.86
3.2.1.93
3.2.2.4
3.3.2.1
3.4.11.23
3.4.13.-
3.5.1.-
3.5.1.16
3.5.1.19
3.5.1.96
3.5.3.11
3.5.3.23
3.5.4.4
3.5.99.6
3.6.1.26
3.6.1.45
3.6.1.67
3.6.1.7
3.6.1.9
4.1.1.11
4.1.1.17
4.1.1.18
4.1.1.50
4.1.2.4
4.1.2.40
4.1.2.48
4.1.2.50
4.1.3.1
4.1.3.36
4.1.99.17
4.1.99.19
4.2.1.113
4.2.1.126
4.2.1.7
4.2.1.8
4.2.3.12
4.2.3.3
4.2.99.20
4.3.1.1
4.4.1.15
4.4.1.16
4.4.1.21
4.6.1.17
5.1.3.14
5.1.3.20
5.1.3.3
5.1.3.4
5.1.3.9
5.3.1.12
5.3.1.14
5.3.1.4
5.3.1.5
5.3.1.8
5.3.3.2
5.3.3.8
5.4.2.11
5.4.2.12
5.4.2.7
5.4.4.2
6.2.1.1
6.2.1.20
6.2.1.26
6.3.1.1
6.3.1.20
6.3.1.5
6.3.2.14
6.3.4.21
222/585 -> 37.9% of EC numbers in Enterobacteriales are new, compared to Gammaproteobacteria majority
Conclusion

Old results, with 100% majority, from 19: 108/190 -> 56.8% At 80% majority, many more EC numbers exist within both, group and super group. Now, 585 instead of 190 in Enterobacteriales. From this bigger set, however, only 38% are now considered ‘new’, in comparison to Gammaproteobacteria.

Both sets seem to be very diverse, but this could be a misinterpretation due to, a) poor choice of example organisms, however, this problem should have already been mitigated by introducing a majority graph. b) not enough organisms per group to really form a characteristic ‘core metabolism’.

On the other hand, it might be that with growing set sizes, there will be no difference left, meaning there is no characteristic difference in ‘core metabolisms’ between Order and Class of bacteria. This might be because, a) differences are only visible between groups farther apart in taxonomy, eg. Order and Phylum, or even Domain. At least LUCA should definitely show differences. b) there are, in general, no significant differences in ‘core metabolisms’ in prokaryotes, maybe due to horizontal gene transfer.

But the general expectation is to find a common ‘core metabolism’, which might be rather small, and should usually contain, for example, amino acid synthesis. Expected exceptions are symbionts.

FEV_KEGG.Experiments.20.enterobacterialesEcGraph()[source]
FEV_KEGG.Experiments.20.gammaproteobacteriaEcGraph()[source]
FEV_KEGG.Experiments.21 module
Context

Similar to 20, where results seemingly showed very diverse metabolism. Possible reasons might have been a poor choice of example organisms or not enough organisms per group. These reasons can be mitigated by this experiment, up to the amount of real-world organisms available in KEGG. A small common ‘core metabolism’ is expected to be found, except for symbionts.

Question

Taking a complete set of organisms, forming a group (Brachyspirales, Order) and a super group (Spirochaetes, Class) of organisms, how many functions occur in the majority network of the group, but not in the majority network of the super group? For varying majority-percentages.

Method

Similar to 20, only different sets, complete sets, and ‘how many?’ instead of ‘which?’ functions. - Create a group of all organisms of Order Brachyspirales to be found in KEGG. - Create a super group of all organisms of Class Spirochaetes to be found in KEGG, including the same organsims as the group of Order. - REPEAT for varying majority-percentages: - Calculate majority substance-ec graphs for both groups. Leaving only EC numbers which occur in all organisms of the group. - Calculate the difference of the two sets of majority EC numbers, leaving only the EC numbers which occur in Order majority, but not in Class majority. - Print the amount of EC numbers and their percentage of all EC numbers in Order, ie. how many of the EC numbers in Order do not exist in Class majority.

Result 
269/295 -> 91.2% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 100% majority for both
249/295 -> 84.4% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 90% majority for both
268/328 -> 81.7% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 80% majority for both
272/342 -> 79.5% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 70% majority for both
271/354 -> 76.6% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 60% majority for both
269/380 -> 70.8% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 50% majority for both
200/380 -> 52.6% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 40% majority for both
146/389 -> 37.5% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 30% majority for both
 78/395 -> 19.7% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 20% majority for both
 36/425 ->  8.5% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 10% majority for both
Conclusion

This group (Brachyspirales) is even more diverse than Enterobacteriales in 20. It is, therefore, unlikely that a poor selection of example organisms caused the results in 20. It might still be the case that KEGG only contains poor representatives of the real group, which can never be ruled out.

Even though the threshold of majority decreases the same for group and super group, the size of the majority network is rather constant for Brachyspirales. The size of the majority network for Spirochaetes, however, seems to increase quicker, yet linearly, with decreasing majority threshold. This indicates an even greater diversity in the super group Spirochaetes.

FEV_KEGG.Experiments.22 module
Context

19 found many EC numbers new to an example group of Enterobacteriales vs. the super group of Gammaproteobacteria. “108/190 -> 56.8% of EC numbers in Enterobacteriales are new, compared to Gammaproteobacteria consensus”

Question

Could this be due to incomplete data in KEGG? Because substance-ec graphs are intersected to form the consensus. Does the same result occur when intersecting the set of EC numbers itself?

Method

Similar to 19, only intersect sets instead of networks. - Create a group of example organisms of Order Enterobacteriales. - Create a group of example organisms of Class Gammaproteobacteria, including the same organsims as the group of Enterobacteriales. - Get sets of EC numbers from each graph. - Calculate consensus set for both groups (Order and Class). Leaving only EC numbers which occur in all organisms of the group. - Calculate the difference of the two sets of consensus EC numbers, leaving only the EC numbers which occur in Enterobacteriales consensus, but not in Gammaproteobacteria consensus. - Print these EC numbers and their percentage of all EC numbers in Enterobacteriales, ie. how many of the EC numbers in Enterobacteriales do not exist in Gammaproteobacteria consensus.

Result 
107/190 -> 56.3% of EC numbers in Enterobacteriales are new, compared to Gammaproteobacteria consensus
Conclusion

Only one EC number (0.5%) was lost due to the way the consensus is calculated. This kind of error in KEGG data should not be able to cause much difference in results.

FEV_KEGG.Experiments.22.enterobacterialesEcSets()[source]
FEV_KEGG.Experiments.22.gammaproteobacteriaEcSets()[source]
FEV_KEGG.Experiments.23 module
Context

Similar to 21, where both group and super group were calculated with the same majority threshold. The super group seemed even more diverse than the group. Maybe the diversity can be leveled out when using different majority thresholds for group and super group.

Question

Taking a complete set of organisms, forming a group (Brachyspirales, Order) and a super group (Spirochaetes, Class) of organisms, how many functions occur in the majority network of the group, but not in the majority network of the super group? For a fixed and high majority threshold for the smaller group, but varying majority thresholds for the bigger super group.

Method

Similar to 21, only fixed majority threshold for group. - Create a group of all organisms of Order Brachyspirales to be found in KEGG. - Create a super group of all organisms of Class Spirochaetes to be found in KEGG, including the same organsims as the group of Order. - Calculate majority substance-ec graph for group. Leaving only EC numbers which occur in all organisms of the group. - REPEAT for varying majority-percentages: - Calculate majority substance-ec graph for super group. Leaving only EC numbers which occur in all organisms of the super group. - Calculate the difference of the two sets of majority EC numbers, leaving only the EC numbers which occur in Order majority, but not in Class majority. - Print the amount of EC numbers and their percentage of all EC numbers in Order, ie. how many of the EC numbers in Order do not exist in Class majority.

Result 
302/328 -> 92.1% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 100% majority for super group and 80% majority for group
280/328 -> 85.4% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 90% majority for super group and 80% majority for group
268/328 -> 81.7% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 80% majority for super group and 80% majority for group
258/328 -> 78.7% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 70% majority for super group and 80% majority for group
245/328 -> 74.7% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 60% majority for super group and 80% majority for group
220/328 -> 67.1% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 50% majority for super group and 80% majority for group
153/328 -> 46.6% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 40% majority for super group and 80% majority for group
108/328 -> 32.9% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 30% majority for super group and 80% majority for group
 43/328 -> 13.1% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 20% majority for super group and 80% majority for group
  1/328 ->  0.3% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 10% majority for super group and 80% majority for group
Conclusion

Percentages above 80%/80% grow a litte bit larger, below a bit smaller. Generally not much change, except for the 10% area. This low area is probably heavily influneced by the fact that the Brachyspirales group is also included in the super group. Maybe the group should be excluded from the super group to get less extreme results. The question answered would then be ‘EC numbers new to group, compared to ALL OTHER groups in super group’. But it could just boost the lower threshold areas.

FEV_KEGG.Experiments.23.groupEcGraph(taxonomy)[source]
FEV_KEGG.Experiments.23.supergroupEcGraph(taxonomy)[source]
FEV_KEGG.Experiments.24 module
Context

Similar to 23, where group and super group were calculated with a fixed and a variable majority threshold. Maybe the group should be excluded from the super group to get less extreme results. The question answered would then be ‘EC numbers new to group, compared to ALL OTHER groups in super group’.

Question

Taking a complete set of organisms, forming a group (Brachyspirales, Order) and a super group (Spirochaetes, Class) of organisms, how many functions occur in the majority network of the group, but not in the majority network of the super group, excluding the organisms of the group? For a fixed and high majority threshold for the smaller group, but varying majority thresholds for the bigger super group.

Method

Similar to 21, only fixed majority threshold for group. - Create a group of all organisms of Order Brachyspirales to be found in KEGG. - Create a super group of all organisms of Class Spirochaetes to be found in KEGG, including the same organsims as the group of Order. - Exclude organisms of group from super group. - Calculate majority substance-ec graph for group. Leaving only EC numbers which occur in all organisms of the group. - REPEAT for varying majority-percentages: - Calculate majority substance-ec graph for super group. Leaving only EC numbers which occur in all organisms of the super group. - Calculate the difference of the two sets of majority EC numbers, leaving only the EC numbers which occur in Order majority, but not in Class majority. - Print the amount of EC numbers and their percentage of all EC numbers in Order, ie. how many of the EC numbers in Order do not exist in Class majority.

Result 
300/328 -> 91.5% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 100% majority for super group and 80% majority for group
281/328 -> 85.7% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 90% majority for super group and 80% majority for group
271/328 -> 82.6% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 80% majority for super group and 80% majority for group
264/328 -> 80.5% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 70% majority for super group and 80% majority for group
254/328 -> 77.4% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 60% majority for super group and 80% majority for group
224/328 -> 68.3% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 50% majority for super group and 80% majority for group
203/328 -> 61.9% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 40% majority for super group and 80% majority for group
142/328 -> 43.3% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 30% majority for super group and 80% majority for group
 85/328 -> 25.9% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 20% majority for super group and 80% majority for group
 35/328 -> 10.7% of EC numbers in Brachyspirales are new, compared to Spirochaetes majority @ 10% majority for super group and 80% majority for group
Conclusion

Leaving out the group and comparing to the rest of the super group merely boosts the percentages for the lower thresholds. For higher thresholds, the group’s redundancy does not have a noticeable effect. If the group were bigger, though, the effect may well be noticeable and skew the higher thresholds, too. It should always be assured, that the super group is sufficiently larger than the group.

FEV_KEGG.Experiments.25 module
Context

Similar to 21, only with a different Class and Order, to see if the distribution of new enzymes by majority threshold is comparable between very different Classes.

Question

Taking a complete set of organisms, forming a group (Desulfobacterales, Order) and a super group (Deltaproteobacteria, Class) of organisms, how many functions occur in the majority network of the group, but not in the majority network of the super group? For varying majority-percentages.

Method

Same as 21, only different Class and Order. - Create a group of all organisms of Order to be found in KEGG. - Create a super group of all organisms of Class to be found in KEGG, including the same organsims as the group of Order. - REPEAT for varying majority-percentages: - Calculate majority substance-ec graphs for both groups. Leaving only EC numbers which occur in all organisms of the group. - Calculate the difference of the two sets of majority EC numbers, leaving only the EC numbers which occur in Order majority, but not in Class majority. - Print the amount of EC numbers and their percentage of all EC numbers in Order, ie. how many of the EC numbers in Order do not exist in Class majority.

Result 
224/238 -> 94.1% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 100% majority for both
 63/238 -> 26.5% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 90% majority for both
 65/299 -> 21.7% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 80% majority for both
 49/333 -> 14.7% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 70% majority for both
 37/373 ->  9.9% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 60% majority for both
 56/418 -> 13.4% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 50% majority for both
 45/470 ->  9.6% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 40% majority for both
 49/526 ->  9.3% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 30% majority for both
 59/602 ->  9.8% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 20% majority for both
 93/736 -> 12.6% of EC numbers in Desulfobacterales are new, compared to Deltaproteobacteria majority @ 10% majority for both
Conclusion

In contrast to Spirochaetes/Brachyspirales from 21, ther percentage of new EC numbers quickly drops. Since both groups are calculated with the same decreasing majority threshold, the percentage of new EC numbers even oscillates. Deltaproteobacteria/Desulfobacterales seem much less diverse than Spirochaetes/Brachyspirales.

FEV_KEGG.Experiments.25.groupEcGraph(taxonomy)[source]
FEV_KEGG.Experiments.25.supergroupEcGraph(taxonomy)[source]
FEV_KEGG.Experiments.26 module
Question

How many core metabolism enzymes may have arisen due to gene duplication in Desulfobacterales, compared to Deltaproteobacteria? How many of those performed neofunctionalisation? How many new functions (EC numbers) arose in Desulfobacterales due to neofunctionalisation?

Method
  • get NCBI taxonomy tree
  • get group of organisms ‘Proteobacteria/Deltaproteobacteria/Desulfobacterales’
  • get supergroup of organisms ‘Proteobacteria/Deltaproteobacteria’
  • calculate number of enzymes in the group, including multifunctional enzymes
  • calculate number of enzymes in the group, excluding multifunctional enzymes
  • calculate number of enzymes in group’s core metabolism
  • calculate number of possible gene duplicates in the group
  • calculate number of possible neofunctionalisations in the group
  • calculate number of new EC numbers in the group
  • calculate neofunctionalised EC numbers in the group
Result 
enzymes in group: 5245
of which excluding multifunctional: 4661
of which core metabolism: 2340
of which gene duplicates: 770
of which neofunctionalisations: 143
EC numbers new in group: 166
EC numbers due to neofunctionalisation: 23
Conclusion

As we have seen before, the core metabolism of Desulfobacterales seems rather large. When applying a majority approach, instead of a consensus, this number is only going to rise. Gene duplications, according to the simple model, are abundant. Many, but by far not all, gene duplications have also lead to new functions. This can be well explained by patchwork evolution theory. Only 9 new functions arose in Desulfobacterales core metabolism which can be explained by neofunctionalisation. Compared to 161 new functions which arose in total. There may be several reasons for this: 1) gene duplication had been too obfuscated to be detected any longer, depends on E-value 2) horizontal gene transfer plays a dominating role in propagating new functions 3) majority core metabolism would yield much different results

FEV_KEGG.Experiments.27 module
Context

Some organisms belong to an ‘unclassified’ taxon. They are hard to compare against other taxa.

Question

How does excluding ‘unclassified’ Archaea change the number of EC numbers new to Thaumarchaeota? How does it change the number of neofunctionalised EC numbers?

Method
  • get NCBI taxonomy tree
  • get group of organisms ‘Archaea/Thaumarchaeota’
  • get supergroup of organisms ‘Archaea’
  • calculate new EC numbers occuring in group’s core metabolism compared to supergroup’s core metabolism
  • calculate neofunctionalised EC numbers in group’s core metabolism
  • repeat all, but excluding taxa containing ‘unclassified’ in both group and supergroup
  • repeat all, but excluding taxa containing ‘Nitrososphaeria’ in both group and supergroup
Result 
taxon exception: None
new EC numbers: 110
neofunctionalised EC numbers: 11

taxon exception: unclassified
new EC numbers: 172
neofunctionalised EC numbers: 16

taxon exception: Nitrososphaeria
new EC numbers: 114
neofunctionalised EC numbers: 9
Conclusion

Excluding ‘unclassfied’ organisms has a significant impact on core metabolism. This might be due to 1) reduced number of organisms, leading to higher chances of a consensus in metabolism 2) the unclassified organisms here have an unusual metabolism

Excluding a sub-group of the same size (4 organisms), however, does not yield significant changes. This implies a strong preference for option 2) above.

FEV_KEGG.Experiments.28 module
Context

The approach of building a consensus/majority graph of enzymes/EC numbers to find a core metabolism shared among several organisms has to be validated against previous research. One such previous research deals with E. coli, but uses a different approach, asking not what the core metabolism ‘can do’, but what it ‘always does’. Almaas et al. (2005) list core reactions calculated via flux analysis in table S1 (https://doi.org/10.1371/journal.pcbi.0010068.st001), some of which have annotated EC numbers. These EC numbers are used to validate the approach of this library. Multifunctional enzymes and EC numbers containing wildcards (e.g. 1.2.-.-) are excluded on both sides, to minimise statistical skew. This leaves 62 EC numbers in Almaas’ approach.

Question

Does the consensus/majority graph approach to core metabolism yield a similar set of EC numbers as the approach of Almaas et al. (2005)?

Method
  • extract EC numbers from Almaas et al. (2005) by hand
  • get group of organisms ‘Escherichia coli’
  • REPEAT for varying majority-percentages:
  • calculate EC numbers occuring in group’s core metabolism
  • overlap Almaas’ set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Maj. %   others    both    ours
100%:    28        34      381
 90%:    19        43      491
 80%:    19        43      499
 70%:    19        43      510
 60%:    19        43      518
 50%:    19        43      522
 40%:    19        43      531
 30%:    19        43      542
 20%:    19        43      550
 10%:    19        43      564
  1%:    19        43      602
Conclusion

With a 90% majority and below, the number of overlapping ECs does not increase any more. This indicates that, at least for E. coli, a 90% majority is enough to create a stable core metabolism, diminishing the skew excerted by unusually specialised organisms. In the case of E. coli these could be soil-based E. coli strains, which remains to be researched.

About 69% of the ECs in the reaction-based core metabolism, as postulated by Almaas et al., are also included in the majority-based core metabolism of our approach. Due to some ECs missing in Almaas’ table S1, this percentage could have been even bigger. This substantial overlap shows most essential reactions are also covered by a majority approach. However, this goes along with two interesting observations:

  1. 31% of essential reactions are not included in any majority, not even in a single organism from KEGG at 1% majority (effectively n=1).
    This could be because of a flaw in either approach, or because the data Almaas et al. use stems from the year 2000 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC25862/) and it might be that then Escherichia coli MG1655 was said to include different ECs than in today’s KEGG database. This has to be investigated.
  2. Only 8% of majority ECs (at 90%) are essential reactions. This indicates that while E. coli organisms share many ECs, most of them are only active at
    certain times.
FEV_KEGG.Experiments.29 module
Context

See experiment 28 conclusion.

Question

Do the missing 19 ECs even exist in today’s Escherichia coli MG1655 (eco)?

Method
  • extract EC numbers from Almaas et al. (2005) by hand
  • get organism ‘Escherichia coli MG1655’ (eco) from current KEGG
  • calculate EC numbers occuring in eco’s core metabolism
  • overlap Almaas’ set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
others    both    ours
19        43      530
Conclusion

As in experiment 28, there are still 19 ECs from ‘essential reactions’ missing from today’s Escherichia coli MG1655, even though they were obviously present in the year 2000. The 19 ECs not contained in our approach of a core metabolism are, therefore, to be attributed to a different set of base data, and thus not necessarily to a flaw in either approach.

All in all, there is no contradiction between both approaches towards a core metabolism. To some extend, the findings could be interpreted as a partial validation of our approach.

FEV_KEGG.Experiments.30 module
Context

The approach of building a consensus/majority graph of enzymes/EC numbers to find a core metabolism shared among several organisms has to be validated against previous research. One such previous research deals with Gammaproteobacteria, but uses a slightly different approach, first calculating Enzymatic Step Sequences (ESS) and comparing these among species. Poot-Hernandez et al. (2015) list EC numbers associated with enzymes from ESS shared among most of the 40 representative species of Gammaproteobacteria in File S2, marked with the hexadecimal code for blue. It does not matter in which category the EC numbers occur, since “highly preserved” etc. only represents the percentage of EC numbers in the pathway, which are actually common in Gammaproteobacteria, and are thus marked as blue. These EC numbers are used to validate the approach of this library. EC numbers containing wildcards (e.g. 1.2.-.-) are excluded on both sides, to minimise statistical skew. Multifunctinal enzymes are, however, included, because they were not excluded by Poot-Hernandez et al. Our group consists of: 1) The exact same organisms deemed representative by Poot-Hernandez et al. (Table 2 lists them) 2) All organisms of Gammaproteobacteria 3) All organisms of Gammaproteobacteria, excluding ‘unclassified’ organisms

Question

Does the consensus/majority graph approach to core metabolism yield a similar set of EC numbers as the approach of Poot-Hernandez et al. (2015)?

Method
  • extract EC numbers from Poot-Hernandez et al. (2015) by hand, any which are marked as blue (preserved)
  • REPEAT with different groups
    1. get group of organisms deemed representative by Poot-Hernandez et al.
    1. get group of organisms ‘Gammaproteobacteria’
    1. get group of organisms ‘Gammaproteobacteria’, excluding unclassified
  • REPEAT for varying majority-percentages:
  • calculate EC numbers occuring in group’s core metabolism
  • overlap Poot-Hernandez’ set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Maj. %    others    both    ours
Representative:
100%:    228    9    14
90%:    128    109    65
80%:    71    166    113
70%:    54    183    163
60%:    44    193    209
50%:    39    198    259
40%:    33    204    315
30%:    26    211    383
20%:    24    213    466
10%:    22    215    659
1%:    15    222    1059

Gammaproteobacteria:
100%:    235    2    0
90%:    85    152    98
80%:    51    186    174
70%:    43    194    219
60%:    39    198    263
50%:    32    205    336
40%:    30    207    402
30%:    25    212    497
20%:    23    214    620
10%:    21    216    760
1%:    18    219    1070

Gammaproteobacteria without unclassified:
100%:    235    2    0
90%:    85    152    98
80%:    51    186    174
70%:    43    194    219
60%:    39    198    264
50%:    32    205    335
40%:    30    207    402
30%:    25    212    500
20%:    23    214    620
10%:    21    216    760
1%:    18    219    1070
Conclusion

Regarding the result at 1% of the representative group: There are 15 EC numbers which occur in Poot-Hernandez’ but nowhere in our organisms. Looking at the EC numbers in detail, this is easily explained by outdated used by Poot-Hernandez: 1.1.1.158 deleted 2013 1.17.1.2 deleted 2016 1.17.4.2 in none of the 40 organisms of today 1.3.1.26 deleted 2013 1.3.3.1 deleted 2011 1.3.99.1 deleted 2014 2.3.1.89 in none of the 40 organisms of today 2.4.2.11 deleted 2013 2.7.4.14 in none of the 40 organisms of today 3.5.1.47 in none of the 40 organisms of today 3.6.1.15 in none of the 40 organisms of today 3.6.1.19 deleted 2016 4.2.1.52 deleted 2012 4.2.1.60 deleted 2012 5.4.2.1 deleted 2013

The experiment should be re-run without the now obsolete EC numbers above, to avoid skewed results.

Regarding the difference between Gammaproteobacteria with and without ‘unclassified’ organisms: In the upper (100/90%) and lower (20/10/1%) regions of majority, there is no difference. Only in the middle regions some results differ by one to three counts. This comes as no surprise, because the group of Gammaproteobacteria consists of 1074 organisms, while only one of them can be excepted as ‘unclassified’. This does not leave much room for difference. Still, it might be best practice to always exclude ‘unclassified’ organisms, if only for their unknown position in taxonomy.

As to be expected, using all Gammaproteobacteria organisms, e.g. at 70% majority, yields a higher overlap between our core metabolism and theirs. But the difference is small, implying that the 40 organisms were well-selected representatives. Still, however, there is a high number of EC numbers only found in their core metabolism. This might result from their methodology. After creating the Enzymatic Step Sequences (ESS), they reduced the EC numbers in the ESS to contain only three levels, i.e. abstracting from substrate specificity keeping only reaction types. Then, at some undocumented point, they translated the set of three-level EC numbers back to the original set of EC numbers. But this results in a list of EC numbers which reactions are preserved, not which substrate specificities are preserved! In order to accurately follow their definition of preservation, we have to reduce both sets of EC numbers, ours and theirs, to their first three levels, and then re-run the experiment.

FEV_KEGG.Experiments.31 module
Context

As concluded in experiment 30, we first need to remove outdated EC numbers from Poot-Hernandez’ set. Then, we have to reduce both sets, theirs and ours, to the first three levels, and then compare them. Now only the group of representative organisms and the Gammaproteobacteria group excluding ‘unclassified’ organisms is used.

Question

Does the consensus/majority graph approach to core metabolism yield a similar set of EC numbers as the approach of Poot-Hernandez et al. (2015)?

Method
  • extract EC numbers from Poot-Hernandez et al. (2015) by hand, any which are marked as blue (preserved)
  • remove outdated EC numbers
  • reduce set of EC numbers to first three levels
  • REPEAT with different groups
    1. get group of organisms deemed representative by Poot-Hernandez et al.
    1. get group of organisms ‘Gammaproteobacteria’, excluding unclassified
  • REPEAT for varying majority-percentages:
  • calculate EC numbers occuring in group’s core metabolism
  • reduce set of EC numbers to first three levels
  • overlap Poot-Hernandez’ set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Maj. %    others    both    ours
Representative:
100%:    43    7    1
 90%:    8    42    11
 80%:    1    49    21
 70%:    0    50    32
 60%:    0    50    39
 50%:    0    50    41
 40%:    0    50    49
 30%:    0    50    56
 20%:    0    50    67
 10%:    0    50    83
  1%:    0    50    108

Gammaproteobacteria without unclassified:
100%:    49    1    0
 90%:    2    48    18
 80%:    0    50    36
 70%:    0    50    40
 60%:    0    50    44
 50%:    0    50    51
 40%:    0    50    56
 30%:    0    50    66
 20%:    0    50    80
 10%:    0    50    88
  1%:    0    50    104
Conclusion

Starting at 70% majority, there a no enzyme reactions in their core metabolism which do not also occur in ours. While this method can not verify our approach, it at least rules out the most obvious path of falsification.

Regarding the full group of Gammaproteobacteria on our side, their set of EC numbers is fully covered by ours at a higher percentage, as to be expected. Therefore, it seems to be a good idea to use the whole taxon, instead of only representative organisms, even though the taxon is more diverse than the chosen representatives, which shows in the higher count of EC numbers only in our set at any majority percentage.

On the other hand, our core metabolism is consistently larger, apart from the special case of a consensus (100%) core metabolism. This could indicate that Poot-Hernandez et al. used a high percentage of occurence - between 100% and 90% - to define ‘preserved’. Which percentage they used is, sadly, not documented. But still, there is no point of clean overlap, showing that the two approaches yield fundamentally different results, with ours yielding a bigger core metabolism.

FEV_KEGG.Experiments.32 module
Context

As in the experiments before, the set of EC numbers predicted by our approach is to be compared with the set predicted by the approach of Oh et al. (2007).

Question

Does the consensus/majority graph approach to core metabolism yield a similar set of EC numbers as the approach of Oh et al. (2007)?

Method
  • extract EC numbers from Oh et al. (2007) by hand
  • remove EC numbers with wildcards
  • get group of organisms ‘Bacillus subtilis’
  • REPEAT for varying majority-percentages:
  • calculate EC numbers occuring in group’s core metabolism
  • remove EC numbers with wildcards
  • overlap Oh’s set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Maj. %    others    both    ours
100%:    135    313    235
 90%:    114    334    261
 80%:    108    340    267
 70%:    108    340    268
 60%:    107    341    268
 50%:    107    341    268
 40%:    107    341    270
 30%:    107    341    270
 20%:    107    341    271
 10%:    107    341    274
  1%:    106    342    283
Conclusion

Even at only 1% (effectively 1 organism) majority, there are many EC numbers predicted by Oh et al., but not occuring anywhere in our model organisms. This may be caused by: 1. EC number is associated with the organism, but not listed in one of KEGG’s hand-drawn pathways. For example 1.13.11.24 is associated with all our 15 organisms, but not present in any pathway. 2. As seen in experiment 30, there may be EC numbers predicted by Oh et al. which are outdated. 3. Oh et al. used a compilation of several sources, some may have predicted EC numbers for B. subtilis which never made their way into KEGG at all, which is our only source.

FEV_KEGG.Experiments.33 module
Context

Closer look at the possible reasons for occurence of EC numbers completely unknown to us in experiment 32. 1. EC number is associated with the organism, but not listed in one of KEGG’s hand-drawn pathways. For example 1.13.11.24 is associated with all our 15 organisms, but not present in any pathway. 2. As seen in experiment 30, there may be EC numbers predicted by Oh et al. which are outdated. 3. Oh et al. used a compilation of several sources, some may have predicted EC numbers for B. subtilis which never made their way into KEGG at all, which is our only source.

Question

Does the high number of EC numbers only in their set from experiment 32 result from outdated/faulty data?

Method
  • get all EC numbers known to any organism in KEGG, using NUKA.
  • take the EC numbers only in Oh’s set at 1% majority (see 32).
  • keep only the ones occuring in NUKA.
  • keep only the ones with a gene occuring in any of our 15 KEGG organisms found as “Bacillus subtilis”
Result 
ECs not in any pathway: 50
Leaving ECs only in theirs: 58
---------------------------------
ECs not in any of our organisms: 57
Leaving ECs only in theirs: 1
3.1.3.3
Conclusion
  1. EC number is associated with the organism, but not listed in one of KEGG’s hand-drawn pathways. For example 1.13.11.24 is associated with all our 15 organisms, but not present in any pathway.

About half (50) of the EC numbers only in Oh’s set are not listed in any of KEGG’s pathways today. While B. subtilis may contain them, KEGG does not, and thus our model can not.

  1. As seen in experiment 30, there may be EC numbers predicted by Oh et al. which are outdated.
  2. Oh et al. used a compilation of several sources, some may have predicted EC numbers for B. subtilis which never made their way into KEGG at all, which is our only source.

After removing all EC numbers unknown to our organisms in KEGG today, only one remains: 3.1.3.3. This seems to be another case of inconsistent data in KEGG, because 3.1.3.3 supposedly is part of pathway 00260 and 00680, and even has three associated genes in ‘bsu’, but it is nowhere to be found in the actual pathways bsu00260 or bsu00680.

Answering the question: yes, all EC numbers missing in our model can be explained by outdated or faulty data in either their set or in KEGG. Discriminating between these two possibilities is impossible for us.

While this experiment does not imply that our model is complete, it does imply that it is correct under the constraints imposed by the completeness and correctness of the KEGG database.

FEV_KEGG.Experiments.33.isKnownToKEGG(ecNumberString, organisms)[source]
FEV_KEGG.Experiments.34 module
Context

Extending 32 by removing the outdated EC numbers found in 33.

Question

Does the consensus/majority graph approach to core metabolism yield a similar set of EC numbers as the approach of Oh et al. (2007)? Not taking into account outdated/faulty data.

Method
  • extract EC numbers from Oh et al. (2007) by hand
  • remove outdated EC numbers
  • remove EC numbers with wildcards
  • get group of organisms ‘Bacillus subtilis’
  • REPEAT for varying majority-percentages:
  • calculate EC numbers occuring in group’s core metabolism
  • remove EC numbers with wildcards
  • overlap Oh’s set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Maj. %    others    both    ours
100%:    30    311    237
 90%:    9    332    263
 80%:    3    338    269
 70%:    3    338    270
 60%:    2    339    270
 50%:    2    339    270
 40%:    2    339    272
 30%:    2    339    272
 20%:    2    339    273
 10%:    2    339    276
  1%:    1    340    285
Conclusion

Beginning with 80% majority there are less than 4 EC numbers unexplainably missing in our core metabolism. This seems to imply that our approach is correct and useful, under the constraints imposed by KEGG’s completeness and correctness.

FEV_KEGG.Experiments.35 module
Context

LUCA has previously been derived from various methods. This is a method of creating a LUCA using only annotated genomes from KEGG. It is expected to be far less precise than methods carefully crafted by experts. Furthermore, this experiment is limited to the common ancestor of Archaea, Bacteria, and Archaea+Bacteria; Eukaryota are not in the scope of this work and, thus, the truley universal LUCA is not.

Question

How many EC numbers are shared among Archaea, Bacteria, and Archaea+Bacteria? Including the ones from multifunctional enzymes.

Method
  • REPEAT for each clade in Archaea, Bacteria, Archaea+Bacteria
  • get collective metabolism of clade
  • REPEAT for varying majority percentages
  • calculate core metabolism
  • print number of ECs by majority percentage
  • IF majority percentage is 100%, i.e. consensus, also print the ECs
Result 
Archaea-CoreLUCA
100% ECs: 8 (6.1.1.2, 6.3.5.7, 6.1.1.20, 6.1.1.4, 2.7.7.6, 2.7.7.7, 6.1.1.21, 2.7.4.3) ->  1% of collective
90% ECs: 101 ->  9% of collective
80% ECs: 152 -> 14% of collective
70% ECs: 207 -> 19% of collective
60% ECs: 241 -> 23% of collective
50% ECs: 293 -> 27% of collective
40% ECs: 328 -> 31% of collective
30% ECs: 400 -> 37% of collective
20% ECs: 460 -> 43% of collective
10% ECs: 603 -> 56% of collective

Bacteria-CoreLUCA
100% ECs: 1 (2.7.7.7) ->  0% of collective
90% ECs: 86 ->  4% of collective
80% ECs: 179 ->  9% of collective
70% ECs: 262 -> 12% of collective
60% ECs: 329 -> 16% of collective
50% ECs: 394 -> 19% of collective
40% ECs: 472 -> 22% of collective
30% ECs: 582 -> 28% of collective
20% ECs: 720 -> 34% of collective
10% ECs: 969 -> 46% of collective

Archaea-Bacteria-CoreLUCA
100% ECs: 1 (2.7.7.7) ->  0% of collective
90% ECs: 70 ->  3% of collective
80% ECs: 164 ->  8% of collective
70% ECs: 255 -> 12% of collective
60% ECs: 321 -> 15% of collective
50% ECs: 388 -> 18% of collective
40% ECs: 466 -> 22% of collective
30% ECs: 571 -> 27% of collective
20% ECs: 708 -> 33% of collective
10% ECs: 965 -> 45% of collective
Conclusion

There are many EC numbers shared among all species of the Archaea, Bacteria, and even the combination of both clades. Even when defining ‘core metabolism’ by consensus, 2.7.7.7 occurs in all organisms.

However, this approach suffers harshly from incomplete annotations, not only resulting in one less count of an EC number which should have occured, but also resulting in a decreased chance of occuring within a fixed majority threshold.

FEV_KEGG.Experiments.36 module
Context

Our method of creating a LUCA was introduced in 35. Now it needs to be compared with other approaches, e.g. with Goldman et al. Beware, though, that this experiment is limited to Archaea and Bacteria, while Goldman is not! We have to reduce our resulting set of EC numbers to three levels, to be able to compare with Goldman’s set.

Question

Which EC numbers from our LUCA approach match the approach of Goldman et al?

Method
  • get Goldman-LUCA
  • REPEAT for each clade in Archaea, Bacteria, Archaea+Bacteria
  • get collective metabolism of clade
  • REPEAT for varying majority percentages
  • calculate core metabolism
  • reduce EC numbers to first three levels
  • overlap Goldman’s set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Archaea-CoreLUCA
100%:    9    1    3
90%:    6    4    37
80%:    6    4    45
70%:    5    5    53
60%:    4    6    57
50%:    3    7    62
40%:    1    9    69
30%:    1    9    78
20%:    1    9    88
10%:    0    10    104


Bacteria-CoreLUCA
100%:    9    1    0
90%:    4    6    30
80%:    3    7    45
70%:    2    8    55
60%:    1    9    63
50%:    1    9    73
40%:    0    10    83
30%:    0    10    96
20%:    0    10    107
10%:    0    10    125


Archaea-Bacteria-CoreLUCA
100%:    9    1    0
90%:    6    4    26
80%:    4    6    42
70%:    2    8    56
60%:    1    9    61
50%:    1    9    71
40%:    0    10    83
30%:    0    10    96
20%:    0    10    105
10%:    0    10    123
Conclusion

At the highest majority percentages, there is little overlap between Goldman’s LUCA and ours. Around 80%, however, there are more shared ECs than mismatched. Starting with 40% majority, almost all ECs found in Goldman’s LUCA are also in ours. Lastly, at 10% and below, all of Goldman’s ECs are included in our LUCA.

However, our LUCA is obviously much bigger than Goldman’s. This would probably not be much different when including Eukaryota. It might be because Goldman’s sources carefully compiled their list of ‘essential’ ECs by hand, implying that our list includes ‘common’ but not ‘essential’ ECs. This is a question of biochemistry and definition outside the scope of this work.

All this seems to prove that our approach is not wrong, albeit only moderately consistent with Goldman’s analysis, and generally more generous about the definition of ‘essential’.

FEV_KEGG.Experiments.37 module
Context

The concept of Simple Gene Duplication can be specialised further, to only include possibly duplicated genes which actually have an orthologous gene in the specified supergroup of ancestors. This is what Chevron Gene Duplication is for. This experiment is based on the method from 27. Keep in mind, though, that this experiment contains updated data from KEGG and, thus, yields different results.

Question

How does changing the definition of gene duplication from Simple to Chevron change the size of the resulting set of neofunctionalised ECs and Enzymes?

Method
  • get NCBI taxonomy tree
  • get group of organisms ‘Archaea/Thaumarchaeota’
  • get supergroup of organisms ‘Archaea’
  • calculate new EC numbers occuring in group’s core metabolism compared to supergroup’s core metabolism
  • calculate neofunctionalised EC numbers in group’s core metabolism
    1. for Simple Gene Duplication
    1. for Chevron Gene Duplication
Result 
new EC numbers: 110

Consensus neofunctionalisation
Simple gene duplication neofunctionalised EC numbers: 11
Chevron gene duplication neofunctionalised EC numbers: 11

Majority neofunctionalisation
Simple gene duplication neofunctionalised EC numbers: 18
Chevron gene duplication neofunctionalised EC numbers: 18
Conclusion

The Chevron Gene Duplication model yields the same number of neofunctionalised EC numbers as the Simple model. Even when using the majority neofunctionalisation approach, the numbers rise, but stay equal.

This leads to the question of whether there actually are abundant cases of genes with a paralog, but without any ortholog. Considering the general abundance of HGT, there are bound to be such cases, but hardly will they stand out when researching a small subset of Archaea.

FEV_KEGG.Experiments.38 module
Context

The approach of building a consensus/majority graph of enzymes/EC numbers to find a core metabolism shared among several organisms has to be validated against previous research. One such previous research deals with Thermus thermophilus HB27, but not with its complete metabolism, but only the essential “core” parts. They enhance the information provided by the KEGG database with information from MetaCyc and, most importantly, from manual curation with organism specific knowledge. Lee et al. (2014) list EC numbers in additional file 1 “12934_2014_968_MOESM1_ESM.xls”. As with other validations before, we have to filter EC numbers which are outdated, or somehow not represented by KEGG’s standard pathways. This is done here by restricting any EC number to the ones in NUKA, whis is done for both, their and our set of EC numbers.

Question

Does the consensus/majority graph approach to core metabolism yield a similar set of EC numbers as the approach of Lee et al. (2014)?

Method
  • extract EC numbers from Lee et al. (2014) by hand
  • sanitise them by leaving only the ones found in NUKA
  • also remove the ones with wildcards
  • REPEAT with different groups
    1. get group of organisms ‘Thermus thermophilus’
    1. get only the organism ‘Thermus thermophilus HB27’
  • REPEAT for varying majority-percentages:
  • calculate EC numbers occuring in group’s core metabolism
  • sanitise them by leaving only the ones found in NUKA
  • also remove the ones with wildcards
  • overlap their set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Maj. %  others  both   ours
All Thermus thermophilus:
100%:    118    306    106
90%:    118    306    106
80%:    118    306    106
70%:    111    313    119
60%:    111    313    119
50%:    102    322    138
40%:    102    322    138
30%:    102    322    138
20%:     95    329    160
10%:     95    329    160
1%:     95    329    160

Thermus thermophilus HB27:
100%:    98    326    119
90%:    98    326    119
80%:    98    326    119
70%:    98    326    119
60%:    98    326    119
50%:    98    326    119
40%:    98    326    119
30%:    98    326    119
20%:    98    326    119
10%:    98    326    119
1%:    98    326    119
Conclusion

Comparing the core metabolism of all Thermus thermophilus, we see less overlap between both sets of EC numbers, which was to be expected. Still, this shows that the variance between Thermus thermophilus subspecies is not huge, but certainly visible. Three EC numbers only overlap when using the consensus metabolism of the whole group (329 vs. 326), indicating that Lee et al. manually added these EC numbers to their HB27 model, while they also exist in other subspecies known to KEGG.

For further analysis, we only regard the metabolism of the HB27 subspecies.

About 30% of overlapping EC numbers fall off either side. This shows a significant disrepancy between today’s data and/or the data Lee et al. added manually. If there were mainly EC numbers occuring only in their set, they would clearly stem from the manual addition. However, even more EC numbers occur only in our set, which raises the question if that many EC numbers could have been added to these organisms in KEGG since 2014. While this is possible, we sadly have no way to verify this. All in all, the overlap is about 60% of the total sum of all EC numbers occuring in either set. This at least shows a fundamental consensus between both approaches and data sets.

FEV_KEGG.Experiments.39 module
Context

The approach of building a consensus/majority graph of enzymes/EC numbers to find a core metabolism shared among several organisms has to be validated against previous research. One such previous research deals with seven representative genomes of Thaumarchaeota, but manually curates all genes, including their associated EC numbers. Kerou et al. (2016) list EC numbers in the additional file “Dataset_S02.xlsx”, from which we extracted the ones on the sheets “Cell surface & glycosyl” and “Metabolism”. As with other validations before, we have to filter EC numbers which are outdated, or somehow not represented by KEGG’s standard pathways. This is done here by restricting any EC number to the ones in NUKA, whis is done for both, their and our set of EC numbers.

Question

Does the consensus/majority graph approach to core metabolism yield a similar set of EC numbers as the approach of Kerou et al. (2016)?

Method
  • extract EC numbers from Kerou et al. (2016) by hand
  • sanitise them by leaving only the ones found in NUKA
  • also remove the ones with wildcards
  • REPEAT with different groups
    1. get group of organisms by clade ‘Thaumarchaeota’
    1. get only the seven organisms used by Kerou et al. (2016)
  • REPEAT for varying majority-percentages:
  • calculate EC numbers occuring in group’s core metabolism
  • sanitise them by leaving only the ones found in NUKA
  • also remove the ones with wildcards
  • overlap their set with ours and print amount of EC numbers inside the intersection and falling off either side
Result 
Maj. %  others both   ours
Thaumarchaeota:
100%:   102     65     80
90%:    73     94    139
80%:    66    101    154
70%:    65    102    156
60%:    62    105    162
50%:    60    107    167
40%:    58    109    174
30%:    53    114    188
20%:    51    116    203
10%:    46    121    240
1%:    38    129    334

Representative organisms:
100%:    74     93    142
90%:    74     93    142
80%:    65    102    155
70%:    65    102    161
60%:    65    102    161
50%:    61    106    174
40%:    53    114    191
30%:    53    114    191
20%:    50    117    209
10%:    47    120    245
1%:    47    120    245
Conclusion

When comparing the core metabolisms of all Thaumarchaeota known today, with only the ones from the seven representative organisms, there is not much difference. This shows that these seven organisms are indeed very well chosen representatives.

Considering the amount of EC numbers falling off to either side: The number of ECs only in our set is larger than the overlap, thus, we again see that core metabolisms created with our approach tend to be bigger than manually curated ones. The latter is most likely due to the fact that ECs which occur in all genomes do not necessarily have to be essential, while Kerou et al. aimed at only including essential ECs. The number of ECs only in their set is also very high, accounting to roughly 65% of the overlap, or 40% of their set, and 20% of the overall set. These ECs only in their set can not stem from ECs not in KEGG pathways at all, since we pre-filtered them using NUKA. The most likely explanations seems to be that Kerou et al. were able to annotate many more EC numbers manually than KEGG’s GENE database has stored to this date. This, again, would mean that KEGG’s data is incomplete, which is strongly implied by the fact that even the collective graph (1% majority) does not contain 47 of the representative’s EC numbers, which can only happen if these EC numbers are nowhere to be found in any of today’s seven organisms in KEGG.

In conclusion of the effectiveness of our approach of building a core metabolism, we are left to say that completeness and quality of EC number annoations vary greatly, both within literature and KEGG. Therefore, to achieve the most exact model of an organisms metabolism, one needs to apply further steps beyond our approach. Such steps may involve flux balance analysis with a manually curated list of ‘essential’ metabolites. Still, however, when reducing the set of EC numbers to the ones known to standard KEGG pathways (using NUKA), core metabolisms created via our approach can be used to roughly compare the metabolic capabilities of closely, or even remotely related organisms, groups of organisms, and whole clades.

FEV_KEGG.Experiments.40 module
Question

When comparing the core metabolism of Archaea and Gammaproteobacteria, what differences and similarities occur?

Method
  • build Archaea -> Gammaproteobacteria clade pair
  • export coloured graph to file, containing all three sets of differing ECs, using the default majority percentage of 80
  • REPEAT for varying majority-percentages:
  • overlap sets and print amount of EC numbers inside the intersection and falling off either side
  • remove wildcard EC numbers
Result 
Maj. %    Archaea    both    Gammap.
100%:    6    2    0
90%:    28    48    154
80%:    33    81    192
70%:    41    121    182
60%:    52    135    201
50%:    73    163    236
40%:    81    188    282
30%:    97    224    319
20%:    102    262    384
10%:    121    355    423
1%:    135    613    509
Conclusion

Regarding 100% majority, it is obvious that neither Archaea, nor Gammaproteobacteria have a significant consensus in themselves, leaving no room for a significant consensus between them. It might be noted that Archaea seem to tend to have a bigger consensus, 8 vs. 2, but then they have only quarter of the organisms the Gammaproteobacteria consist of. What this does show, however, is that both taxa possess a great varity of metabolic capabilities, or at least a lack of complete data sets.

Regarding the span between 90% and 10% majority, the amount of ECs added in either category grow almost linearly, with a slight exponential tendency, but equally distributed between the three sets.

Regarding the jump from 10% to 1%, it shows that both groups suddenly share almost double the ECs, without adding much more to their only set. This might ordinarily mean that both groups are equally diversified in metabolic function and they use most functions known to nature.

However, this could also be evidence of horizontal gene transfer rarely occuring between small numbers of archaea and gammaproteobacteria strains. To further research this idea, one would have to extract the ECs occuring only in a few archaea/gammaproteobacteria (~1% majority). Then for each EC, find the encoding enzymes, grouped by archaea and gammaproteobacteria. Then, find out how many of these enzymes, sharing the same EC but belonging to different groups, have orthologous genes. If there is a significant amount of these, it is proof of relatively abundant horizontal gene transfer for rare metabolic functions.

FEV_KEGG.Experiments.40.getArchaeaClade()[source]
FEV_KEGG.Experiments.40.getGammaproteobacteriaClade()[source]
FEV_KEGG.Experiments.41 module
Question

When comparing the core metabolism of Archaea and Bacteria, what differences and similarities occur?

Method
  • build Bacteria clade
  • build Archaea clade
  • REPEAT for varying majority-percentages:
  • overlap core metabolisms and print amount of EC numbers inside the intersection and falling off either side
  • remove wildcard EC numbers
  • END
  • build clade pair
  • export unified metabolism, coloured by only-Archaea/both/only-Bacteria
Result 
Maj. %    Bacteria    both    Archaea
100%:    0    1    7
90%:    50    40    36
80%:    83    67    47
70%:    103    103    59
60%:    125    129    58
50%:    153    163    72
40%:    191    192    75
30%:    235    229    90
20%:    304    279    83
10%:    400    386    87
1%:    631    653    91

See bacteria_vs_archaea.jpeg
Conclusion

Bacteria and Archaea always share a significant amount of EC numbers, but never all of them. The much bigger group of Bacteria also has many more EC numbers which never occur in Archaea. This might be because there are more known Bacteria organisms than known Archaea organisms, i.e. a statistical skew. Or it might be because Bacteria are, as a group, more versatile in habitat than Archaea.

The exported graph comparing Bacteria and Archaea directly (at 80% majority) shows several regions (more or less complete pathways) which only occur in either of the clades’ core metabolisms. Which does not mean they do not occur in any individual organism of the other clade! For example: Only in Bacteria: 00061 Fatty acid biosynthesis and 00550 Peptidoglycan biosynthesis Only in Archaea: 00790 Folate biosynthesis and 00900 Terpenoid backbone biosynthesis

Apart from these regions standing out, both clades seem to have evolved different ways of providing redundancy to their common metabolism.

FEV_KEGG.Experiments.41.getArchaeaClade()[source]
FEV_KEGG.Experiments.41.getBacteriaClade()[source]
FEV_KEGG.Experiments.42 module
Question

Which EC numbers of the core metabolism of Archaea come into the core at which majority percentage?

Method
  • get Archaea clade
  • calculate collective metabolism, containing the majority percentage thershold for each edge
  • export graph annotating each edge with its majority threshold (can be interpreted as transparency)
Result
::
See archaea.png
Conclusion

The resulting graph, interpreting the majority threshold at which an edge appears as transparency, shows that minorities of Archaea usually add to the core metabolism on the outside. This adds capabilities to metabolise under more conditions. Sometimes ths even connects components of the graph not connected in a majority of Archaea. However, it also seems quite widespread to add redundancy to the central parts of the core, increasing robustness. Although sometimes, the added edges in the central parts of the core might also be necessary to prevent breakage of the graph, because another edge which is part of a majority of Archaea might be missing in a certain minority, requiring replacement without actually providing redundancy. This can not be visualised in this kind of graph.

FEV_KEGG.Experiments.42.getArchaeaClade()[source]
FEV_KEGG.Experiments.43 module
Question

Which EC numbers in Desulfobacterales, come from neofunctionalised enzymes? How do they differ varying certain parameters of computation? Which is the set of parameters most suited for investigating neofunctionalisation?

Method
  • Get the clade
  • Print all neofunctionalised EC numbers
  • REPEAT for varying parameters of computation:
  • Different gene duplication models: SimpleGeneDuplication / SimpleGroupGeneDuplication
  • Different set of allowed gene duplicates: restricted to enzymes within the core metabolism / unrestricted
  • Different neofunctionalisation-majority values. This is the number of organisms (in percent of the group) required to have a neofunctionalisation involving an EC number fort this EC number to be reported as “neofunctionalised”.
Result
::

neofunctionalisation-majority: 70%

SimpleGeneDuplication + unrestricted: 29 (62%) 1.17.1.9 1.3.5.4 1.4.3.16 2.1.3.2 2.1.3.3 2.5.1.1 2.5.1.10 2.5.1.29 2.5.1.90 2.6.1.11 2.6.1.17 2.6.1.85 4.1.3.27 4.2.1.46 5.1.3.2 5.1.3.6 5.4.2.10 5.4.2.8 5.4.3.8 6.1.1.4 6.1.1.5 6.1.1.6 6.1.1.9 6.2.1.- 6.2.1.1 6.2.1.3 6.3.1.- 6.3.2.45 6.3.2.8

SimpleGeneDuplication + restriction: 7 (15%) 2.1.3.2 2.1.3.3 4.2.1.46 5.1.3.6 6.1.1.4 6.1.1.5 6.1.1.9

SimpleGroupGeneDuplication + unrestricted: 56 (119%) 1.1.1.205 1.1.1.23 1.1.1.308 1.1.1.42 1.1.1.85 1.3.5.1 1.3.5.4 1.4.1.1 1.4.3.16 1.5.1.20 1.6.1.2 1.7.1.7 2.1.1.10 2.1.2.1 2.1.2.10 2.1.3.2 2.1.3.3 2.2.1.1 2.2.1.7 2.3.1.1 2.5.1.1 2.5.1.10 2.5.1.29 2.5.1.47 2.5.1.54 2.5.1.55 2.5.1.90 2.6.1.- 2.6.1.83 2.6.1.85 2.6.1.9 2.7.2.8 3.5.2.2 3.5.2.3 4.1.1.3 4.1.1.48 4.1.1.81 4.1.3.27 4.2.1.12 4.2.1.46 4.2.1.9 5.1.3.2 5.1.3.6 5.3.1.24 5.4.2.10 5.4.2.8 5.4.99.18 6.1.1.16 6.1.1.17 6.1.1.18 6.1.1.4 6.1.1.5 6.1.1.6 6.1.1.9 6.3.4.13 6.4.1.1

SimpleGroupGeneDuplication + restriction: 29 (62%) 1.1.1.42 1.1.1.85 2.1.3.2 2.1.3.3 2.3.1.1 2.5.1.47 2.5.1.54 2.5.1.55 2.6.1.1 2.6.1.83 2.6.1.9 2.7.2.8 2.7.9.1 2.7.9.2 4.1.1.3 4.2.1.46 5.1.3.2 5.1.3.6 6.1.1.12 6.1.1.16 6.1.1.17 6.1.1.18 6.1.1.4 6.1.1.5 6.1.1.6 6.1.1.9 6.2.1.1 6.2.1.3 6.4.1.1

neofunctionalisation-majority: 20%

SimpleGeneDuplication + restriction: 25 (53%) 1.1.1.42 1.1.1.85 2.1.3.2 2.1.3.3 2.4.2.14 2.5.1.47 2.5.1.54 2.5.1.55 2.6.1.1 2.6.1.16 2.6.1.83 2.6.1.9 4.2.1.46 5.1.3.2 5.1.3.6 6.1.1.12 6.1.1.16 6.1.1.4 6.1.1.5 6.1.1.6 6.1.1.9 6.2.1.1 6.2.1.3 6.3.2.8 6.3.2.9

SimpleGroupGeneDuplication + restriction: 34 (72%) 1.1.1.42 1.1.1.85 2.1.3.2 2.1.3.3 2.3.1.1 2.4.2.14 2.5.1.47 2.5.1.54 2.5.1.55 2.6.1.1 2.6.1.16 2.6.1.83 2.6.1.9 2.7.2.8 2.7.9.1 2.7.9.2 4.1.1.3 4.2.1.46 5.1.3.2 5.1.3.6 6.1.1.12 6.1.1.16 6.1.1.17 6.1.1.18 6.1.1.22 6.1.1.4 6.1.1.5 6.1.1.6 6.1.1.9 6.2.1.1 6.2.1.3 6.3.2.8 6.3.2.9 6.4.1.1

neofunctionalisation-majority: 0%

SimpleGeneDuplication + restriction: 30 (64%) 1.1.1.42 1.1.1.85 2.1.3.2 2.1.3.3 2.3.1.1 2.4.2.14 2.5.1.47 2.5.1.54 2.5.1.55 2.6.1.1 2.6.1.16 2.6.1.83 2.6.1.9 2.7.2.8 2.7.9.1 2.7.9.2 4.2.1.46 5.1.3.2 5.1.3.6 6.1.1.12 6.1.1.16 6.1.1.22 6.1.1.4 6.1.1.5 6.1.1.6 6.1.1.9 6.2.1.1 6.2.1.3 6.3.2.8 6.3.2.9

Conclusion

Restricting the set of allowed gene duplicates to enzymes within the core metabolism helps to keep secondary metabolism out, when this is wanted. As we usually handle core metabolisms, we certainly want to keep ties to non-core metabolism out of the results.

One problem could be too few cases of neofunctionalisation, which can be avoided using SimpleGeneDuplication with a low neofunctionalisation-majority value.

SimpleGroupGeneDuplication is far too slow for groups of significant size, even for the small group of Desulfobacterales (9 organisms), the download of all gene matching takes about one hour. With the increase of group size, the time to download grows almost exponentially.

In summary, we will only be using SimpleGeneDuplication + restriction for investigating neofunctionalisation.

FEV_KEGG.Experiments.43.getDesulfobacteralesClade()[source]
FEV_KEGG.Experiments.44 module
Question

Which EC numbers are linked with neofunctionalisations in Deltaproteobacteria and Spirochaetes? How do the two groups compare?

Method
  • get both clades
  • calculate set of “neofunctionalised” ECs for Alphaproteobacteria
  • calculate set of “neofunctionalised” ECs for Betaproteobacteria
  • REPEAT for varying core metabolism majority-percentages:
  • overlap sets and print amount of EC numbers inside the intersection and falling off either side
Result 
core metabolism majority: 80%
neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)

Deltaproteobacteria:

core metabolism ECs: 228

"neofunctionalised" ECs: 36 (16%)
1.1.1.42
1.1.1.85
2.1.3.2
2.1.3.3
2.2.1.1
2.2.1.7
2.4.2.14
2.5.1.47
2.6.1.1
2.6.1.16
2.6.1.62
2.6.1.9
4.1.3.-
4.2.1.46
5.1.1.1
5.1.3.2
5.1.3.6
5.3.1.16
5.4.3.8
5.4.99.18
6.1.1.12
6.1.1.16
6.1.1.17
6.1.1.18
6.1.1.22
6.1.1.4
6.1.1.5
6.1.1.6
6.1.1.9
6.2.1.1
6.2.1.3
6.3.2.10
6.3.2.13
6.3.2.8
6.3.2.9
6.3.4.13


Spirochaetes:

core metabolism ECs: 80

"neofunctionalised" ECs: 10 (12%)
6.1.1.10
6.1.1.12
6.1.1.20
6.1.1.22
6.1.1.4
6.1.1.5
6.1.1.6
6.1.1.9
6.3.2.13
6.3.2.8


Comparison:
100%:   0       2       3
80%:    28      8       2
60%:    47      8       4
40%:    72      20      8
20%:    125     40      14
Conclusion

Deltaproteobacteria consistently have more “neofunctionalised” EC numbers, which is not surprising, as the core metabolism is much bigger. The same effect explains the constant increase in “neofunctionalised” EC numbers with growing core metabolism, due to lower majority-percentage. This indicates that neofunctionalisation is widespread and not limited to the most important, hence widespread, parts of metabolism. However, there might still be a statistical skew which remains to be investigated.

Occurence in these results above does not mean, that those ECs are actually “neofunctionalised” in all of the organisms! Because in this experiment, a single neofunctionalisation is enough to mark the associated ECs as “neofunctionalised”. It might be interesting to increase the neofunctionalisation majority percentage, to only include ECs which have neofunctionalisations in x% of the clade’s organisms.

FEV_KEGG.Experiments.44.getCladeA()[source]
FEV_KEGG.Experiments.44.getCladeB()[source]
FEV_KEGG.Experiments.45 module
Question

How many EC numbers in Deltaproteobacteria are (partially) redundant?

Method
  • get Deltaproteobacteria
  • get core metabolism
  • calculate redundancy
  • print percentage of redundant ECs, for all types of redundancy
Result
::

core metabolism majority: 80%

Deltaproteobacteria:

core metabolism ECs: 228

Robustness fully: 7.0% Robustness partial: 4.8% Robustness both: 11.8%

Flexibility fully: 17.1% Flexibility partial: 13.6% Flexibility both: 30.7%

Target-flexibility fully: 21.9% Target-flexibility partial: 22.8% Target-flexibility both: 44.7%

Source-flexibility fully: 40.8% Source-flexibility partial: 24.6% Source-flexibility both: 65.4%

Conclusion

As expected, the occurence of redundancy increases with a more general definition.

However, it seems to be odd, at first, to have a much higher source-flexibility than target-flexibility. This might be explained by the idea that, in general, metabolism has a main direction, because its purpose is to take one heap of molecules and turn it into a more useful heap of molecules. This obviously only works if at least some enzymes only catalyse one direction of the reaction, the one towards the more useful molecule. If we presume this is the case, there have to be substances which are mostly consumed, likely in the center of the metabolic network, and substances which are mostly produced, likely at the rim of the metabolic network. Substances mostly consumed are very likely to have redundant edges leading away from them, but any intermediate product might not be as likely to be the intermediate product of another path. There is a similar case for end products: they are unlikely to be the end product of another path, but it might still be that their predecessor is the intermediate product of another path.

FEV_KEGG.Experiments.45.getClade()[source]
FEV_KEGG.Experiments.46 module
Question

Which gene-duplicated enzymes exist in Deltaproteobacteria? Does their existence increase redundancy? If yes, how much?

Method
  • get Deltaproteobacteria
  • get and print gene-duplicated enzyme pairs
  • calculate redundancy
  • REPEAT for each gene-duplicated enzyme
  • print number of enzymes the gene-duplicated enzyme provides redundancy for (robustness and flexibility)
Result
::

core metabolism majority: 80%

Deltaproteobacteria:

core metabolism enzymes: 21519

gene-duplicated enzyme pairs: 5561 (ade:Adeh_0005, ade:Adeh_2750) (ade:Adeh_0012, ade:Adeh_2390) (ade:Adeh_0012, ade:Adeh_2727) (ade:Adeh_0036, ade:Adeh_0038) (ade:Adeh_0069, ade:Adeh_4344) (ade:Adeh_0171, ade:Adeh_0588) (ade:Adeh_0221, ade:Adeh_1954) (ade:Adeh_0221, ade:Adeh_1955) (ade:Adeh_0221, ade:Adeh_4288) (ade:Adeh_0255, ade:Adeh_1600) (ade:Adeh_0255, ade:Adeh_2078) (ade:Adeh_0255, ade:Adeh_3927) (ade:Adeh_0295, ade:Adeh_2597) (ade:Adeh_0533, ade:Adeh_1731) (ade:Adeh_0533, ade:Adeh_2315) (ade:Adeh_0592, ade:Adeh_1048) (ade:Adeh_0768, ade:Adeh_3694) (ade:Adeh_0821, ade:Adeh_1830) (ade:Adeh_0925, ade:Adeh_1165) (ade:Adeh_0925, ade:Adeh_2345) (ade:Adeh_0925, ade:Adeh_2359) (ade:Adeh_0925, ade:Adeh_2886) (ade:Adeh_1015, ade:Adeh_1978) (ade:Adeh_1052, ade:Adeh_2654) (ade:Adeh_1052, ade:Adeh_3428) (ade:Adeh_1057, ade:Adeh_4305) (ade:Adeh_1078, ade:Adeh_2533) (ade:Adeh_1165, ade:Adeh_2345) (ade:Adeh_1165, ade:Adeh_2359) (ade:Adeh_1165, ade:Adeh_2619) (ade:Adeh_1165, ade:Adeh_2886) (ade:Adeh_1280, ade:Adeh_2316) (ade:Adeh_1280, ade:Adeh_2668) (ade:Adeh_1312, ade:Adeh_3637) (ade:Adeh_1334, ade:Adeh_2434) (ade:Adeh_1600, ade:Adeh_2078) (ade:Adeh_1600, ade:Adeh_3927) (ade:Adeh_1613, ade:Adeh_2484) (ade:Adeh_1618, ade:Adeh_2691) (ade:Adeh_1638, ade:Adeh_3931) (ade:Adeh_1729, ade:Adeh_3514) (ade:Adeh_1954, ade:Adeh_1955) (ade:Adeh_1954, ade:Adeh_4288) (ade:Adeh_1955, ade:Adeh_4288) (ade:Adeh_1963, ade:Adeh_2867) (ade:Adeh_1981, ade:Adeh_2071) (ade:Adeh_1981, ade:Adeh_3037) (ade:Adeh_1994, ade:Adeh_2493) (ade:Adeh_2047, ade:Adeh_2619) (ade:Adeh_2047, ade:Adeh_3396) (ade:Adeh_2057, ade:Adeh_4242) (ade:Adeh_2078, ade:Adeh_3927) (ade:Adeh_2316, ade:Adeh_2668) (ade:Adeh_2345, ade:Adeh_2359) (ade:Adeh_2345, ade:Adeh_2886) (ade:Adeh_2349, ade:Adeh_3135) (ade:Adeh_2359, ade:Adeh_2886) (ade:Adeh_2390, ade:Adeh_2727) (ade:Adeh_2449, ade:Adeh_3774) (ade:Adeh_2533, ade:Adeh_2728) (ade:Adeh_2619, ade:Adeh_3396) (ade:Adeh_2748, ade:Adeh_2760) (ade:Adeh_2748, ade:Adeh_3141) (ade:Adeh_2760, ade:Adeh_3141) (ade:Adeh_2780, ade:Adeh_2789) (ade:Adeh_3748, ade:Adeh_4057) (ade:Adeh_3766, ade:Adeh_3767) (ade:Adeh_3766, ade:Adeh_3769) (ade:Adeh_3769, ade:Adeh_3772) (ade:Adeh_3784, ade:Adeh_4220) (ade:Adeh_3959, ade:Adeh_4206) (afw:Anae109_0005, afw:Anae109_2739) (afw:Anae109_0013, afw:Anae109_1477) (afw:Anae109_0013, afw:Anae109_2719) (afw:Anae109_0039, afw:Anae109_0041) (afw:Anae109_0070, afw:Anae109_4491) (afw:Anae109_0075, afw:Anae109_1348) (afw:Anae109_0087, afw:Anae109_2040) (afw:Anae109_0125, afw:Anae109_4122) (afw:Anae109_0180, afw:Anae109_0633) (afw:Anae109_0276, afw:Anae109_0508) (afw:Anae109_0276, afw:Anae109_2213) (afw:Anae109_0315, afw:Anae109_2025) (afw:Anae109_0315, afw:Anae109_3317) (afw:Anae109_0319, afw:Anae109_1264) (afw:Anae109_0323, afw:Anae109_2310) (afw:Anae109_0371, afw:Anae109_3865) (afw:Anae109_0462, afw:Anae109_4354) (afw:Anae109_0473, afw:Anae109_2361) (afw:Anae109_0473, afw:Anae109_3313) (afw:Anae109_0473, afw:Anae109_3360) (afw:Anae109_0508, afw:Anae109_2213) (afw:Anae109_0637, afw:Anae109_1098) (afw:Anae109_0814, afw:Anae109_3137) (afw:Anae109_0814, afw:Anae109_3823) (afw:Anae109_0859, afw:Anae109_1990) (afw:Anae109_0968, afw:Anae109_1212) (afw:Anae109_0968, afw:Anae109_1510) (afw:Anae109_0968, afw:Anae109_1529) (afw:Anae109_1089, afw:Anae109_1877) (afw:Anae109_1102, afw:Anae109_2639) (afw:Anae109_1117, afw:Anae109_1329) (afw:Anae109_1136, afw:Anae109_3317) (afw:Anae109_1212, afw:Anae109_1510) (afw:Anae109_1212, afw:Anae109_1529) (afw:Anae109_1212, afw:Anae109_2586) (afw:Anae109_1212, afw:Anae109_3170) (afw:Anae109_1374, afw:Anae109_1845) (afw:Anae109_1384, afw:Anae109_2198) (afw:Anae109_1418, afw:Anae109_3887) (afw:Anae109_1445, afw:Anae109_2433) (afw:Anae109_1477, afw:Anae109_2719) (afw:Anae109_1510, afw:Anae109_1529) (afw:Anae109_1524, afw:Anae109_3133) (afw:Anae109_1753, afw:Anae109_1874) (afw:Anae109_1767, afw:Anae109_2586) (afw:Anae109_1767, afw:Anae109_3170) (afw:Anae109_1767, afw:Anae109_3461) 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(dgg:DGI_1348, dgg:DGI_2795) (dgg:DGI_1422, dgg:DGI_3110) (dgg:DGI_1438, dgg:DGI_1737) (dgg:DGI_1438, dgg:DGI_2476) (dgg:DGI_1438, dgg:DGI_3014) (dgg:DGI_1613, dgg:DGI_4019) (dgg:DGI_1648, dgg:DGI_1902) (dgg:DGI_1648, dgg:DGI_2774) (dgg:DGI_1737, dgg:DGI_2476) (dgg:DGI_1737, dgg:DGI_3014) (dgg:DGI_1796, dgg:DGI_1888) (dgg:DGI_1805, dgg:DGI_1879) (dgg:DGI_1807, dgg:DGI_1877) (dgg:DGI_1837, dgg:DGI_3520) (dgg:DGI_1851, dgg:DGI_3260) (dgg:DGI_1902, dgg:DGI_2774) (dgg:DGI_2188, dgg:DGI_2546) (dgg:DGI_2242, dgg:DGI_2476) (dgg:DGI_2250, dgg:DGI_2938) (dgg:DGI_2250, dgg:DGI_3042) (dgg:DGI_2250, dgg:DGI_3046) (dgg:DGI_2466, dgg:DGI_3030) (dgg:DGI_2476, dgg:DGI_3014) (dgg:DGI_2503, dgg:DGI_3263) (dgg:DGI_2521, dgg:DGI_2781) (dgg:DGI_2559, dgg:DGI_2876) (dgg:DGI_2559, dgg:DGI_3140) (dgg:DGI_2559, dgg:DGI_3493) (dgg:DGI_2657, dgg:DGI_2716) (dgg:DGI_2681, dgg:DGI_3398) (dgg:DGI_2876, dgg:DGI_3140) (dgg:DGI_2876, dgg:DGI_3493) (dgg:DGI_2938, dgg:DGI_2942) (dgg:DGI_2938, dgg:DGI_3042) (dgg:DGI_2938, dgg:DGI_3046) (dgg:DGI_2942, dgg:DGI_3042) (dgg:DGI_2942, dgg:DGI_3046) (dgg:DGI_3042, dgg:DGI_3046) (dgg:DGI_3140, dgg:DGI_3493) (dgg:DGI_3482, dgg:DGI_3507) (dhy:DESAM_10054, dhy:DESAM_20574) (dhy:DESAM_10054, dhy:DESAM_21809) (dhy:DESAM_10059, dhy:DESAM_20948) (dhy:DESAM_10157, dhy:DESAM_20373) (dhy:DESAM_10157, dhy:DESAM_20586) (dhy:DESAM_10178, dhy:DESAM_22526) (dhy:DESAM_10265, dhy:DESAM_22216) (dhy:DESAM_20002, dhy:DESAM_22296) (dhy:DESAM_20071, dhy:DESAM_20072) (dhy:DESAM_20071, dhy:DESAM_21286) (dhy:DESAM_20072, dhy:DESAM_21286) (dhy:DESAM_20147, dhy:DESAM_21598) (dhy:DESAM_20155, dhy:DESAM_20564) (dhy:DESAM_20155, dhy:DESAM_20633) (dhy:DESAM_20155, dhy:DESAM_20863) (dhy:DESAM_20155, dhy:DESAM_20933) (dhy:DESAM_20155, dhy:DESAM_21612) (dhy:DESAM_20155, dhy:DESAM_22144) (dhy:DESAM_20160, dhy:DESAM_21173) (dhy:DESAM_20241, dhy:DESAM_20902) (dhy:DESAM_20242, dhy:DESAM_21156) (dhy:DESAM_20242, dhy:DESAM_22147) (dhy:DESAM_20244, dhy:DESAM_21153) (dhy:DESAM_20245, dhy:DESAM_22644) (dhy:DESAM_20254, dhy:DESAM_20480) (dhy:DESAM_20254, dhy:DESAM_22252) (dhy:DESAM_20295, dhy:DESAM_20696) (dhy:DESAM_20295, dhy:DESAM_20962) (dhy:DESAM_20338, dhy:DESAM_22470) (dhy:DESAM_20409, dhy:DESAM_23096) (dhy:DESAM_20444, dhy:DESAM_20447) (dhy:DESAM_20444, dhy:DESAM_22632) (dhy:DESAM_20447, dhy:DESAM_22632) (dhy:DESAM_20480, dhy:DESAM_22252) (dhy:DESAM_20492, dhy:DESAM_22667) (dhy:DESAM_20564, dhy:DESAM_20633) (dhy:DESAM_20564, dhy:DESAM_20863) (dhy:DESAM_20564, dhy:DESAM_20933) (dhy:DESAM_20564, dhy:DESAM_21612) (dhy:DESAM_20633, dhy:DESAM_20863) (dhy:DESAM_20633, dhy:DESAM_20933) (dhy:DESAM_20633, dhy:DESAM_21612) (dhy:DESAM_20683, dhy:DESAM_20949) (dhy:DESAM_20683, dhy:DESAM_21666) (dhy:DESAM_20683, dhy:DESAM_22139) (dhy:DESAM_20683, dhy:DESAM_22222) (dhy:DESAM_20683, dhy:DESAM_22335) (dhy:DESAM_20696, dhy:DESAM_20962) (dhy:DESAM_20710, dhy:DESAM_22412) (dhy:DESAM_20726, dhy:DESAM_20916) (dhy:DESAM_20726, dhy:DESAM_21837) (dhy:DESAM_20726, dhy:DESAM_22057) (dhy:DESAM_20726, dhy:DESAM_22216) (dhy:DESAM_20796, dhy:DESAM_21103) (dhy:DESAM_20814, dhy:DESAM_22360) (dhy:DESAM_20814, dhy:DESAM_22954) (dhy:DESAM_20816, dhy:DESAM_22128) (dhy:DESAM_20816, dhy:DESAM_22453) (dhy:DESAM_20863, dhy:DESAM_20933) (dhy:DESAM_20863, dhy:DESAM_21612) (dhy:DESAM_20884, dhy:DESAM_21172) (dhy:DESAM_20884, dhy:DESAM_22958) (dhy:DESAM_20916, dhy:DESAM_21837) (dhy:DESAM_20916, dhy:DESAM_22057) (dhy:DESAM_20916, dhy:DESAM_22216) (dhy:DESAM_20933, dhy:DESAM_21612) (dhy:DESAM_20949, dhy:DESAM_21666) (dhy:DESAM_20949, dhy:DESAM_22139) (dhy:DESAM_20949, dhy:DESAM_22222) (dhy:DESAM_20949, dhy:DESAM_22335) (dhy:DESAM_20985, dhy:DESAM_22951) (dhy:DESAM_21156, dhy:DESAM_22147) (dhy:DESAM_21172, dhy:DESAM_22958) (dhy:DESAM_21414, dhy:DESAM_21558) (dhy:DESAM_21448, dhy:DESAM_21850) (dhy:DESAM_21448, dhy:DESAM_22210) (dhy:DESAM_21666, dhy:DESAM_22139) (dhy:DESAM_21666, dhy:DESAM_22222) (dhy:DESAM_21666, dhy:DESAM_22335) (dhy:DESAM_21680, dhy:DESAM_21926) (dhy:DESAM_21837, dhy:DESAM_22216) (dhy:DESAM_21922, dhy:DESAM_22258) (dhy:DESAM_22043, dhy:DESAM_23096) (dhy:DESAM_22057, dhy:DESAM_22216) (dhy:DESAM_22128, dhy:DESAM_22453) (dhy:DESAM_22139, dhy:DESAM_22222) (dhy:DESAM_22139, dhy:DESAM_22335) (dhy:DESAM_22222, dhy:DESAM_22335) (dhy:DESAM_22317, dhy:DESAM_22957) (dhy:DESAM_22360, dhy:DESAM_22954) (dhy:DESAM_22427, dhy:DESAM_22538) (dhy:DESAM_22537, dhy:DESAM_22801) (dhy:DESAM_22936, dhy:DESAM_22955) (dma:DMR_00110, dma:DMR_28600) (dma:DMR_00430, dma:DMR_04400) (dma:DMR_00560, dma:DMR_42760) (dma:DMR_01800, dma:DMR_37150) (dma:DMR_01890, dma:DMR_02380) (dma:DMR_01890, dma:DMR_16700) (dma:DMR_02050, dma:DMR_04560) (dma:DMR_02050, dma:DMR_22170) (dma:DMR_02170, dma:DMR_33250) (dma:DMR_02380, dma:DMR_16700) (dma:DMR_04400, dma:DMR_45660) (dma:DMR_04560, dma:DMR_22170) (dma:DMR_05110, dma:DMR_09030) (dma:DMR_05110, dma:DMR_11340) (dma:DMR_05110, dma:DMR_16990) (dma:DMR_05110, dma:DMR_25440) (dma:DMR_05110, dma:DMR_27000) (dma:DMR_05260, dma:DMR_19490) (dma:DMR_05730, dma:DMR_34300) (dma:DMR_05740, dma:DMR_34310) (dma:DMR_06660, dma:DMR_17770) (dma:DMR_06660, dma:DMR_19670) (dma:DMR_07470, dma:DMR_20060) (dma:DMR_09030, dma:DMR_11340) (dma:DMR_09030, dma:DMR_16990) (dma:DMR_09030, dma:DMR_25440) (dma:DMR_09030, dma:DMR_27000) (dma:DMR_10970, dma:DMR_11010) (dma:DMR_11340, dma:DMR_16990) (dma:DMR_11340, dma:DMR_25440) (dma:DMR_11340, dma:DMR_27000) (dma:DMR_13630, dma:DMR_17800) (dma:DMR_13630, dma:DMR_21660) (dma:DMR_14920, dma:DMR_39990) (dma:DMR_15980, dma:DMR_17880) (dma:DMR_16010, dma:DMR_28220) (dma:DMR_16990, dma:DMR_25440) (dma:DMR_16990, dma:DMR_27000) (dma:DMR_17120, dma:DMR_30710) (dma:DMR_17120, dma:DMR_37140) (dma:DMR_17130, dma:DMR_37080) (dma:DMR_17770, dma:DMR_19670) (dma:DMR_17800, dma:DMR_21660) (dma:DMR_18200, dma:DMR_37110) (dma:DMR_19210, dma:DMR_28790) (dma:DMR_19340, dma:DMR_39240) (dma:DMR_21220, dma:DMR_21290) (dma:DMR_21830, dma:DMR_34180) (dma:DMR_22790, dma:DMR_39960) (dma:DMR_23160, dma:DMR_30710) (dma:DMR_25440, dma:DMR_27000) (dma:DMR_28090, dma:DMR_35020) (dma:DMR_28090, dma:DMR_42440) (dma:DMR_30710, dma:DMR_37140) (dma:DMR_34740, dma:DMR_45930) (dma:DMR_35020, dma:DMR_37260) (dma:DMR_35020, dma:DMR_38720) (dma:DMR_35020, dma:DMR_42440) (dma:DMR_37260, dma:DMR_38720) (dma:DMR_37260, dma:DMR_42440) (dma:DMR_38720, dma:DMR_42440) (dma:DMR_39860, dma:DMR_44510) (dml:Dmul_00120, dml:Dmul_30910) (dml:Dmul_00400, dml:Dmul_34340) (dml:Dmul_00400, dml:Dmul_34350) (dml:Dmul_00440, dml:Dmul_11190) (dml:Dmul_00590, dml:Dmul_15560) (dml:Dmul_01560, dml:Dmul_16000) (dml:Dmul_01560, dml:Dmul_16810) (dml:Dmul_01640, dml:Dmul_38840) (dml:Dmul_01800, dml:Dmul_38840) (dml:Dmul_03450, dml:Dmul_25270) (dml:Dmul_03970, dml:Dmul_38190) (dml:Dmul_05580, dml:Dmul_15210) (dml:Dmul_05590, dml:Dmul_15200) (dml:Dmul_06060, dml:Dmul_07750) (dml:Dmul_06060, dml:Dmul_15350) (dml:Dmul_06060, dml:Dmul_26870) (dml:Dmul_07460, dml:Dmul_32700) (dml:Dmul_07490, dml:Dmul_09580) (dml:Dmul_07490, dml:Dmul_23280) (dml:Dmul_07490, dml:Dmul_24260) (dml:Dmul_07680, dml:Dmul_09400) (dml:Dmul_07750, dml:Dmul_15350) (dml:Dmul_07750, dml:Dmul_26870) (dml:Dmul_08540, dml:Dmul_19320) (dml:Dmul_08540, dml:Dmul_21830) (dml:Dmul_08540, dml:Dmul_23620) (dml:Dmul_08540, dml:Dmul_24630) (dml:Dmul_08540, dml:Dmul_28300) (dml:Dmul_08540, dml:Dmul_36880) (dml:Dmul_08800, dml:Dmul_27550) (dml:Dmul_08960, dml:Dmul_35620) (dml:Dmul_09580, dml:Dmul_23280) (dml:Dmul_09580, dml:Dmul_24260) (dml:Dmul_10150, dml:Dmul_22850) (dml:Dmul_11080, dml:Dmul_22990) (dml:Dmul_11080, dml:Dmul_23060) (dml:Dmul_12180, dml:Dmul_36330) (dml:Dmul_14330, dml:Dmul_22400) (dml:Dmul_14330, dml:Dmul_25380) (dml:Dmul_14360, dml:Dmul_34490) (dml:Dmul_14400, dml:Dmul_15600) (dml:Dmul_15350, dml:Dmul_26870) (dml:Dmul_15430, dml:Dmul_28400) (dml:Dmul_16000, dml:Dmul_16810) (dml:Dmul_16500, dml:Dmul_21160) (dml:Dmul_16810, dml:Dmul_22280) (dml:Dmul_18930, dml:Dmul_22850) (dml:Dmul_19320, dml:Dmul_21830) (dml:Dmul_19320, dml:Dmul_23620) (dml:Dmul_19320, dml:Dmul_24630) (dml:Dmul_19320, dml:Dmul_28300) (dml:Dmul_19320, dml:Dmul_36880) (dml:Dmul_19830, dml:Dmul_34880) (dml:Dmul_20530, dml:Dmul_22820) (dml:Dmul_20590, dml:Dmul_21250) (dml:Dmul_20590, dml:Dmul_38810) (dml:Dmul_20930, dml:Dmul_34830) (dml:Dmul_21170, dml:Dmul_38690) (dml:Dmul_21250, dml:Dmul_38810) (dml:Dmul_21290, dml:Dmul_32710) (dml:Dmul_21510, dml:Dmul_24950) (dml:Dmul_21510, dml:Dmul_28060) (dml:Dmul_21830, dml:Dmul_23620) (dml:Dmul_21830, dml:Dmul_24630) (dml:Dmul_21830, dml:Dmul_28300) (dml:Dmul_22810, dml:Dmul_24040) (dml:Dmul_22990, dml:Dmul_23060) (dml:Dmul_23530, dml:Dmul_23540) (dml:Dmul_23620, dml:Dmul_24630) (dml:Dmul_23620, dml:Dmul_28300) (dml:Dmul_23620, dml:Dmul_36880) (dml:Dmul_24630, dml:Dmul_28300) (dml:Dmul_24630, dml:Dmul_36880) (dml:Dmul_24950, dml:Dmul_28060) (dml:Dmul_24950, dml:Dmul_31480) (dml:Dmul_27020, dml:Dmul_31150) (dml:Dmul_27750, dml:Dmul_27780) (dml:Dmul_27800, dml:Dmul_27810) (dml:Dmul_28240, dml:Dmul_28270) (dml:Dmul_28300, dml:Dmul_36880) (dml:Dmul_31220, dml:Dmul_35200) (dml:Dmul_34340, dml:Dmul_34350) (doa:AXF15_00335, doa:AXF15_04820) (doa:AXF15_00575, doa:AXF15_02605) (doa:AXF15_00575, doa:AXF15_06215) (doa:AXF15_00690, doa:AXF15_04310) (doa:AXF15_00690, doa:AXF15_09000) (doa:AXF15_00690, doa:AXF15_10595) (doa:AXF15_01445, doa:AXF15_04685) (doa:AXF15_01830, doa:AXF15_07630) (doa:AXF15_02145, doa:AXF15_05040) (doa:AXF15_02215, doa:AXF15_03465) (doa:AXF15_02215, doa:AXF15_08610) (doa:AXF15_02480, doa:AXF15_03010) (doa:AXF15_02605, doa:AXF15_06215) (doa:AXF15_03265, doa:AXF15_09390) (doa:AXF15_03265, doa:AXF15_09785) (doa:AXF15_03265, doa:AXF15_11375) (doa:AXF15_03650, doa:AXF15_04445) (doa:AXF15_03730, doa:AXF15_05165) (doa:AXF15_04035, doa:AXF15_06350) (doa:AXF15_04135, doa:AXF15_11000) (doa:AXF15_04135, doa:AXF15_11370) (doa:AXF15_04310, doa:AXF15_09000) (doa:AXF15_04310, doa:AXF15_10595) (doa:AXF15_04690, doa:AXF15_12135) (doa:AXF15_04965, doa:AXF15_04970) (doa:AXF15_05690, doa:AXF15_11880) (doa:AXF15_05735, doa:AXF15_11960) (doa:AXF15_05770, doa:AXF15_05775) (doa:AXF15_05770, doa:AXF15_07580) (doa:AXF15_05775, doa:AXF15_07580) (doa:AXF15_06240, doa:AXF15_06360) (doa:AXF15_06240, doa:AXF15_08785) (doa:AXF15_06360, doa:AXF15_08785) (doa:AXF15_06400, doa:AXF15_08605) (doa:AXF15_06400, doa:AXF15_11595) (doa:AXF15_07625, doa:AXF15_09515) (doa:AXF15_08605, doa:AXF15_11595) (doa:AXF15_08670, doa:AXF15_11865) (doa:AXF15_09000, doa:AXF15_10595) (doa:AXF15_09390, doa:AXF15_09785) (doa:AXF15_09390, doa:AXF15_11375) (doa:AXF15_09785, doa:AXF15_11375) (doa:AXF15_10405, doa:AXF15_11375) (doa:AXF15_11000, doa:AXF15_11370) (dol:Dole_0026, dol:Dole_1063) (dol:Dole_0063, dol:Dole_0202) (dol:Dole_0063, dol:Dole_0683) (dol:Dole_0063, dol:Dole_0684) (dol:Dole_0121, dol:Dole_1446) (dol:Dole_0122, dol:Dole_2113) (dol:Dole_0128, dol:Dole_0983) (dol:Dole_0128, dol:Dole_1881) (dol:Dole_0164, dol:Dole_0314) (dol:Dole_0164, dol:Dole_3006) (dol:Dole_0187, dol:Dole_2859) (dol:Dole_0202, dol:Dole_0683) (dol:Dole_0202, dol:Dole_0684) (dol:Dole_0222, dol:Dole_0500) (dol:Dole_0261, dol:Dole_1885) (dol:Dole_0314, dol:Dole_0337) (dol:Dole_0314, dol:Dole_3006) (dol:Dole_0337, dol:Dole_1973) (dol:Dole_0337, dol:Dole_1975) (dol:Dole_0337, dol:Dole_3006) (dol:Dole_0367, dol:Dole_1131) (dol:Dole_0514, dol:Dole_2492) (dol:Dole_0542, dol:Dole_3206) (dol:Dole_0559, dol:Dole_0838) (dol:Dole_0559, dol:Dole_2323) (dol:Dole_0582, dol:Dole_1800) (dol:Dole_0670, dol:Dole_2847) (dol:Dole_0679, dol:Dole_1545) (dol:Dole_0683, dol:Dole_0684) (dol:Dole_0756, dol:Dole_2243) (dol:Dole_0783, dol:Dole_2351) (dol:Dole_0838, dol:Dole_2323) (dol:Dole_0966, dol:Dole_2680) (dol:Dole_0983, dol:Dole_1881) (dol:Dole_0983, dol:Dole_2499) (dol:Dole_1002, dol:Dole_1013) (dol:Dole_1010, dol:Dole_1848) (dol:Dole_1010, dol:Dole_2324) (dol:Dole_1012, dol:Dole_1961) (dol:Dole_1021, dol:Dole_2616) (dol:Dole_1068, dol:Dole_1134) (dol:Dole_1107, dol:Dole_1462) (dol:Dole_1130, dol:Dole_1662) (dol:Dole_1132, dol:Dole_1545) (dol:Dole_1166, dol:Dole_1667) (dol:Dole_1191, dol:Dole_1729) (dol:Dole_1191, dol:Dole_2438) (dol:Dole_1326, dol:Dole_2037) (dol:Dole_1355, dol:Dole_2393) (dol:Dole_1426, dol:Dole_2749) (dol:Dole_1564, dol:Dole_2074) (dol:Dole_1608, dol:Dole_2084) (dol:Dole_1729, dol:Dole_2438) (dol:Dole_1848, dol:Dole_2324) (dol:Dole_1881, dol:Dole_2499) (dol:Dole_1908, dol:Dole_2219) (dol:Dole_1973, dol:Dole_1975) (dol:Dole_2040, dol:Dole_2041) (dol:Dole_2786, dol:Dole_2791) (dol:Dole_2791, dol:Dole_2792) (dpb:BABL1_gene_13, dpb:BABL1_gene_199) (dpb:BABL1_gene_13, dpb:BABL1_gene_858) (dpb:BABL1_gene_199, dpb:BABL1_gene_858) (dpb:BABL1_gene_330, dpb:BABL1_gene_705) (dpb:BABL1_gene_5, dpb:BABL1_gene_6) (dpb:BABL1_gene_545, dpb:BABL1_gene_809) (dpb:BABL1_gene_545, dpb:BABL1_gene_827) (dpb:BABL1_gene_545, dpb:BABL1_gene_980) (dpb:BABL1_gene_809, dpb:BABL1_gene_827) (dpb:BABL1_gene_809, dpb:BABL1_gene_980) (dpb:BABL1_gene_827, dpb:BABL1_gene_980) (dpg:DESPIGER_0283, dpg:DESPIGER_1297) (dpg:DESPIGER_0283, dpg:DESPIGER_1913) (dpg:DESPIGER_0323, dpg:DESPIGER_1250) (dpg:DESPIGER_0323, dpg:DESPIGER_1949) (dpg:DESPIGER_0326, dpg:DESPIGER_2419) (dpg:DESPIGER_0351, dpg:DESPIGER_0488) (dpg:DESPIGER_0493, dpg:DESPIGER_1352) (dpg:DESPIGER_0549, dpg:DESPIGER_0552) (dpg:DESPIGER_0549, dpg:DESPIGER_1482) (dpg:DESPIGER_0552, dpg:DESPIGER_0649) (dpg:DESPIGER_0552, dpg:DESPIGER_1482) (dpg:DESPIGER_0559, dpg:DESPIGER_1110) (dpg:DESPIGER_0559, dpg:DESPIGER_1638) (dpg:DESPIGER_0559, dpg:DESPIGER_1832) (dpg:DESPIGER_0649, dpg:DESPIGER_1482) (dpg:DESPIGER_0682, dpg:DESPIGER_2427) (dpg:DESPIGER_0694, dpg:DESPIGER_2441) (dpg:DESPIGER_0969, dpg:DESPIGER_1531) (dpg:DESPIGER_1072, dpg:DESPIGER_2402) (dpg:DESPIGER_1079, dpg:DESPIGER_1284) (dpg:DESPIGER_1079, dpg:DESPIGER_2129) (dpg:DESPIGER_1110, dpg:DESPIGER_1638) (dpg:DESPIGER_1110, dpg:DESPIGER_1832) (dpg:DESPIGER_1191, dpg:DESPIGER_1719) (dpg:DESPIGER_1250, dpg:DESPIGER_1949) (dpg:DESPIGER_1284, dpg:DESPIGER_2129) (dpg:DESPIGER_1297, dpg:DESPIGER_1913) (dpg:DESPIGER_1545, dpg:DESPIGER_1797) (dpg:DESPIGER_1552, dpg:DESPIGER_2055) (dpg:DESPIGER_1638, dpg:DESPIGER_1832) (dpg:DESPIGER_1704, dpg:DESPIGER_1830) (dpg:DESPIGER_1814, dpg:DESPIGER_1815) (dpg:DESPIGER_1840, dpg:DESPIGER_2071) (dpi:BN4_10025, dpi:BN4_10583) (dpi:BN4_10026, dpi:BN4_10584) (dpi:BN4_10112, dpi:BN4_10485) (dpi:BN4_10115, dpi:BN4_11407) (dpi:BN4_10127, dpi:BN4_12214) (dpi:BN4_10161, dpi:BN4_10320) (dpi:BN4_10161, dpi:BN4_11381) (dpi:BN4_10196, dpi:BN4_11977) (dpi:BN4_10242, dpi:BN4_20389) (dpi:BN4_10265, dpi:BN4_10725) (dpi:BN4_10278, dpi:BN4_11854) (dpi:BN4_10278, dpi:BN4_11857) (dpi:BN4_10320, dpi:BN4_11381) (dpi:BN4_10344, dpi:BN4_10871) (dpi:BN4_10344, dpi:BN4_11060) (dpi:BN4_10344, dpi:BN4_12231) (dpi:BN4_10368, dpi:BN4_10404) (dpi:BN4_10369, dpi:BN4_12300) (dpi:BN4_10393, dpi:BN4_11936) (dpi:BN4_10393, dpi:BN4_12812) (dpi:BN4_10396, dpi:BN4_11008) (dpi:BN4_10396, dpi:BN4_11230) (dpi:BN4_10420, dpi:BN4_10697) (dpi:BN4_10420, dpi:BN4_20024) (dpi:BN4_10458, dpi:BN4_11868) (dpi:BN4_10478, dpi:BN4_12061) (dpi:BN4_10697, dpi:BN4_20024) (dpi:BN4_10697, dpi:BN4_20088) (dpi:BN4_10871, dpi:BN4_11060) (dpi:BN4_10871, dpi:BN4_12231) (dpi:BN4_10876, dpi:BN4_10996) (dpi:BN4_10961, dpi:BN4_12643) (dpi:BN4_11008, dpi:BN4_11230) (dpi:BN4_11008, dpi:BN4_11826) (dpi:BN4_11060, dpi:BN4_12231) (dpi:BN4_11318, dpi:BN4_12469) (dpi:BN4_11318, dpi:BN4_20265) (dpi:BN4_11354, dpi:BN4_11717) (dpi:BN4_11368, dpi:BN4_11611) (dpi:BN4_11683, dpi:BN4_20324) (dpi:BN4_11854, dpi:BN4_11857) (dpi:BN4_11936, dpi:BN4_12812) (dpi:BN4_12054, dpi:BN4_12384) (dpi:BN4_12054, dpi:BN4_12584) (dpi:BN4_12054, dpi:BN4_12643) (dpi:BN4_12067, dpi:BN4_12189) (dpi:BN4_12067, dpi:BN4_12690) (dpi:BN4_12189, dpi:BN4_12690) (dpi:BN4_12384, dpi:BN4_12584) (dpi:BN4_12384, dpi:BN4_12643) (dpi:BN4_12531, dpi:BN4_12775) (dpi:BN4_12584, dpi:BN4_12643) (dpi:BN4_20024, dpi:BN4_20088) (dpi:BN4_20344, dpi:BN4_20419) (dpr:Despr_0075, dpr:Despr_0082) (dpr:Despr_0279, dpr:Despr_2958) (dpr:Despr_0281, dpr:Despr_0744) (dpr:Despr_0281, dpr:Despr_1504) (dpr:Despr_0314, dpr:Despr_1916) (dpr:Despr_0363, dpr:Despr_1373) (dpr:Despr_0386, dpr:Despr_1962) (dpr:Despr_0441, dpr:Despr_1394) (dpr:Despr_0441, dpr:Despr_2534) (dpr:Despr_0517, dpr:Despr_3156) (dpr:Despr_0555, dpr:Despr_2467) (dpr:Despr_0559, dpr:Despr_1674) (dpr:Despr_0574, dpr:Despr_0909) (dpr:Despr_0744, dpr:Despr_1504) (dpr:Despr_0827, dpr:Despr_2589) (dpr:Despr_0862, dpr:Despr_1050) (dpr:Despr_0910, dpr:Despr_2483) (dpr:Despr_0918, dpr:Despr_2776) (dpr:Despr_0929, dpr:Despr_3296) (dpr:Despr_1050, dpr:Despr_3168) (dpr:Despr_1394, dpr:Despr_2534) (dpr:Despr_1502, dpr:Despr_2672) (dpr:Despr_1528, dpr:Despr_2721) (dpr:Despr_1538, dpr:Despr_3102) (dpr:Despr_1538, dpr:Despr_3332) (dpr:Despr_1637, dpr:Despr_2003) (dpr:Despr_1637, dpr:Despr_2089) (dpr:Despr_1640, dpr:Despr_2189) (dpr:Despr_1640, dpr:Despr_2956) (dpr:Despr_1776, dpr:Despr_2311) (dpr:Despr_1832, dpr:Despr_2394) (dpr:Despr_1832, dpr:Despr_3037) (dpr:Despr_1881, dpr:Despr_1928) (dpr:Despr_1896, dpr:Despr_2908) (dpr:Despr_2003, dpr:Despr_2089) (dpr:Despr_2009, dpr:Despr_2670) (dpr:Despr_2011, dpr:Despr_2500) (dpr:Despr_2011, dpr:Despr_2665) (dpr:Despr_2042, dpr:Despr_2813) (dpr:Despr_2042, dpr:Despr_2865) (dpr:Despr_2042, dpr:Despr_2867) (dpr:Despr_2042, dpr:Despr_2873) (dpr:Despr_2092, dpr:Despr_2093) (dpr:Despr_2189, dpr:Despr_2956) (dpr:Despr_2283, dpr:Despr_3183) (dpr:Despr_2289, dpr:Despr_2324) (dpr:Despr_2346, dpr:Despr_2376) (dpr:Despr_2394, dpr:Despr_3037) (dpr:Despr_2813, dpr:Despr_2865) (dpr:Despr_2813, dpr:Despr_2867) (dpr:Despr_2813, dpr:Despr_2873) (dpr:Despr_2865, dpr:Despr_2867) (dpr:Despr_2865, dpr:Despr_2873) (dpr:Despr_2867, dpr:Despr_2873) (dpr:Despr_2977, dpr:Despr_3152) (dpr:Despr_2980, dpr:Despr_3256) (dpr:Despr_2989, dpr:Despr_3183) (dpr:Despr_3102, dpr:Despr_3332) (dpr:Despr_3168, dpr:Despr_3306) (dps:DP0014, dps:DPPB70) (dps:DP0022, dps:DPPB68) (dps:DP0026, dps:DP1007) (dps:DP0026, dps:DPPB64) (dps:DP0044, dps:DP2221) (dps:DP0045, dps:DP2220) (dps:DP0045, dps:DP2716) (dps:DP0059, dps:DP1022) (dps:DP0067, dps:DP0555) (dps:DP0067, dps:DP1333) (dps:DP0103, dps:DP0822) (dps:DP0106, dps:DP0437) (dps:DP0394, dps:DP1088) (dps:DP0475, dps:DP2376) (dps:DP0540, dps:DP0544) (dps:DP0555, dps:DP1333) (dps:DP0555, dps:DP2097) (dps:DP0555, dps:DPPB37) (dps:DP0660, dps:DP2768) (dps:DP0784, dps:DP1431) (dps:DP0812, dps:DP2548) (dps:DP0825, dps:DP2097) (dps:DP0825, dps:DPPB37) (dps:DP0950, dps:DP0951) (dps:DP0950, dps:DP0952) (dps:DP0950, dps:DP0955) (dps:DP0951, dps:DP0952) (dps:DP0951, dps:DP0955) (dps:DP0952, dps:DP0955) (dps:DP1007, dps:DPPB64) (dps:DP1165, dps:DP1905) (dps:DP1266, dps:DP1272) (dps:DP1331, dps:DP1629) (dps:DP1472, dps:DP2110) (dps:DP1631, dps:DP2949) (dps:DP1796, dps:DP2552) (dps:DP1796, dps:DP2600) (dps:DP1847, dps:DP2407) (dps:DP1847, dps:DP2790) (dps:DP1859, dps:DP2403) (dps:DP1859, dps:DP2788) (dps:DP2097, dps:DPPB37) (dps:DP2172, dps:DP2991) (dps:DP2220, dps:DP2716) (dps:DP2403, dps:DP2788) (dps:DP2407, dps:DP2790) (dps:DP2474, dps:DP2475) (dps:DP2474, dps:DP2990) (dps:DP2475, dps:DP2990) (dps:DP2552, dps:DP2600) (drt:Dret_0011, drt:Dret_2110) (drt:Dret_0014, drt:Dret_2234) (drt:Dret_0042, drt:Dret_1756) (drt:Dret_0079, drt:Dret_2027) (drt:Dret_0124, drt:Dret_0798) (drt:Dret_0143, drt:Dret_0321) (drt:Dret_0199, drt:Dret_0202) (drt:Dret_0251, drt:Dret_1118) (drt:Dret_0251, drt:Dret_1425) (drt:Dret_0307, drt:Dret_2499) (drt:Dret_0340, drt:Dret_1397) (drt:Dret_0439, drt:Dret_1100) (drt:Dret_0460, drt:Dret_1139) (drt:Dret_0460, drt:Dret_2408) (drt:Dret_0460, drt:Dret_2432) (drt:Dret_0505, drt:Dret_1107) (drt:Dret_0537, drt:Dret_0830) (drt:Dret_0542, drt:Dret_0772) (drt:Dret_0542, drt:Dret_1907) (drt:Dret_0704, drt:Dret_1010) (drt:Dret_0730, drt:Dret_2103) (drt:Dret_0772, drt:Dret_1907) (drt:Dret_0818, drt:Dret_1756) (drt:Dret_0818, drt:Dret_2132) (drt:Dret_0818, drt:Dret_2481) (drt:Dret_0830, drt:Dret_1385) (drt:Dret_1046, drt:Dret_2421) (drt:Dret_1118, drt:Dret_1425) (drt:Dret_1139, drt:Dret_2408) (drt:Dret_1139, drt:Dret_2432) (drt:Dret_1384, drt:Dret_1409) (drt:Dret_1459, drt:Dret_1706) (drt:Dret_1756, drt:Dret_2132) (drt:Dret_1756, drt:Dret_2481) (drt:Dret_1968, drt:Dret_2034) (drt:Dret_2102, drt:Dret_2429) (drt:Dret_2132, drt:Dret_2481) (drt:Dret_2408, drt:Dret_2432) (dsa:Desal_0017, dsa:Desal_1784) (dsa:Desal_0041, dsa:Desal_0990) (dsa:Desal_0041, dsa:Desal_2027) (dsa:Desal_0041, dsa:Desal_2493) (dsa:Desal_0092, dsa:Desal_0152) (dsa:Desal_0092, dsa:Desal_0743) (dsa:Desal_0092, dsa:Desal_2829) (dsa:Desal_0136, dsa:Desal_2862) (dsa:Desal_0143, dsa:Desal_2527) (dsa:Desal_0152, dsa:Desal_0743) (dsa:Desal_0152, dsa:Desal_2829) (dsa:Desal_0178, dsa:Desal_3407) (dsa:Desal_0250, dsa:Desal_0650) (dsa:Desal_0250, dsa:Desal_2004) (dsa:Desal_0284, dsa:Desal_0289) (dsa:Desal_0284, dsa:Desal_1318) (dsa:Desal_0289, dsa:Desal_1318) (dsa:Desal_0368, dsa:Desal_1338) (dsa:Desal_0408, dsa:Desal_1363) (dsa:Desal_0408, dsa:Desal_1745) (dsa:Desal_0408, dsa:Desal_1818) (dsa:Desal_0408, dsa:Desal_3739) (dsa:Desal_0523, dsa:Desal_0538) (dsa:Desal_0523, dsa:Desal_0658) (dsa:Desal_0538, dsa:Desal_0658) (dsa:Desal_0541, dsa:Desal_0576) (dsa:Desal_0541, dsa:Desal_0660) (dsa:Desal_0558, dsa:Desal_0574) (dsa:Desal_0558, dsa:Desal_0740) (dsa:Desal_0559, dsa:Desal_0575) (dsa:Desal_0559, dsa:Desal_3668) (dsa:Desal_0574, dsa:Desal_0740) (dsa:Desal_0575, dsa:Desal_3668) (dsa:Desal_0576, dsa:Desal_0660) (dsa:Desal_0616, dsa:Desal_3305) (dsa:Desal_0650, dsa:Desal_2004) (dsa:Desal_0657, dsa:Desal_1305) (dsa:Desal_0661, dsa:Desal_3652) (dsa:Desal_0743, dsa:Desal_2464) (dsa:Desal_0743, dsa:Desal_2829) (dsa:Desal_0753, dsa:Desal_2978) (dsa:Desal_0836, dsa:Desal_0837) (dsa:Desal_0990, dsa:Desal_2027) (dsa:Desal_0990, dsa:Desal_2493) (dsa:Desal_1082, dsa:Desal_3603) (dsa:Desal_1093, dsa:Desal_1585) (dsa:Desal_1102, dsa:Desal_2208) (dsa:Desal_1102, dsa:Desal_2266) (dsa:Desal_1363, dsa:Desal_1745) (dsa:Desal_1363, dsa:Desal_1818) (dsa:Desal_1363, dsa:Desal_3739) (dsa:Desal_1479, dsa:Desal_2397) (dsa:Desal_1582, dsa:Desal_1998) (dsa:Desal_1628, dsa:Desal_2872) (dsa:Desal_1628, dsa:Desal_3397) (dsa:Desal_1645, dsa:Desal_2033) (dsa:Desal_1645, dsa:Desal_3834) (dsa:Desal_1745, dsa:Desal_1818) (dsa:Desal_1745, dsa:Desal_3739) (dsa:Desal_1769, dsa:Desal_2398) (dsa:Desal_1818, dsa:Desal_3739) (dsa:Desal_1910, dsa:Desal_3742) (dsa:Desal_2027, dsa:Desal_2493) (dsa:Desal_2033, dsa:Desal_2682) (dsa:Desal_2033, dsa:Desal_3834) (dsa:Desal_2037, dsa:Desal_2198) (dsa:Desal_2170, dsa:Desal_3566) (dsa:Desal_2198, dsa:Desal_2676) (dsa:Desal_2302, dsa:Desal_2437) (dsa:Desal_2682, dsa:Desal_3834) (dsa:Desal_2806, dsa:Desal_3025) (dsa:Desal_2862, dsa:Desal_3356) (dsa:Desal_2872, dsa:Desal_3397) (dsa:Desal_2997, dsa:Desal_3027) (dsa:Desal_3010, dsa:Desal_3055) (dsa:Desal_3303, dsa:Desal_3402) (dsa:Desal_3407, dsa:Desal_3772) (dsf:UWK_00066, dsf:UWK_03051) (dsf:UWK_00067, dsf:UWK_03052) (dsf:UWK_00087, dsf:UWK_00094) (dsf:UWK_00105, dsf:UWK_01819) (dsf:UWK_00122, dsf:UWK_00143) (dsf:UWK_00122, dsf:UWK_00144) (dsf:UWK_00122, dsf:UWK_02571) (dsf:UWK_00122, dsf:UWK_02973) (dsf:UWK_00132, dsf:UWK_02569) (dsf:UWK_00132, dsf:UWK_02977) (dsf:UWK_00143, dsf:UWK_00144) (dsf:UWK_00143, dsf:UWK_02571) (dsf:UWK_00143, dsf:UWK_02973) (dsf:UWK_00144, dsf:UWK_02571) (dsf:UWK_00144, dsf:UWK_02973) (dsf:UWK_00180, dsf:UWK_02799) (dsf:UWK_00180, dsf:UWK_03410) (dsf:UWK_00304, dsf:UWK_00318) (dsf:UWK_00304, dsf:UWK_00709) (dsf:UWK_00316, dsf:UWK_03294) (dsf:UWK_00318, dsf:UWK_00709) (dsf:UWK_00454, dsf:UWK_02742) (dsf:UWK_00579, dsf:UWK_01937) (dsf:UWK_00627, dsf:UWK_02355) (dsf:UWK_00627, dsf:UWK_02650) (dsf:UWK_00683, dsf:UWK_00793) (dsf:UWK_00704, dsf:UWK_00709) (dsf:UWK_00789, dsf:UWK_01687) (dsf:UWK_00827, dsf:UWK_02784) (dsf:UWK_00846, dsf:UWK_01435) (dsf:UWK_00965, dsf:UWK_02667) (dsf:UWK_00991, dsf:UWK_02122) (dsf:UWK_00991, dsf:UWK_03294) (dsf:UWK_01050, dsf:UWK_01840) (dsf:UWK_01152, dsf:UWK_03535) (dsf:UWK_01260, dsf:UWK_03510) (dsf:UWK_01351, dsf:UWK_01777) (dsf:UWK_01351, dsf:UWK_01801) (dsf:UWK_01372, dsf:UWK_01373) (dsf:UWK_01373, dsf:UWK_01758) (dsf:UWK_01482, dsf:UWK_01685) (dsf:UWK_01506, dsf:UWK_02745) (dsf:UWK_01617, dsf:UWK_03336) (dsf:UWK_01660, dsf:UWK_02972) (dsf:UWK_01662, dsf:UWK_03406) (dsf:UWK_01777, dsf:UWK_01801) (dsf:UWK_01819, dsf:UWK_02241) (dsf:UWK_01838, dsf:UWK_02522) (dsf:UWK_01915, dsf:UWK_02087) (dsf:UWK_01920, dsf:UWK_02430) (dsf:UWK_01920, dsf:UWK_02594) (dsf:UWK_02316, dsf:UWK_02927) (dsf:UWK_02323, dsf:UWK_02569) (dsf:UWK_02355, dsf:UWK_02650) (dsf:UWK_02372, dsf:UWK_02435) (dsf:UWK_02372, dsf:UWK_03174) (dsf:UWK_02430, dsf:UWK_02594) (dsf:UWK_02435, dsf:UWK_03174) (dsf:UWK_02496, dsf:UWK_03539) (dsf:UWK_02513, dsf:UWK_03421) (dsf:UWK_02514, dsf:UWK_02797) (dsf:UWK_02569, dsf:UWK_02977) (dsf:UWK_02571, dsf:UWK_02973) (dsf:UWK_02595, dsf:UWK_02885) (dsf:UWK_02799, dsf:UWK_03410) (dsf:UWK_03000, dsf:UWK_03057) (dsf:UWK_03329, dsf:UWK_03366) (dti:Desti_0036, dti:Desti_2232) (dti:Desti_0036, dti:Desti_5358) (dti:Desti_0051, dti:Desti_4903) (dti:Desti_0057, dti:Desti_0426) (dti:Desti_0059, dti:Desti_2327) (dti:Desti_0059, dti:Desti_4020) (dti:Desti_0062, dti:Desti_3199) (dti:Desti_0148, dti:Desti_1492) (dti:Desti_0149, dti:Desti_2111) (dti:Desti_0149, dti:Desti_3139) (dti:Desti_0205, dti:Desti_1014) (dti:Desti_0205, dti:Desti_3300) (dti:Desti_0219, dti:Desti_0353) (dti:Desti_0219, dti:Desti_0901) (dti:Desti_0219, dti:Desti_1366) (dti:Desti_0219, dti:Desti_1457) (dti:Desti_0219, dti:Desti_1808) (dti:Desti_0219, dti:Desti_2003) (dti:Desti_0219, dti:Desti_2341) (dti:Desti_0219, dti:Desti_2345) (dti:Desti_0219, dti:Desti_2348) (dti:Desti_0219, dti:Desti_2479) (dti:Desti_0219, dti:Desti_2797) (dti:Desti_0219, dti:Desti_3164) (dti:Desti_0219, dti:Desti_3693) (dti:Desti_0219, dti:Desti_4164) (dti:Desti_0219, dti:Desti_4337) (dti:Desti_0219, dti:Desti_4907) (dti:Desti_0225, dti:Desti_2739) (dti:Desti_0225, dti:Desti_2740) (dti:Desti_0234, dti:Desti_1206) (dti:Desti_0234, dti:Desti_2998) (dti:Desti_0240, dti:Desti_0755) (dti:Desti_0240, dti:Desti_1340) (dti:Desti_0353, dti:Desti_0901) (dti:Desti_0353, dti:Desti_1366) (dti:Desti_0353, dti:Desti_1457) (dti:Desti_0353, dti:Desti_1808) (dti:Desti_0353, dti:Desti_2003) (dti:Desti_0353, dti:Desti_2345) (dti:Desti_0353, dti:Desti_2348) (dti:Desti_0353, dti:Desti_2479) (dti:Desti_0353, dti:Desti_2797) (dti:Desti_0353, dti:Desti_2892) (dti:Desti_0353, dti:Desti_3164) (dti:Desti_0353, dti:Desti_3693) (dti:Desti_0353, dti:Desti_4164) (dti:Desti_0353, dti:Desti_4337) (dti:Desti_0353, dti:Desti_4907) (dti:Desti_0395, dti:Desti_0830) (dti:Desti_0395, dti:Desti_1171) (dti:Desti_0441, dti:Desti_0981) (dti:Desti_0441, dti:Desti_2096) (dti:Desti_0441, dti:Desti_4769) (dti:Desti_0441, dti:Desti_5499) (dti:Desti_0473, dti:Desti_2739) (dti:Desti_0504, dti:Desti_4345) (dti:Desti_0569, dti:Desti_0774) (dti:Desti_0569, dti:Desti_1836) (dti:Desti_0569, dti:Desti_4547) (dti:Desti_0569, dti:Desti_4995) (dti:Desti_0754, dti:Desti_4149) (dti:Desti_0755, dti:Desti_1340) (dti:Desti_0757, dti:Desti_4402) (dti:Desti_0757, dti:Desti_5563) (dti:Desti_0759, dti:Desti_1036) (dti:Desti_0759, dti:Desti_2825) (dti:Desti_0759, dti:Desti_3101) (dti:Desti_0774, dti:Desti_0925) (dti:Desti_0774, dti:Desti_0942) (dti:Desti_0774, dti:Desti_4572) (dti:Desti_0802, dti:Desti_2957) (dti:Desti_0830, dti:Desti_1171) (dti:Desti_0874, dti:Desti_1662) (dti:Desti_0874, dti:Desti_2134) (dti:Desti_0874, dti:Desti_4384) (dti:Desti_0874, dti:Desti_5141) (dti:Desti_0881, dti:Desti_0896) (dti:Desti_0881, dti:Desti_2278) (dti:Desti_0881, dti:Desti_2371) (dti:Desti_0881, dti:Desti_3356) (dti:Desti_0896, dti:Desti_2278) (dti:Desti_0896, dti:Desti_2371) (dti:Desti_0901, dti:Desti_1366) (dti:Desti_0901, dti:Desti_1457) (dti:Desti_0901, dti:Desti_1808) (dti:Desti_0901, dti:Desti_2003) (dti:Desti_0901, dti:Desti_2341) (dti:Desti_0901, dti:Desti_2345) (dti:Desti_0901, dti:Desti_2348) (dti:Desti_0901, dti:Desti_2479) (dti:Desti_0901, dti:Desti_2797) (dti:Desti_0901, dti:Desti_3164) (dti:Desti_0901, dti:Desti_4164) (dti:Desti_0901, dti:Desti_4907) (dti:Desti_0925, dti:Desti_0942) (dti:Desti_0925, dti:Desti_4572) (dti:Desti_0927, dti:Desti_1600) (dti:Desti_0927, dti:Desti_2811) (dti:Desti_0927, dti:Desti_3611) (dti:Desti_0942, dti:Desti_4572) (dti:Desti_0981, dti:Desti_2096) (dti:Desti_0981, dti:Desti_4769) (dti:Desti_0981, dti:Desti_5499) (dti:Desti_0988, dti:Desti_4113) (dti:Desti_1014, dti:Desti_3300) (dti:Desti_1036, dti:Desti_2825) (dti:Desti_1036, dti:Desti_3101) (dti:Desti_1039, dti:Desti_2110) (dti:Desti_1152, dti:Desti_3121) (dti:Desti_1190, dti:Desti_3729) (dti:Desti_1200, dti:Desti_1201) (dti:Desti_1200, dti:Desti_1674) (dti:Desti_1200, dti:Desti_4911) (dti:Desti_1201, dti:Desti_1674) (dti:Desti_1201, dti:Desti_4911) (dti:Desti_1206, dti:Desti_2998) (dti:Desti_1259, dti:Desti_3121) (dti:Desti_1266, dti:Desti_4116) (dti:Desti_1366, dti:Desti_1457) (dti:Desti_1366, dti:Desti_1808) (dti:Desti_1366, dti:Desti_2003) (dti:Desti_1366, dti:Desti_2479) (dti:Desti_1366, dti:Desti_2797) (dti:Desti_1366, dti:Desti_2892) (dti:Desti_1366, dti:Desti_3164) (dti:Desti_1366, dti:Desti_3693) (dti:Desti_1366, dti:Desti_4337) (dti:Desti_1366, dti:Desti_4907) (dti:Desti_1457, dti:Desti_1808) (dti:Desti_1457, dti:Desti_2003) (dti:Desti_1457, dti:Desti_2341) (dti:Desti_1457, dti:Desti_2345) (dti:Desti_1457, dti:Desti_2348) (dti:Desti_1457, dti:Desti_2479) (dti:Desti_1457, dti:Desti_2797) (dti:Desti_1457, dti:Desti_3164) (dti:Desti_1457, dti:Desti_3693) (dti:Desti_1457, dti:Desti_4164) (dti:Desti_1457, dti:Desti_4337) (dti:Desti_1457, dti:Desti_4907) (dti:Desti_1600, dti:Desti_2811) (dti:Desti_1600, dti:Desti_3611) (dti:Desti_1662, dti:Desti_2134) (dti:Desti_1662, dti:Desti_4384) (dti:Desti_1662, dti:Desti_5141) (dti:Desti_1674, dti:Desti_4911) (dti:Desti_1695, dti:Desti_3108) (dti:Desti_1700, dti:Desti_4704) (dti:Desti_1700, dti:Desti_4705) (dti:Desti_1808, dti:Desti_2003) (dti:Desti_1808, dti:Desti_2345) (dti:Desti_1808, dti:Desti_2348) (dti:Desti_1808, dti:Desti_2479) (dti:Desti_1808, dti:Desti_2797) (dti:Desti_1808, dti:Desti_2892) (dti:Desti_1808, dti:Desti_3164) (dti:Desti_1808, dti:Desti_3693) (dti:Desti_1808, dti:Desti_4164) (dti:Desti_1808, dti:Desti_4337) (dti:Desti_1808, dti:Desti_4907) (dti:Desti_1836, dti:Desti_4547) (dti:Desti_1836, dti:Desti_4995) (dti:Desti_1892, dti:Desti_5539) (dti:Desti_2003, dti:Desti_2341) (dti:Desti_2003, dti:Desti_2345) (dti:Desti_2003, dti:Desti_2348) (dti:Desti_2003, dti:Desti_2479) (dti:Desti_2003, dti:Desti_2797) (dti:Desti_2003, dti:Desti_2892) (dti:Desti_2003, dti:Desti_3164) (dti:Desti_2003, dti:Desti_3693) (dti:Desti_2003, dti:Desti_4164) (dti:Desti_2003, dti:Desti_4337) (dti:Desti_2003, dti:Desti_4907) (dti:Desti_2096, dti:Desti_4769) (dti:Desti_2096, dti:Desti_5499) (dti:Desti_2111, dti:Desti_3139) (dti:Desti_2134, dti:Desti_4384) (dti:Desti_2134, dti:Desti_5141) (dti:Desti_2232, dti:Desti_5358) (dti:Desti_2278, dti:Desti_2371) (dti:Desti_2278, dti:Desti_3356) (dti:Desti_2327, dti:Desti_4020) (dti:Desti_2341, dti:Desti_2345) (dti:Desti_2341, dti:Desti_2348) (dti:Desti_2341, dti:Desti_2479) (dti:Desti_2341, dti:Desti_2797) (dti:Desti_2341, dti:Desti_3164) (dti:Desti_2341, dti:Desti_4164) (dti:Desti_2341, dti:Desti_4907) (dti:Desti_2345, dti:Desti_2348) (dti:Desti_2345, dti:Desti_2479) (dti:Desti_2345, dti:Desti_2797) (dti:Desti_2345, dti:Desti_3164) (dti:Desti_2345, dti:Desti_4164) (dti:Desti_2345, dti:Desti_4907) (dti:Desti_2348, dti:Desti_2479) (dti:Desti_2348, dti:Desti_2797) (dti:Desti_2348, dti:Desti_3164) (dti:Desti_2348, dti:Desti_4164) (dti:Desti_2348, dti:Desti_4907) (dti:Desti_2371, dti:Desti_3356) (dti:Desti_2479, dti:Desti_2797) (dti:Desti_2479, dti:Desti_2892) (dti:Desti_2479, dti:Desti_3164) (dti:Desti_2479, dti:Desti_3693) (dti:Desti_2479, dti:Desti_4164) (dti:Desti_2479, dti:Desti_4337) (dti:Desti_2479, dti:Desti_4907) (dti:Desti_2554, dti:Desti_4464) (dti:Desti_2576, dti:Desti_5667) (dti:Desti_2718, dti:Desti_5320) (dti:Desti_2739, dti:Desti_2740) (dti:Desti_2768, dti:Desti_2856) (dti:Desti_2768, dti:Desti_4587) (dti:Desti_2797, dti:Desti_3164) (dti:Desti_2797, dti:Desti_3693) (dti:Desti_2797, dti:Desti_4164) (dti:Desti_2797, dti:Desti_4337) (dti:Desti_2797, dti:Desti_4907) (dti:Desti_2811, dti:Desti_3611) (dti:Desti_2825, dti:Desti_3101) (dti:Desti_2856, dti:Desti_4587) (dti:Desti_2892, dti:Desti_3693) (dti:Desti_2892, dti:Desti_4337) (dti:Desti_2892, dti:Desti_4907) (dti:Desti_2988, dti:Desti_4182) (dti:Desti_2988, dti:Desti_4732) (dti:Desti_3051, dti:Desti_3628) (dti:Desti_3164, dti:Desti_4164) (dti:Desti_3164, dti:Desti_4907) (dti:Desti_3578, dti:Desti_3894) (dti:Desti_3650, dti:Desti_3747) (dti:Desti_3684, dti:Desti_3834) (dti:Desti_3684, dti:Desti_4083) (dti:Desti_3693, dti:Desti_4337) (dti:Desti_3693, dti:Desti_4907) (dti:Desti_3834, dti:Desti_4083) (dti:Desti_4150, dti:Desti_4253) (dti:Desti_4164, dti:Desti_4907) (dti:Desti_4182, dti:Desti_4732) (dti:Desti_4337, dti:Desti_4907) (dti:Desti_4384, dti:Desti_5141) (dti:Desti_4402, dti:Desti_5563) (dti:Desti_4450, dti:Desti_4868) (dti:Desti_4547, dti:Desti_4995) (dti:Desti_4769, dti:Desti_5499) (dto:TOL2_C00330, dto:TOL2_C15960) (dto:TOL2_C00560, dto:TOL2_C39750) (dto:TOL2_C02640, dto:TOL2_C13310) (dto:TOL2_C03020, dto:TOL2_C03030) (dto:TOL2_C03020, dto:TOL2_C41730) (dto:TOL2_C03020, dto:TOL2_C43490) (dto:TOL2_C03020, dto:TOL2_C43570) (dto:TOL2_C03030, dto:TOL2_C41730) (dto:TOL2_C03030, dto:TOL2_C43490) (dto:TOL2_C03030, dto:TOL2_C43570) (dto:TOL2_C03360, dto:TOL2_C41270) (dto:TOL2_C03820, dto:TOL2_C04490) (dto:TOL2_C03820, dto:TOL2_C38530) (dto:TOL2_C04170, dto:TOL2_C15960) (dto:TOL2_C05070, dto:TOL2_C28470) (dto:TOL2_C05080, dto:TOL2_C28480) (dto:TOL2_C05120, dto:TOL2_C29790) (dto:TOL2_C05220, dto:TOL2_C26900) (dto:TOL2_C05220, dto:TOL2_C27090) (dto:TOL2_C05220, dto:TOL2_C27260) (dto:TOL2_C05220, dto:TOL2_C27460) (dto:TOL2_C05220, dto:TOL2_C27650) (dto:TOL2_C05220, dto:TOL2_C31520) (dto:TOL2_C05220, dto:TOL2_C37120) (dto:TOL2_C05370, dto:TOL2_C22520) (dto:TOL2_C07190, dto:TOL2_C16630) (dto:TOL2_C08210, dto:TOL2_C12360) (dto:TOL2_C08210, dto:TOL2_C23400) (dto:TOL2_C08210, dto:TOL2_C35200) (dto:TOL2_C08210, dto:TOL2_C35290) (dto:TOL2_C08510, dto:TOL2_C33600) (dto:TOL2_C10040, dto:TOL2_C42990) (dto:TOL2_C10990, dto:TOL2_C13310) (dto:TOL2_C11340, dto:TOL2_C22880) (dto:TOL2_C11440, dto:TOL2_C39790) (dto:TOL2_C12360, dto:TOL2_C23400) (dto:TOL2_C12360, dto:TOL2_C35200) (dto:TOL2_C12360, dto:TOL2_C35290) (dto:TOL2_C13270, dto:TOL2_C13420) (dto:TOL2_C15720, dto:TOL2_C42790) (dto:TOL2_C16510, dto:TOL2_C21050) (dto:TOL2_C16510, dto:TOL2_C22640) (dto:TOL2_C16630, dto:TOL2_C16640) (dto:TOL2_C17330, dto:TOL2_C38950) (dto:TOL2_C17500, dto:TOL2_C18400) (dto:TOL2_C18190, dto:TOL2_C18860) (dto:TOL2_C21050, dto:TOL2_C22640) (dto:TOL2_C21920, dto:TOL2_C24560) (dto:TOL2_C22060, dto:TOL2_C39980) (dto:TOL2_C23200, dto:TOL2_C35960) (dto:TOL2_C23400, dto:TOL2_C35200) (dto:TOL2_C23400, dto:TOL2_C35290) (dto:TOL2_C24750, dto:TOL2_C24800) (dto:TOL2_C26900, dto:TOL2_C27090) (dto:TOL2_C26900, dto:TOL2_C27260) (dto:TOL2_C26900, dto:TOL2_C27460) (dto:TOL2_C26900, dto:TOL2_C27650) (dto:TOL2_C26900, dto:TOL2_C37120) (dto:TOL2_C26900, dto:TOL2_C38520) (dto:TOL2_C27090, dto:TOL2_C27260) (dto:TOL2_C27090, dto:TOL2_C27460) (dto:TOL2_C27090, dto:TOL2_C27650) (dto:TOL2_C27090, dto:TOL2_C37120) (dto:TOL2_C27090, dto:TOL2_C38520) (dto:TOL2_C27260, dto:TOL2_C27460) (dto:TOL2_C27260, dto:TOL2_C27650) (dto:TOL2_C27260, dto:TOL2_C37120) (dto:TOL2_C27260, dto:TOL2_C38520) (dto:TOL2_C27460, dto:TOL2_C27650) (dto:TOL2_C27460, dto:TOL2_C37120) (dto:TOL2_C27460, dto:TOL2_C38520) (dto:TOL2_C27650, dto:TOL2_C37120) (dto:TOL2_C27650, dto:TOL2_C38520) (dto:TOL2_C28080, dto:TOL2_C28120) (dto:TOL2_C31520, dto:TOL2_C37120) (dto:TOL2_C35200, dto:TOL2_C35290) (dto:TOL2_C36220, dto:TOL2_C43000) (dto:TOL2_C38340, dto:TOL2_C38550) (dto:TOL2_C41730, dto:TOL2_C43490) (dto:TOL2_C41730, dto:TOL2_C43570) (dto:TOL2_C43490, dto:TOL2_C43570) (dvu:DVU0085, dvu:DVU0470) (dvu:DVU0152, dvu:DVU0246) (dvu:DVU0152, dvu:DVU1833) (dvu:DVU0152, dvu:DVU2739) (dvu:DVU0152, dvu:DVU3214) (dvu:DVU0152, dvu:DVU3237) (dvu:DVU0246, dvu:DVU2739) (dvu:DVU0246, dvu:DVU3214) (dvu:DVU0246, dvu:DVU3237) (dvu:DVU0283, dvu:DVU0377) (dvu:DVU0283, dvu:DVU1457) (dvu:DVU0283, dvu:DVU1838) (dvu:DVU0341, dvu:DVU3114) (dvu:DVU0360, dvu:DVU1376) (dvu:DVU0360, dvu:DVU3293) (dvu:DVU0377, dvu:DVU1838) (dvu:DVU0477, dvu:DVU2985) (dvu:DVU0489, dvu:DVU1615) (dvu:DVU0489, dvu:DVU2735) (dvu:DVU0489, dvu:DVU3253) (dvu:DVU0565, dvu:DVU2144) (dvu:DVU0626, dvu:DVU1377) (dvu:DVU0732, dvu:DVU1196) (dvu:DVU0732, dvu:DVU1927) (dvu:DVU0748, dvu:DVU1453) (dvu:DVU0748, dvu:DVU2250) (dvu:DVU0748, dvu:DVU2969) (dvu:DVU0827, dvu:DVU3027) (dvu:DVU0841, dvu:DVU3223) (dvu:DVU0951, dvu:DVU2990) (dvu:DVU1196, dvu:DVU1927) (dvu:DVU1204, dvu:DVU2563) (dvu:DVU1206, dvu:DVU3137) (dvu:DVU1350, dvu:DVU2530) (dvu:DVU1360, dvu:DVU1364) (dvu:DVU1360, dvu:DVU2996) (dvu:DVU1360, dvu:DVU3356) (dvu:DVU1364, dvu:DVU3356) (dvu:DVU1376, dvu:DVU3293) (dvu:DVU1453, dvu:DVU2250) (dvu:DVU1453, dvu:DVU2969) (dvu:DVU1453, dvu:DVU3119) (dvu:DVU1457, dvu:DVU1838) (dvu:DVU1615, dvu:DVU2735) (dvu:DVU1615, dvu:DVU3253) (dvu:DVU1647, dvu:DVU2566) (dvu:DVU1693, dvu:DVU2552) (dvu:DVU1833, dvu:DVU2739) (dvu:DVU1833, dvu:DVU3214) (dvu:DVU1914, dvu:DVU2981) (dvu:DVU1940, dvu:DVU2673) (dvu:DVU1940, dvu:DVU3132) (dvu:DVU2091, dvu:DVU2362) (dvu:DVU2250, dvu:DVU2969) (dvu:DVU2396, dvu:DVU2405) (dvu:DVU2396, dvu:DVU2885) (dvu:DVU2396, dvu:DVU2905) (dvu:DVU2405, dvu:DVU2885) (dvu:DVU2405, dvu:DVU2905) (dvu:DVU2559, dvu:DVU3168) (dvu:DVU2673, dvu:DVU3132) (dvu:DVU2735, dvu:DVU3253) (dvu:DVU2739, dvu:DVU3214) (dvu:DVU2739, dvu:DVU3237) (dvu:DVU2885, dvu:DVU2905) (dvu:DVU2969, dvu:DVU3119) (dvu:DVU3014, dvu:DVUA0073) (dvu:DVU3214, dvu:DVU3237) (gao:A2G06_01250, gao:A2G06_08995) (gao:A2G06_02140, gao:A2G06_08985) (gao:A2G06_03585, gao:A2G06_08130) (gao:A2G06_03585, gao:A2G06_13760) (gao:A2G06_05615, gao:A2G06_05630) (gao:A2G06_05670, gao:A2G06_06115) (gao:A2G06_05980, gao:A2G06_09675) (gao:A2G06_06120, gao:A2G06_07620) (gao:A2G06_06270, gao:A2G06_06650) (gao:A2G06_06270, gao:A2G06_14765) (gao:A2G06_06620, gao:A2G06_08260) (gao:A2G06_06650, gao:A2G06_14765) (gao:A2G06_07085, gao:A2G06_08260) (gao:A2G06_07325, gao:A2G06_07920) (gao:A2G06_08130, gao:A2G06_13760) (gao:A2G06_09115, gao:A2G06_13050) (gao:A2G06_10540, gao:A2G06_15675) (gao:A2G06_10625, gao:A2G06_11490) (gao:A2G06_12745, gao:A2G06_14560) (gao:A2G06_12745, gao:A2G06_14565) (gao:A2G06_13760, gao:A2G06_16175) (gao:A2G06_13765, gao:A2G06_16175) (gao:A2G06_14560, gao:A2G06_14565) (gbm:Gbem_0212, gbm:Gbem_3205) (gbm:Gbem_0259, gbm:Gbem_1465) (gbm:Gbem_0259, gbm:Gbem_3222) (gbm:Gbem_0260, gbm:Gbem_1464) (gbm:Gbem_0260, gbm:Gbem_3223) (gbm:Gbem_0279, gbm:Gbem_1379) (gbm:Gbem_0280, gbm:Gbem_1258) (gbm:Gbem_0280, gbm:Gbem_3362) (gbm:Gbem_0486, gbm:Gbem_0487) (gbm:Gbem_0493, gbm:Gbem_3180) (gbm:Gbem_0564, gbm:Gbem_2906) (gbm:Gbem_0567, gbm:Gbem_3400) (gbm:Gbem_0635, gbm:Gbem_2980) (gbm:Gbem_0751, gbm:Gbem_1531) (gbm:Gbem_0751, gbm:Gbem_3650) (gbm:Gbem_0823, gbm:Gbem_1554) (gbm:Gbem_0836, gbm:Gbem_2903) (gbm:Gbem_0861, gbm:Gbem_3346) (gbm:Gbem_0909, gbm:Gbem_0910) (gbm:Gbem_1081, gbm:Gbem_1615) (gbm:Gbem_1081, gbm:Gbem_1778) (gbm:Gbem_1258, gbm:Gbem_3362) (gbm:Gbem_1265, gbm:Gbem_2742) (gbm:Gbem_1341, gbm:Gbem_1725) (gbm:Gbem_1348, gbm:Gbem_2274) (gbm:Gbem_1349, gbm:Gbem_2149) (gbm:Gbem_1349, gbm:Gbem_2273) (gbm:Gbem_1354, gbm:Gbem_1436) (gbm:Gbem_1354, gbm:Gbem_2272) (gbm:Gbem_1436, gbm:Gbem_2272) (gbm:Gbem_1464, gbm:Gbem_3223) (gbm:Gbem_1465, gbm:Gbem_3222) (gbm:Gbem_1531, gbm:Gbem_3650) (gbm:Gbem_1571, gbm:Gbem_3162) (gbm:Gbem_1615, gbm:Gbem_1778) (gbm:Gbem_1629, gbm:Gbem_2352) (gbm:Gbem_1630, gbm:Gbem_2353) (gbm:Gbem_1652, gbm:Gbem_3905) (gbm:Gbem_1896, gbm:Gbem_3637) (gbm:Gbem_1958, gbm:Gbem_3321) (gbm:Gbem_1983, gbm:Gbem_3163) (gbm:Gbem_2051, gbm:Gbem_3927) (gbm:Gbem_2125, gbm:Gbem_2216) (gbm:Gbem_2149, gbm:Gbem_2273) (gbm:Gbem_2173, gbm:Gbem_2258) (gbm:Gbem_2184, gbm:Gbem_2192) (gbm:Gbem_2235, gbm:Gbem_2446) (gbm:Gbem_2235, gbm:Gbem_3820) (gbm:Gbem_2336, gbm:Gbem_3789) (gbm:Gbem_2446, gbm:Gbem_3820) (gbm:Gbem_2561, gbm:Gbem_3783) (gbm:Gbem_2692, gbm:Gbem_2828) (gbm:Gbem_2797, gbm:Gbem_3530) (gbm:Gbem_2859, gbm:Gbem_4055) (gbm:Gbem_3108, gbm:Gbem_3995) (gbm:Gbem_3345, gbm:Gbem_4020) (gbm:Gbem_3463, gbm:Gbem_3809) (gbm:Gbem_3700, gbm:Gbem_3701) (geb:GM18_0169, geb:GM18_3247) (geb:GM18_0287, geb:GM18_3274) (geb:GM18_0288, geb:GM18_3275) (geb:GM18_0316, geb:GM18_1241) (geb:GM18_0317, geb:GM18_1116) (geb:GM18_0317, geb:GM18_3441) (geb:GM18_0559, geb:GM18_2665) (geb:GM18_0559, geb:GM18_2739) (geb:GM18_0634, geb:GM18_4239) (geb:GM18_0699, geb:GM18_3789) (geb:GM18_0719, geb:GM18_1389) (geb:GM18_0730, geb:GM18_2790) (geb:GM18_0750, geb:GM18_3424) (geb:GM18_0750, geb:GM18_4171) (geb:GM18_0779, geb:GM18_3827) (geb:GM18_0809, geb:GM18_0810) (geb:GM18_0958, geb:GM18_1602) (geb:GM18_1054, geb:GM18_3547) (geb:GM18_1091, geb:GM18_2560) (geb:GM18_1116, geb:GM18_3441) (geb:GM18_1123, geb:GM18_2608) (geb:GM18_1206, geb:GM18_1956) (geb:GM18_1206, geb:GM18_4466) (geb:GM18_1211, geb:GM18_1958) (geb:GM18_1366, geb:GM18_3598) (geb:GM18_1366, geb:GM18_4108) (geb:GM18_1403, geb:GM18_1836) (geb:GM18_1436, geb:GM18_3257) (geb:GM18_1436, geb:GM18_4171) (geb:GM18_1438, geb:GM18_1454) (geb:GM18_1438, geb:GM18_1672) (geb:GM18_1442, geb:GM18_4151) (geb:GM18_1443, geb:GM18_4149) (geb:GM18_1454, geb:GM18_1672) (geb:GM18_1602, geb:GM18_2013) (geb:GM18_1602, geb:GM18_2111) (geb:GM18_1720, geb:GM18_4095) (geb:GM18_1893, geb:GM18_4219) (geb:GM18_1956, geb:GM18_4466) (geb:GM18_1971, geb:GM18_2068) (geb:GM18_1990, geb:GM18_2304) (geb:GM18_1990, geb:GM18_3980) (geb:GM18_1990, geb:GM18_4250) (geb:GM18_2013, geb:GM18_2111) (geb:GM18_2054, geb:GM18_2062) (geb:GM18_2054, geb:GM18_4063) (geb:GM18_2062, geb:GM18_4063) (geb:GM18_2157, geb:GM18_4391) (geb:GM18_2226, geb:GM18_3132) (geb:GM18_2264, geb:GM18_3400) (geb:GM18_2304, geb:GM18_3980) (geb:GM18_2304, geb:GM18_4250) (geb:GM18_2665, geb:GM18_2739) (geb:GM18_2719, geb:GM18_4516) (geb:GM18_2759, geb:GM18_4463) (geb:GM18_2793, geb:GM18_3792) (geb:GM18_3075, geb:GM18_4050) (geb:GM18_3075, geb:GM18_4055) (geb:GM18_3075, geb:GM18_4066) (geb:GM18_3077, geb:GM18_4069) (geb:GM18_3079, geb:GM18_4453) (geb:GM18_3185, geb:GM18_3885) (geb:GM18_3257, geb:GM18_3424) (geb:GM18_3257, geb:GM18_4171) (geb:GM18_3424, geb:GM18_4171) (geb:GM18_3598, geb:GM18_4108) (geb:GM18_3889, geb:GM18_3891) (geb:GM18_3891, geb:GM18_3892) (geb:GM18_3980, geb:GM18_4250) (geb:GM18_4050, geb:GM18_4055) (geb:GM18_4050, geb:GM18_4066) (geb:GM18_4055, geb:GM18_4066) (geb:GM18_4149, geb:GM18_4150) (gem:GM21_0195, gem:GM21_1058) (gem:GM21_0244, gem:GM21_1041) (gem:GM21_0244, gem:GM21_2788) (gem:GM21_0245, gem:GM21_1040) (gem:GM21_0245, gem:GM21_2789) (gem:GM21_0264, gem:GM21_2903) (gem:GM21_0264, gem:GM21_3398) (gem:GM21_0265, gem:GM21_0883) (gem:GM21_0265, gem:GM21_3025) (gem:GM21_0265, gem:GM21_3397) (gem:GM21_0503, gem:GM21_0504) (gem:GM21_0506, gem:GM21_0509) (gem:GM21_0510, gem:GM21_1080) (gem:GM21_0510, gem:GM21_2456) (gem:GM21_0577, gem:GM21_1319) (gem:GM21_0580, gem:GM21_3463) (gem:GM21_0718, gem:GM21_3566) (gem:GM21_0766, gem:GM21_2685) (gem:GM21_0766, gem:GM21_3757) (gem:GM21_0883, gem:GM21_3025) (gem:GM21_0883, gem:GM21_3397) (gem:GM21_0899, gem:GM21_3403) (gem:GM21_0900, gem:GM21_4111) (gem:GM21_0925, gem:GM21_2258) (gem:GM21_1040, gem:GM21_2789) (gem:GM21_1041, gem:GM21_2788) (gem:GM21_1080, gem:GM21_2456) (gem:GM21_1096, gem:GM21_2237) (gem:GM21_1097, gem:GM21_2642) (gem:GM21_1154, gem:GM21_4090) (gem:GM21_1322, gem:GM21_3424) (gem:GM21_1355, gem:GM21_4145) (gem:GM21_1385, gem:GM21_1547) (gem:GM21_1413, gem:GM21_3596) (gem:GM21_1499, gem:GM21_3018) (gem:GM21_1667, gem:GM21_3867) (gem:GM21_1771, gem:GM21_1992) (gem:GM21_1771, gem:GM21_3904) (gem:GM21_1884, gem:GM21_3873) (gem:GM21_1949, gem:GM21_2937) (gem:GM21_1950, gem:GM21_2072) (gem:GM21_1950, gem:GM21_2936) (gem:GM21_1951, gem:GM21_2818) (gem:GM21_1951, gem:GM21_2931) (gem:GM21_1966, gem:GM21_2050) (gem:GM21_1992, gem:GM21_3904) (gem:GM21_2011, gem:GM21_2093) (gem:GM21_2035, gem:GM21_2043) (gem:GM21_2043, gem:GM21_2454) (gem:GM21_2072, gem:GM21_2936) (gem:GM21_2166, gem:GM21_4011) (gem:GM21_2312, gem:GM21_3742) (gem:GM21_2457, gem:GM21_3802) (gem:GM21_2469, gem:GM21_3180) (gem:GM21_2561, gem:GM21_3990) (gem:GM21_2662, gem:GM21_3438) (gem:GM21_2685, gem:GM21_3757) (gem:GM21_2818, gem:GM21_2931) (gem:GM21_2903, gem:GM21_3398) (gem:GM21_3025, gem:GM21_3397) (gem:GM21_3529, gem:GM21_3893) (gem:GM21_3795, gem:GM21_3796) (geo:Geob_0099, geo:Geob_1910) (geo:Geob_0099, geo:Geob_2614) (geo:Geob_0150, geo:Geob_1333) (geo:Geob_0150, geo:Geob_1637) (geo:Geob_0150, geo:Geob_1647) (geo:Geob_0247, geo:Geob_0762) (geo:Geob_0248, geo:Geob_0761) (geo:Geob_0284, geo:Geob_2923) (geo:Geob_0378, geo:Geob_2151) (geo:Geob_0392, geo:Geob_2171) (geo:Geob_0392, geo:Geob_3082) (geo:Geob_0461, geo:Geob_3010) (geo:Geob_0514, geo:Geob_3549) (geo:Geob_0532, geo:Geob_3462) (geo:Geob_0543, geo:Geob_1417) (geo:Geob_0666, geo:Geob_1368) (geo:Geob_0666, geo:Geob_2629) (geo:Geob_0666, geo:Geob_3664) (geo:Geob_0667, geo:Geob_1002) (geo:Geob_0667, geo:Geob_1367) (geo:Geob_0692, geo:Geob_0693) (geo:Geob_0775, geo:Geob_0776) (geo:Geob_0778, geo:Geob_0781) (geo:Geob_0805, geo:Geob_1439) (geo:Geob_0952, geo:Geob_1550) (geo:Geob_1002, geo:Geob_1367) (geo:Geob_1002, geo:Geob_1368) (geo:Geob_1002, geo:Geob_3664) (geo:Geob_1062, geo:Geob_2796) (geo:Geob_1062, geo:Geob_2804) (geo:Geob_1088, geo:Geob_1753) (geo:Geob_1123, geo:Geob_3264) (geo:Geob_1129, geo:Geob_1143) (geo:Geob_1167, geo:Geob_2897) (geo:Geob_1333, geo:Geob_1637) (geo:Geob_1333, geo:Geob_1647) (geo:Geob_1368, geo:Geob_2629) (geo:Geob_1368, geo:Geob_3664) (geo:Geob_1403, geo:Geob_2459) (geo:Geob_1403, geo:Geob_2530) (geo:Geob_1420, geo:Geob_2508) (geo:Geob_1458, geo:Geob_2134) (geo:Geob_1504, geo:Geob_2938) (geo:Geob_1637, geo:Geob_1647) (geo:Geob_1656, geo:Geob_2241) (geo:Geob_1870, geo:Geob_2923) (geo:Geob_1910, geo:Geob_2614) (geo:Geob_1911, geo:Geob_2616) (geo:Geob_1980, geo:Geob_2507) (geo:Geob_1980, geo:Geob_2526) (geo:Geob_1980, geo:Geob_3049) (geo:Geob_2094, geo:Geob_2661) (geo:Geob_2171, geo:Geob_3082) (geo:Geob_2295, geo:Geob_2315) (geo:Geob_2459, geo:Geob_2530) (geo:Geob_2507, geo:Geob_2526) (geo:Geob_2507, geo:Geob_3049) (geo:Geob_2526, geo:Geob_3049) (geo:Geob_2612, geo:Geob_3708) (geo:Geob_2629, geo:Geob_3664) (geo:Geob_2796, geo:Geob_2804) (geo:Geob_3651, geo:Geob_3652) (glo:Glov_0210, glo:Glov_0893) (glo:Glov_0210, glo:Glov_3585) (glo:Glov_0365, glo:Glov_1947) (glo:Glov_0418, glo:Glov_1939) (glo:Glov_0418, glo:Glov_2418) (glo:Glov_0474, glo:Glov_3457) (glo:Glov_0479, glo:Glov_1658) (glo:Glov_0479, glo:Glov_3365) (glo:Glov_0555, glo:Glov_2962) (glo:Glov_0584, glo:Glov_2128) (glo:Glov_0674, glo:Glov_0675) (glo:Glov_0692, glo:Glov_3718) (glo:Glov_0757, glo:Glov_1622) (glo:Glov_0763, glo:Glov_1937) (glo:Glov_0786, glo:Glov_2503) (glo:Glov_0795, glo:Glov_2804) (glo:Glov_0796, glo:Glov_2182) (glo:Glov_0796, glo:Glov_2235) (glo:Glov_0808, glo:Glov_1512) (glo:Glov_0823, glo:Glov_2405) (glo:Glov_0835, glo:Glov_1607) (glo:Glov_0892, glo:Glov_1159) (glo:Glov_0893, glo:Glov_3585) (glo:Glov_0909, glo:Glov_1157) (glo:Glov_0981, glo:Glov_2116) (glo:Glov_0981, glo:Glov_2538) (glo:Glov_1018, glo:Glov_1019) (glo:Glov_1018, glo:Glov_3399) (glo:Glov_1024, glo:Glov_3068) (glo:Glov_1067, glo:Glov_1531) (glo:Glov_1099, glo:Glov_2713) (glo:Glov_1211, glo:Glov_1213) (glo:Glov_1616, glo:Glov_2562) (glo:Glov_1658, glo:Glov_3365) (glo:Glov_1768, glo:Glov_2600) (glo:Glov_1858, glo:Glov_1910) (glo:Glov_1934, glo:Glov_2193) (glo:Glov_1936, glo:Glov_2194) (glo:Glov_1939, glo:Glov_2418) (glo:Glov_2038, glo:Glov_3325) (glo:Glov_2085, glo:Glov_3149) (glo:Glov_2116, glo:Glov_2538) (glo:Glov_2182, glo:Glov_2235) (glo:Glov_2247, glo:Glov_3139) (glo:Glov_2508, glo:Glov_3322) (glo:Glov_2764, glo:Glov_3677) (glo:Glov_3217, glo:Glov_3634) (gme:Gmet_0065, gme:Gmet_3078) (gme:Gmet_0104, gme:Gmet_1487) (gme:Gmet_0178, gme:Gmet_0551) (gme:Gmet_0178, gme:Gmet_0552) (gme:Gmet_0205, gme:Gmet_1769) (gme:Gmet_0219, gme:Gmet_2019) (gme:Gmet_0264, gme:Gmet_1558) (gme:Gmet_0264, gme:Gmet_2988) (gme:Gmet_0301, gme:Gmet_0337) (gme:Gmet_0301, gme:Gmet_2095) (gme:Gmet_0336, gme:Gmet_1038) (gme:Gmet_0336, gme:Gmet_1804) (gme:Gmet_0337, gme:Gmet_2095) (gme:Gmet_0351, gme:Gmet_0956) (gme:Gmet_0351, gme:Gmet_2300) (gme:Gmet_0388, gme:Gmet_0389) (gme:Gmet_0407, gme:Gmet_0408) (gme:Gmet_0407, gme:Gmet_0410) (gme:Gmet_0410, gme:Gmet_0413) (gme:Gmet_0471, gme:Gmet_2910) (gme:Gmet_0552, gme:Gmet_1934) (gme:Gmet_0552, gme:Gmet_2822) (gme:Gmet_0661, gme:Gmet_1774) (gme:Gmet_0707, gme:Gmet_3175) (gme:Gmet_0729, gme:Gmet_2069) (gme:Gmet_0729, gme:Gmet_2261) (gme:Gmet_0730, gme:Gmet_2068) (gme:Gmet_0730, gme:Gmet_2260) (gme:Gmet_0770, gme:Gmet_2101) (gme:Gmet_0872, gme:Gmet_0992) (gme:Gmet_0884, gme:Gmet_3339) (gme:Gmet_0940, gme:Gmet_2767) (gme:Gmet_0940, gme:Gmet_3159) (gme:Gmet_0950, gme:Gmet_1818) (gme:Gmet_0950, gme:Gmet_1825) (gme:Gmet_0956, gme:Gmet_2300) (gme:Gmet_1016, gme:Gmet_2763) (gme:Gmet_1038, gme:Gmet_1804) (gme:Gmet_1124, gme:Gmet_2689) (gme:Gmet_1211, gme:Gmet_1946) (gme:Gmet_1265, gme:Gmet_1879) (gme:Gmet_1297, gme:Gmet_1910) (gme:Gmet_1357, gme:Gmet_2360) (gme:Gmet_1469, gme:Gmet_1613) (gme:Gmet_1486, gme:Gmet_2329) (gme:Gmet_1558, gme:Gmet_2988) (gme:Gmet_1580, gme:Gmet_3356) (gme:Gmet_1599, gme:Gmet_3272) (gme:Gmet_1601, gme:Gmet_1694) (gme:Gmet_1601, gme:Gmet_2059) (gme:Gmet_1603, gme:Gmet_1695) (gme:Gmet_1604, gme:Gmet_2621) (gme:Gmet_1613, gme:Gmet_2229) (gme:Gmet_1613, gme:Gmet_2340) (gme:Gmet_1694, gme:Gmet_2059) (gme:Gmet_1818, gme:Gmet_1825) (gme:Gmet_1818, gme:Gmet_2007) (gme:Gmet_1825, gme:Gmet_2007) (gme:Gmet_1896, gme:Gmet_2764) (gme:Gmet_1934, gme:Gmet_2822) (gme:Gmet_1954, gme:Gmet_2911) (gme:Gmet_2024, gme:Gmet_2172) (gme:Gmet_2068, gme:Gmet_2260) (gme:Gmet_2069, gme:Gmet_2261) (gme:Gmet_2229, gme:Gmet_2340) (gme:Gmet_2319, gme:Gmet_3422) (gme:Gmet_2329, gme:Gmet_2473) (gme:Gmet_2330, gme:Gmet_2473) (gme:Gmet_2353, gme:Gmet_2567) (gme:Gmet_2482, gme:Gmet_2493) (gpi:GPICK_00285, gpi:GPICK_06970) (gpi:GPICK_00320, gpi:GPICK_14070) (gpi:GPICK_01105, gpi:GPICK_06205) (gpi:GPICK_01155, gpi:GPICK_03805) (gpi:GPICK_01155, gpi:GPICK_10945) (gpi:GPICK_01260, gpi:GPICK_02005) (gpi:GPICK_01260, gpi:GPICK_09250) (gpi:GPICK_01260, gpi:GPICK_13690) (gpi:GPICK_01450, gpi:GPICK_09850) (gpi:GPICK_01855, gpi:GPICK_04525) (gpi:GPICK_01855, gpi:GPICK_09465) (gpi:GPICK_02005, gpi:GPICK_09250) (gpi:GPICK_02005, gpi:GPICK_13690) (gpi:GPICK_02075, gpi:GPICK_05460) (gpi:GPICK_02075, gpi:GPICK_10225) (gpi:GPICK_02235, gpi:GPICK_02240) (gpi:GPICK_02335, gpi:GPICK_02340) (gpi:GPICK_02630, gpi:GPICK_13390) (gpi:GPICK_02895, gpi:GPICK_08135) (gpi:GPICK_02900, gpi:GPICK_04075) (gpi:GPICK_02900, gpi:GPICK_07275) (gpi:GPICK_03195, gpi:GPICK_03200) (gpi:GPICK_03805, gpi:GPICK_10945) (gpi:GPICK_03840, gpi:GPICK_05200) (gpi:GPICK_04075, gpi:GPICK_07275) (gpi:GPICK_04525, gpi:GPICK_09465) (gpi:GPICK_04615, gpi:GPICK_11140) (gpi:GPICK_04625, gpi:GPICK_06080) (gpi:GPICK_04625, gpi:GPICK_07085) (gpi:GPICK_05040, gpi:GPICK_06250) (gpi:GPICK_05075, gpi:GPICK_09355) (gpi:GPICK_05080, gpi:GPICK_09350) (gpi:GPICK_05085, gpi:GPICK_09910) (gpi:GPICK_05385, gpi:GPICK_14470) (gpi:GPICK_05460, gpi:GPICK_10225) (gpi:GPICK_06080, gpi:GPICK_07085) (gpi:GPICK_06360, gpi:GPICK_09020) (gpi:GPICK_07425, gpi:GPICK_08415) (gpi:GPICK_07440, gpi:GPICK_07790) (gpi:GPICK_07485, gpi:GPICK_14900) (gpi:GPICK_07640, gpi:GPICK_15365) (gpi:GPICK_07650, gpi:GPICK_10370) (gpi:GPICK_07650, gpi:GPICK_10380) (gpi:GPICK_07830, gpi:GPICK_15315) (gpi:GPICK_07925, gpi:GPICK_15035) (gpi:GPICK_07935, gpi:GPICK_09325) (gpi:GPICK_07935, gpi:GPICK_15425) (gpi:GPICK_07945, gpi:GPICK_15430) (gpi:GPICK_08200, gpi:GPICK_08240) (gpi:GPICK_08380, gpi:GPICK_15365) (gpi:GPICK_08745, gpi:GPICK_10520) (gpi:GPICK_09250, gpi:GPICK_13690) (gpi:GPICK_09325, gpi:GPICK_15425) (gpi:GPICK_10090, gpi:GPICK_11530) (gpi:GPICK_10320, gpi:GPICK_15670) (gpi:GPICK_10370, gpi:GPICK_10380) (gpi:GPICK_10370, gpi:GPICK_11740) (gpi:GPICK_10380, gpi:GPICK_11740) (gpi:GPICK_10485, gpi:GPICK_12360) (gpi:GPICK_11735, gpi:GPICK_13255) (gpi:GPICK_11785, gpi:GPICK_11795) (gpi:GPICK_12055, gpi:GPICK_14550) (gpi:GPICK_12620, gpi:GPICK_15235) (gsb:GSUB_00160, gsb:GSUB_02660) (gsb:GSUB_00535, gsb:GSUB_02445) (gsb:GSUB_00535, gsb:GSUB_13565) (gsb:GSUB_00615, gsb:GSUB_09020) (gsb:GSUB_01295, gsb:GSUB_07510) (gsb:GSUB_01445, gsb:GSUB_09555) (gsb:GSUB_01445, gsb:GSUB_13975) (gsb:GSUB_01620, gsb:GSUB_05255) (gsb:GSUB_01730, gsb:GSUB_07600) (gsb:GSUB_01730, gsb:GSUB_11175) (gsb:GSUB_01835, gsb:GSUB_13655) (gsb:GSUB_01970, gsb:GSUB_12980) (gsb:GSUB_02190, gsb:GSUB_09375) (gsb:GSUB_02445, gsb:GSUB_13565) (gsb:GSUB_02540, gsb:GSUB_02545) (gsb:GSUB_02540, gsb:GSUB_08845) (gsb:GSUB_02545, gsb:GSUB_08845) (gsb:GSUB_02810, gsb:GSUB_14410) (gsb:GSUB_02815, gsb:GSUB_06155) (gsb:GSUB_02815, gsb:GSUB_14410) (gsb:GSUB_03040, gsb:GSUB_09180) (gsb:GSUB_03270, gsb:GSUB_08910) (gsb:GSUB_03680, gsb:GSUB_05075) (gsb:GSUB_03880, gsb:GSUB_09165) (gsb:GSUB_04800, gsb:GSUB_10480) (gsb:GSUB_07140, gsb:GSUB_10305) (gsb:GSUB_07515, gsb:GSUB_17495) (gsb:GSUB_07600, gsb:GSUB_11175) (gsb:GSUB_07655, gsb:GSUB_10525) (gsb:GSUB_08095, gsb:GSUB_08160) (gsb:GSUB_08160, gsb:GSUB_09095) (gsb:GSUB_08160, gsb:GSUB_09105) (gsb:GSUB_08195, gsb:GSUB_15430) (gsb:GSUB_08785, gsb:GSUB_10925) (gsb:GSUB_08785, gsb:GSUB_12790) (gsb:GSUB_08840, gsb:GSUB_15700) (gsb:GSUB_09095, gsb:GSUB_09105) (gsb:GSUB_09095, gsb:GSUB_13365) (gsb:GSUB_09105, gsb:GSUB_13365) (gsb:GSUB_09400, gsb:GSUB_11235) (gsb:GSUB_09400, gsb:GSUB_13265) (gsb:GSUB_09555, gsb:GSUB_13975) (gsb:GSUB_10905, gsb:GSUB_12340) (gsb:GSUB_10925, gsb:GSUB_12790) (gsb:GSUB_11235, gsb:GSUB_13265) (gsb:GSUB_12475, gsb:GSUB_12485) (gsb:GSUB_12985, gsb:GSUB_13010) (gsb:GSUB_13010, gsb:GSUB_13015) (gsu:GSU0067, gsu:GSU2307) (gsu:GSU0094, gsu:GSU2230) (gsu:GSU0152, gsu:GSU1271) (gsu:GSU0290, gsu:GSU1601) (gsu:GSU0337, gsu:GSU1582) (gsu:GSU0371, gsu:GSU2066) (gsu:GSU0460, gsu:GSU1605) (gsu:GSU0461, gsu:GSU1603) (gsu:GSU0482, gsu:GSU3372) (gsu:GSU0535, gsu:GSU3158) (gsu:GSU0604, gsu:GSU3005) (gsu:GSU0686, gsu:GSU1764) (gsu:GSU0686, gsu:GSU2918) (gsu:GSU0846, gsu:GSU2445) (gsu:GSU0999, gsu:GSU2264) (gsu:GSU1023, gsu:GSU3257) (gsu:GSU1061, gsu:GSU1242) (gsu:GSU1463, gsu:GSU2271) (gsu:GSU1623, gsu:GSU3296) (gsu:GSU1729, gsu:GSU1737) (gsu:GSU1764, gsu:GSU2918) (gsu:GSU1798, gsu:GSU1906) (gsu:GSU2011, gsu:GSU2570) (gsu:GSU2011, gsu:GSU2786) (gsu:GSU2045, gsu:GSU2209) (gsu:GSU2045, gsu:GSU3136) (gsu:GSU2209, gsu:GSU3136) (gsu:GSU2241, gsu:GSU2366) (gsu:GSU2375, gsu:GSU2379) (gsu:GSU2446, gsu:GSU2588) (gsu:GSU2570, gsu:GSU2786) (gsu:GSU2918, gsu:GSU3423) (gsu:GSU2919, gsu:GSU3423) (gsu:GSU3095, gsu:GSU3096) (gur:Gura_0074, gur:Gura_2025) (gur:Gura_0135, gur:Gura_1875) (gur:Gura_0155, gur:Gura_3486) (gur:Gura_0155, gur:Gura_3998) (gur:Gura_0155, gur:Gura_4349) (gur:Gura_0156, gur:Gura_3485) (gur:Gura_0156, gur:Gura_3999) (gur:Gura_0156, gur:Gura_4348) (gur:Gura_0185, gur:Gura_2259) (gur:Gura_0191, gur:Gura_0937) (gur:Gura_0227, gur:Gura_1856) (gur:Gura_0462, gur:Gura_3393) (gur:Gura_0462, gur:Gura_3541) (gur:Gura_0491, gur:Gura_0841) (gur:Gura_0491, gur:Gura_0970) (gur:Gura_0492, gur:Gura_0841) (gur:Gura_0492, gur:Gura_1018) (gur:Gura_0492, gur:Gura_2175) (gur:Gura_0620, gur:Gura_3720) (gur:Gura_0648, gur:Gura_2199) (gur:Gura_0822, gur:Gura_3859) (gur:Gura_0822, gur:Gura_3907) (gur:Gura_0841, gur:Gura_0970) (gur:Gura_1018, gur:Gura_2175) (gur:Gura_1046, gur:Gura_1047) (gur:Gura_1346, gur:Gura_1351) (gur:Gura_1387, gur:Gura_2953) (gur:Gura_1493, gur:Gura_1833) (gur:Gura_1570, gur:Gura_2061) (gur:Gura_1570, gur:Gura_2659) (gur:Gura_1570, gur:Gura_4250) (gur:Gura_1685, gur:Gura_2598) (gur:Gura_1685, gur:Gura_3171) (gur:Gura_1685, gur:Gura_3273) (gur:Gura_1691, gur:Gura_4055) (gur:Gura_1692, gur:Gura_4053) (gur:Gura_1705, gur:Gura_2661) (gur:Gura_1705, gur:Gura_3854) (gur:Gura_1705, gur:Gura_4193) (gur:Gura_1735, gur:Gura_2532) (gur:Gura_1735, gur:Gura_3288) (gur:Gura_1799, gur:Gura_3134) (gur:Gura_1799, gur:Gura_4313) (gur:Gura_1877, gur:Gura_3607) (gur:Gura_1879, gur:Gura_3606) (gur:Gura_2061, gur:Gura_2659) (gur:Gura_2061, gur:Gura_4250) (gur:Gura_2124, gur:Gura_2133) (gur:Gura_2196, gur:Gura_3240) (gur:Gura_2244, gur:Gura_4245) (gur:Gura_2317, gur:Gura_3715) (gur:Gura_2419, gur:Gura_3571) (gur:Gura_2420, gur:Gura_3574) (gur:Gura_2501, gur:Gura_3354) (gur:Gura_2532, gur:Gura_3288) (gur:Gura_2566, gur:Gura_2643) (gur:Gura_2598, gur:Gura_3273) (gur:Gura_2655, gur:Gura_4409) (gur:Gura_2659, gur:Gura_4250) (gur:Gura_2661, gur:Gura_3854) (gur:Gura_2661, gur:Gura_4193) (gur:Gura_3134, gur:Gura_4313) (gur:Gura_3154, gur:Gura_4327) (gur:Gura_3393, gur:Gura_3541) (gur:Gura_3485, gur:Gura_3999) (gur:Gura_3485, gur:Gura_4348) (gur:Gura_3486, gur:Gura_3998) (gur:Gura_3486, gur:Gura_4349) (gur:Gura_3622, gur:Gura_4137) (gur:Gura_3830, gur:Gura_3934) (gur:Gura_3852, gur:Gura_4183) (gur:Gura_3854, gur:Gura_4193) (gur:Gura_3859, gur:Gura_3907) (gur:Gura_3978, gur:Gura_3979) (gur:Gura_3998, gur:Gura_4349) (gur:Gura_3999, gur:Gura_4348) (gur:Gura_4053, gur:Gura_4054) (hmr:Hipma_0012, hmr:Hipma_0985) (hmr:Hipma_0121, hmr:Hipma_0501) (hmr:Hipma_0146, hmr:Hipma_0574) (hmr:Hipma_0146, hmr:Hipma_1193) (hmr:Hipma_0215, hmr:Hipma_1516) (hmr:Hipma_0301, hmr:Hipma_1016) (hmr:Hipma_0301, hmr:Hipma_1167) (hmr:Hipma_0341, hmr:Hipma_0431) (hmr:Hipma_0369, hmr:Hipma_0390) (hmr:Hipma_0412, hmr:Hipma_0845) (hmr:Hipma_0432, hmr:Hipma_1565) (hmr:Hipma_0574, hmr:Hipma_1193) (hmr:Hipma_0577, hmr:Hipma_1526) (hmr:Hipma_0790, hmr:Hipma_1462) (hmr:Hipma_0954, hmr:Hipma_0956) (hmr:Hipma_1016, hmr:Hipma_1167) (hmr:Hipma_1025, hmr:Hipma_1045) (hmr:Hipma_1025, hmr:Hipma_1397) (hmr:Hipma_1212, hmr:Hipma_1646) (hmr:Hipma_1401, hmr:Hipma_1703) (hoh:Hoch_0005, hoh:Hoch_0232) (hoh:Hoch_0005, hoh:Hoch_2946) (hoh:Hoch_0005, hoh:Hoch_6403) (hoh:Hoch_0106, hoh:Hoch_3273) (hoh:Hoch_0124, hoh:Hoch_4480) (hoh:Hoch_0217, hoh:Hoch_4175) (hoh:Hoch_0217, hoh:Hoch_4179) (hoh:Hoch_0217, hoh:Hoch_6176) (hoh:Hoch_0232, hoh:Hoch_2946) (hoh:Hoch_0232, hoh:Hoch_6403) (hoh:Hoch_0240, hoh:Hoch_3234) (hoh:Hoch_0240, hoh:Hoch_3705) (hoh:Hoch_0240, hoh:Hoch_4996) (hoh:Hoch_0330, hoh:Hoch_4501) (hoh:Hoch_0343, hoh:Hoch_4475) (hoh:Hoch_0343, hoh:Hoch_6015) (hoh:Hoch_0345, hoh:Hoch_5950) (hoh:Hoch_0360, hoh:Hoch_4160) (hoh:Hoch_0379, hoh:Hoch_6609) (hoh:Hoch_0394, hoh:Hoch_5324) (hoh:Hoch_0481, hoh:Hoch_5030) (hoh:Hoch_0481, hoh:Hoch_5651) (hoh:Hoch_0610, hoh:Hoch_4469) (hoh:Hoch_0637, hoh:Hoch_0966) (hoh:Hoch_0637, hoh:Hoch_1023) (hoh:Hoch_0966, hoh:Hoch_1023) (hoh:Hoch_1085, hoh:Hoch_3033) (hoh:Hoch_1478, hoh:Hoch_4463) (hoh:Hoch_1786, hoh:Hoch_4360) (hoh:Hoch_1786, hoh:Hoch_4947) (hoh:Hoch_1849, hoh:Hoch_2693) (hoh:Hoch_1849, hoh:Hoch_6383) (hoh:Hoch_1891, hoh:Hoch_4042) (hoh:Hoch_2046, hoh:Hoch_5389) (hoh:Hoch_2104, hoh:Hoch_5290) (hoh:Hoch_2190, hoh:Hoch_2547) (hoh:Hoch_2190, hoh:Hoch_3724) (hoh:Hoch_2547, hoh:Hoch_3724) (hoh:Hoch_2693, hoh:Hoch_6383) (hoh:Hoch_3033, hoh:Hoch_6151) (hoh:Hoch_3186, hoh:Hoch_3975) (hoh:Hoch_3189, hoh:Hoch_5889) (hoh:Hoch_3234, hoh:Hoch_3705) (hoh:Hoch_3234, hoh:Hoch_4996) (hoh:Hoch_3248, hoh:Hoch_3514) (hoh:Hoch_3248, hoh:Hoch_3572) (hoh:Hoch_3248, hoh:Hoch_4679) (hoh:Hoch_3514, hoh:Hoch_3572) (hoh:Hoch_3514, hoh:Hoch_4679) (hoh:Hoch_3572, hoh:Hoch_4679) (hoh:Hoch_3581, hoh:Hoch_6801) (hoh:Hoch_3705, hoh:Hoch_4996) (hoh:Hoch_4024, hoh:Hoch_4575) (hoh:Hoch_4075, hoh:Hoch_4355) (hoh:Hoch_4175, hoh:Hoch_4179) (hoh:Hoch_4175, hoh:Hoch_6176) (hoh:Hoch_4179, hoh:Hoch_6176) (hoh:Hoch_4359, hoh:Hoch_6171) (hoh:Hoch_4360, hoh:Hoch_4947) (hoh:Hoch_4463, hoh:Hoch_5556) (hoh:Hoch_4475, hoh:Hoch_6015) (hoh:Hoch_4475, hoh:Hoch_6893) (hoh:Hoch_4947, hoh:Hoch_6475) (hoh:Hoch_4968, hoh:Hoch_5530) (hoh:Hoch_5001, hoh:Hoch_5030) (hoh:Hoch_5001, hoh:Hoch_5197) (hoh:Hoch_5001, hoh:Hoch_5651) (hoh:Hoch_5030, hoh:Hoch_5197) (hoh:Hoch_5030, hoh:Hoch_5651) (hoh:Hoch_5197, hoh:Hoch_5651) (hoh:Hoch_5539, hoh:Hoch_6139) (hoh:Hoch_5889, hoh:Hoch_6458) (hoh:Hoch_6483, hoh:Hoch_6870) (lip:LI0152, lip:LI0648) (lip:LI0152, lip:LI1051) (lip:LI0379, lip:LI0580) (lip:LI0466, lip:LI0580) (lip:LI0466, lip:LI1066) (lip:LI0466, lip:LIC023) (lip:LI0580, lip:LI1066) (lip:LI0580, lip:LIC023) (lip:LI0648, lip:LI1051) (lip:LI0764, lip:LI1119) (llu:AKJ09_00297, llu:AKJ09_10095) (llu:AKJ09_00381, llu:AKJ09_01495) (llu:AKJ09_00381, llu:AKJ09_02991) (llu:AKJ09_00381, llu:AKJ09_05314) (llu:AKJ09_00381, llu:AKJ09_09399) (llu:AKJ09_00430, llu:AKJ09_07617) (llu:AKJ09_00430, llu:AKJ09_08666) (llu:AKJ09_00430, llu:AKJ09_08721) (llu:AKJ09_00430, llu:AKJ09_10708) (llu:AKJ09_00583, llu:AKJ09_03976) (llu:AKJ09_00609, llu:AKJ09_05284) (llu:AKJ09_00609, llu:AKJ09_06932) (llu:AKJ09_00756, llu:AKJ09_09548) (llu:AKJ09_00929, llu:AKJ09_08845) (llu:AKJ09_00929, llu:AKJ09_09652) (llu:AKJ09_00976, llu:AKJ09_01814) (llu:AKJ09_00976, llu:AKJ09_01852) (llu:AKJ09_00976, llu:AKJ09_05466) (llu:AKJ09_00976, llu:AKJ09_07370) (llu:AKJ09_00976, llu:AKJ09_09565) (llu:AKJ09_00988, llu:AKJ09_10878) (llu:AKJ09_01024, llu:AKJ09_10129) (llu:AKJ09_01101, llu:AKJ09_02491) (llu:AKJ09_01219, llu:AKJ09_01359) (llu:AKJ09_01219, llu:AKJ09_01443) (llu:AKJ09_01219, llu:AKJ09_01932) (llu:AKJ09_01219, llu:AKJ09_02362) (llu:AKJ09_01219, llu:AKJ09_04925) (llu:AKJ09_01219, llu:AKJ09_10314) (llu:AKJ09_01219, llu:AKJ09_11473) (llu:AKJ09_01359, llu:AKJ09_01932) (llu:AKJ09_01359, llu:AKJ09_02362) (llu:AKJ09_01359, llu:AKJ09_10314) (llu:AKJ09_01359, llu:AKJ09_11473) (llu:AKJ09_01443, llu:AKJ09_01932) (llu:AKJ09_01443, llu:AKJ09_02362) (llu:AKJ09_01443, llu:AKJ09_04925) (llu:AKJ09_01443, llu:AKJ09_10314) (llu:AKJ09_01443, llu:AKJ09_11473) (llu:AKJ09_01492, llu:AKJ09_07273) (llu:AKJ09_01492, llu:AKJ09_08550) (llu:AKJ09_01495, llu:AKJ09_02991) (llu:AKJ09_01495, llu:AKJ09_05314) (llu:AKJ09_01495, llu:AKJ09_09399) (llu:AKJ09_01814, llu:AKJ09_01852) (llu:AKJ09_01814, llu:AKJ09_05466) (llu:AKJ09_01814, llu:AKJ09_09565) (llu:AKJ09_01841, llu:AKJ09_09395) (llu:AKJ09_01841, llu:AKJ09_10314) (llu:AKJ09_01852, llu:AKJ09_05466) (llu:AKJ09_01852, llu:AKJ09_09565) (llu:AKJ09_01880, llu:AKJ09_09477) (llu:AKJ09_01932, llu:AKJ09_02362) (llu:AKJ09_01932, llu:AKJ09_04925) (llu:AKJ09_01932, llu:AKJ09_10314) (llu:AKJ09_01932, llu:AKJ09_11473) (llu:AKJ09_02037, llu:AKJ09_07537) (llu:AKJ09_02362, llu:AKJ09_04925) (llu:AKJ09_02362, llu:AKJ09_07818) (llu:AKJ09_02362, llu:AKJ09_09395) (llu:AKJ09_02362, llu:AKJ09_10314) (llu:AKJ09_02362, llu:AKJ09_11473) (llu:AKJ09_02446, llu:AKJ09_09492) (llu:AKJ09_02465, llu:AKJ09_10313) (llu:AKJ09_02467, llu:AKJ09_05171) (llu:AKJ09_02467, llu:AKJ09_10310) (llu:AKJ09_02570, llu:AKJ09_06892) (llu:AKJ09_02591, llu:AKJ09_04506) (llu:AKJ09_02591, llu:AKJ09_06301) (llu:AKJ09_02591, llu:AKJ09_07318) (llu:AKJ09_02664, llu:AKJ09_04170) (llu:AKJ09_02664, llu:AKJ09_09576) (llu:AKJ09_02687, llu:AKJ09_10940) (llu:AKJ09_02763, llu:AKJ09_02816) (llu:AKJ09_02792, llu:AKJ09_05385) (llu:AKJ09_02792, llu:AKJ09_07279) (llu:AKJ09_02824, llu:AKJ09_11361) (llu:AKJ09_02949, llu:AKJ09_09992) (llu:AKJ09_02979, llu:AKJ09_10337) (llu:AKJ09_02991, llu:AKJ09_05314) (llu:AKJ09_02991, llu:AKJ09_09399) (llu:AKJ09_03084, llu:AKJ09_09654) (llu:AKJ09_03136, llu:AKJ09_03141) (llu:AKJ09_03445, llu:AKJ09_09838) (llu:AKJ09_03567, llu:AKJ09_04767) (llu:AKJ09_03571, llu:AKJ09_06135) (llu:AKJ09_04170, llu:AKJ09_09576) (llu:AKJ09_04246, llu:AKJ09_04918) (llu:AKJ09_04269, llu:AKJ09_10333) (llu:AKJ09_04272, llu:AKJ09_10397) (llu:AKJ09_04281, llu:AKJ09_09908) (llu:AKJ09_04504, llu:AKJ09_06902) (llu:AKJ09_04506, llu:AKJ09_06301) (llu:AKJ09_04506, llu:AKJ09_07318) (llu:AKJ09_04690, llu:AKJ09_04691) (llu:AKJ09_04777, llu:AKJ09_05088) (llu:AKJ09_04777, llu:AKJ09_07825) (llu:AKJ09_04857, llu:AKJ09_08807) (llu:AKJ09_04925, llu:AKJ09_07818) (llu:AKJ09_04925, llu:AKJ09_09395) (llu:AKJ09_04925, llu:AKJ09_10314) (llu:AKJ09_04925, llu:AKJ09_11473) (llu:AKJ09_05088, llu:AKJ09_05091) (llu:AKJ09_05088, llu:AKJ09_07825) (llu:AKJ09_05171, llu:AKJ09_06116) (llu:AKJ09_05171, llu:AKJ09_08280) (llu:AKJ09_05171, llu:AKJ09_08589) (llu:AKJ09_05171, llu:AKJ09_10310) (llu:AKJ09_05284, llu:AKJ09_06932) (llu:AKJ09_05314, llu:AKJ09_09399) (llu:AKJ09_05385, llu:AKJ09_07279) (llu:AKJ09_05466, llu:AKJ09_06149) (llu:AKJ09_05466, llu:AKJ09_07370) (llu:AKJ09_05466, llu:AKJ09_09565) (llu:AKJ09_05499, llu:AKJ09_08079) (llu:AKJ09_05604, llu:AKJ09_10077) (llu:AKJ09_05604, llu:AKJ09_11361) (llu:AKJ09_05672, llu:AKJ09_06311) (llu:AKJ09_05672, llu:AKJ09_09034) (llu:AKJ09_05860, llu:AKJ09_11455) (llu:AKJ09_05861, llu:AKJ09_08207) (llu:AKJ09_05870, llu:AKJ09_08543) (llu:AKJ09_05870, llu:AKJ09_11129) (llu:AKJ09_06116, llu:AKJ09_08280) (llu:AKJ09_06116, llu:AKJ09_08589) (llu:AKJ09_06116, llu:AKJ09_10310) (llu:AKJ09_06149, llu:AKJ09_07370) (llu:AKJ09_06301, llu:AKJ09_07318) (llu:AKJ09_06311, llu:AKJ09_07946) (llu:AKJ09_06311, llu:AKJ09_09034) (llu:AKJ09_07273, llu:AKJ09_08550) (llu:AKJ09_07617, llu:AKJ09_08666) (llu:AKJ09_07617, llu:AKJ09_08721) (llu:AKJ09_07617, llu:AKJ09_10708) (llu:AKJ09_07685, llu:AKJ09_08366) (llu:AKJ09_07813, llu:AKJ09_08204) (llu:AKJ09_07814, llu:AKJ09_08130) (llu:AKJ09_07818, llu:AKJ09_10314) (llu:AKJ09_07818, llu:AKJ09_11473) (llu:AKJ09_07946, llu:AKJ09_09034) (llu:AKJ09_07972, llu:AKJ09_11102) (llu:AKJ09_08130, llu:AKJ09_08203) (llu:AKJ09_08280, llu:AKJ09_08589) (llu:AKJ09_08280, llu:AKJ09_10310) (llu:AKJ09_08401, llu:AKJ09_09066) (llu:AKJ09_08401, llu:AKJ09_09070) (llu:AKJ09_08434, llu:AKJ09_08436) (llu:AKJ09_08434, llu:AKJ09_08893) (llu:AKJ09_08434, llu:AKJ09_10316) (llu:AKJ09_08434, llu:AKJ09_10666) (llu:AKJ09_08436, llu:AKJ09_08893) (llu:AKJ09_08436, llu:AKJ09_10316) (llu:AKJ09_08436, llu:AKJ09_10666) (llu:AKJ09_08534, llu:AKJ09_10905) (llu:AKJ09_08543, llu:AKJ09_11129) (llu:AKJ09_08589, llu:AKJ09_10310) (llu:AKJ09_08666, llu:AKJ09_08721) (llu:AKJ09_08666, llu:AKJ09_10708) (llu:AKJ09_08711, llu:AKJ09_10720) (llu:AKJ09_08721, llu:AKJ09_10708) (llu:AKJ09_08845, llu:AKJ09_09652) (llu:AKJ09_08892, llu:AKJ09_08893) (llu:AKJ09_08892, llu:AKJ09_10316) (llu:AKJ09_08892, llu:AKJ09_10666) (llu:AKJ09_08893, llu:AKJ09_10316) (llu:AKJ09_08893, llu:AKJ09_10666) (llu:AKJ09_08899, llu:AKJ09_10905) (llu:AKJ09_09066, llu:AKJ09_09070) (llu:AKJ09_09395, llu:AKJ09_10314) (llu:AKJ09_09446, llu:AKJ09_11379) (llu:AKJ09_09653, llu:AKJ09_09654) (llu:AKJ09_09735, llu:AKJ09_10188) (llu:AKJ09_09735, llu:AKJ09_10739) (llu:AKJ09_10188, llu:AKJ09_10739) (llu:AKJ09_10314, llu:AKJ09_11473) (llu:AKJ09_10316, llu:AKJ09_10666) (mbd:MEBOL_000129, mbd:MEBOL_002196) (mbd:MEBOL_000129, mbd:MEBOL_003801) (mbd:MEBOL_000129, mbd:MEBOL_005988) (mbd:MEBOL_000129, mbd:MEBOL_007910) (mbd:MEBOL_000187, mbd:MEBOL_003207) (mbd:MEBOL_000187, mbd:MEBOL_004288) (mbd:MEBOL_000191, mbd:MEBOL_005729) (mbd:MEBOL_000258, mbd:MEBOL_005248) (mbd:MEBOL_000259, mbd:MEBOL_002466) (mbd:MEBOL_000279, mbd:MEBOL_004899) (mbd:MEBOL_000359, mbd:MEBOL_005201) (mbd:MEBOL_000546, mbd:MEBOL_004742) (mbd:MEBOL_000633, mbd:MEBOL_002331) (mbd:MEBOL_000633, mbd:MEBOL_002469) (mbd:MEBOL_000658, mbd:MEBOL_002086) (mbd:MEBOL_000709, mbd:MEBOL_005163) (mbd:MEBOL_000749, mbd:MEBOL_004362) (mbd:MEBOL_000749, mbd:MEBOL_005080) (mbd:MEBOL_000749, mbd:MEBOL_008059) (mbd:MEBOL_000779, mbd:MEBOL_005961) (mbd:MEBOL_000837, mbd:MEBOL_003186) (mbd:MEBOL_000837, mbd:MEBOL_003365) (mbd:MEBOL_000837, mbd:MEBOL_005346) (mbd:MEBOL_000837, mbd:MEBOL_006810) (mbd:MEBOL_000837, mbd:MEBOL_006971) (mbd:MEBOL_000907, mbd:MEBOL_005217) (mbd:MEBOL_000935, mbd:MEBOL_003654) (mbd:MEBOL_000935, mbd:MEBOL_007806) (mbd:MEBOL_000951, mbd:MEBOL_002586) (mbd:MEBOL_001212, mbd:MEBOL_002076) (mbd:MEBOL_001212, mbd:MEBOL_003120) (mbd:MEBOL_001212, mbd:MEBOL_003524) (mbd:MEBOL_001212, mbd:MEBOL_004866) (mbd:MEBOL_001212, mbd:MEBOL_005276) (mbd:MEBOL_001262, mbd:MEBOL_001387) (mbd:MEBOL_001262, mbd:MEBOL_006356) (mbd:MEBOL_001387, mbd:MEBOL_001640) (mbd:MEBOL_001387, mbd:MEBOL_004626) (mbd:MEBOL_001387, mbd:MEBOL_006356) (mbd:MEBOL_001393, mbd:MEBOL_006939) (mbd:MEBOL_001459, mbd:MEBOL_006635) (mbd:MEBOL_001626, mbd:MEBOL_006697) (mbd:MEBOL_001640, mbd:MEBOL_004626) (mbd:MEBOL_001640, mbd:MEBOL_006356) (mbd:MEBOL_001826, mbd:MEBOL_006201) (mbd:MEBOL_001876, mbd:MEBOL_006515) (mbd:MEBOL_001876, mbd:MEBOL_007650) (mbd:MEBOL_001936, mbd:MEBOL_006847) (mbd:MEBOL_002073, mbd:MEBOL_007696) (mbd:MEBOL_002076, mbd:MEBOL_003120) (mbd:MEBOL_002076, mbd:MEBOL_003524) (mbd:MEBOL_002076, mbd:MEBOL_004866) (mbd:MEBOL_002076, mbd:MEBOL_005276) (mbd:MEBOL_002081, mbd:MEBOL_002622) (mbd:MEBOL_002081, mbd:MEBOL_005080) (mbd:MEBOL_002081, mbd:MEBOL_008059) (mbd:MEBOL_002196, mbd:MEBOL_003801) (mbd:MEBOL_002196, mbd:MEBOL_007910) (mbd:MEBOL_002331, mbd:MEBOL_002469) (mbd:MEBOL_002332, mbd:MEBOL_004464) (mbd:MEBOL_002444, mbd:MEBOL_006356) (mbd:MEBOL_002467, mbd:MEBOL_007199) (mbd:MEBOL_002467, mbd:MEBOL_007247) (mbd:MEBOL_002622, mbd:MEBOL_005080) (mbd:MEBOL_002622, mbd:MEBOL_008059) (mbd:MEBOL_002704, mbd:MEBOL_002972) (mbd:MEBOL_002704, mbd:MEBOL_003044) (mbd:MEBOL_002704, mbd:MEBOL_004723) (mbd:MEBOL_002704, mbd:MEBOL_005964) (mbd:MEBOL_002704, mbd:MEBOL_007830) (mbd:MEBOL_002843, mbd:MEBOL_005688) (mbd:MEBOL_002893, mbd:MEBOL_004287) (mbd:MEBOL_002972, mbd:MEBOL_003044) (mbd:MEBOL_002972, mbd:MEBOL_004723) (mbd:MEBOL_002972, mbd:MEBOL_005964) (mbd:MEBOL_002972, mbd:MEBOL_007830) (mbd:MEBOL_003044, mbd:MEBOL_003610) (mbd:MEBOL_003044, mbd:MEBOL_004723) (mbd:MEBOL_003044, mbd:MEBOL_005964) (mbd:MEBOL_003044, mbd:MEBOL_007830) (mbd:MEBOL_003120, mbd:MEBOL_003524) (mbd:MEBOL_003120, mbd:MEBOL_004866) (mbd:MEBOL_003120, mbd:MEBOL_005276) (mbd:MEBOL_003149, mbd:MEBOL_006208) (mbd:MEBOL_003186, mbd:MEBOL_003365) (mbd:MEBOL_003186, mbd:MEBOL_005346) (mbd:MEBOL_003186, mbd:MEBOL_005347) (mbd:MEBOL_003186, mbd:MEBOL_006810) (mbd:MEBOL_003186, mbd:MEBOL_006971) (mbd:MEBOL_003195, mbd:MEBOL_005966) (mbd:MEBOL_003207, mbd:MEBOL_004288) (mbd:MEBOL_003365, mbd:MEBOL_005346) (mbd:MEBOL_003365, mbd:MEBOL_006810) (mbd:MEBOL_003365, mbd:MEBOL_006971) (mbd:MEBOL_003524, mbd:MEBOL_004866) (mbd:MEBOL_003524, mbd:MEBOL_005276) (mbd:MEBOL_003610, mbd:MEBOL_004723) (mbd:MEBOL_003610, mbd:MEBOL_005964) (mbd:MEBOL_003612, mbd:MEBOL_005962) (mbd:MEBOL_003654, mbd:MEBOL_007806) (mbd:MEBOL_003759, mbd:MEBOL_003822) (mbd:MEBOL_003801, mbd:MEBOL_005988) (mbd:MEBOL_003801, mbd:MEBOL_007910) (mbd:MEBOL_003817, mbd:MEBOL_004536) (mbd:MEBOL_004017, mbd:MEBOL_007718) (mbd:MEBOL_004362, mbd:MEBOL_005080) (mbd:MEBOL_004362, mbd:MEBOL_008059) (mbd:MEBOL_004403, mbd:MEBOL_006600) (mbd:MEBOL_004403, mbd:MEBOL_007560) (mbd:MEBOL_004563, mbd:MEBOL_004893) (mbd:MEBOL_004613, mbd:MEBOL_006920) (mbd:MEBOL_004626, mbd:MEBOL_006356) (mbd:MEBOL_004723, mbd:MEBOL_005964) (mbd:MEBOL_004723, mbd:MEBOL_007830) (mbd:MEBOL_004866, mbd:MEBOL_005276) (mbd:MEBOL_004988, mbd:MEBOL_006600) (mbd:MEBOL_005080, mbd:MEBOL_008059) (mbd:MEBOL_005217, mbd:MEBOL_006623) (mbd:MEBOL_005346, mbd:MEBOL_006971) (mbd:MEBOL_005347, mbd:MEBOL_006810) (mbd:MEBOL_005347, mbd:MEBOL_006971) (mbd:MEBOL_005452, mbd:MEBOL_006903) (mbd:MEBOL_005477, mbd:MEBOL_007719) (mbd:MEBOL_005679, mbd:MEBOL_007750) (mbd:MEBOL_005896, mbd:MEBOL_006725) (mbd:MEBOL_005963, mbd:MEBOL_006606) (mbd:MEBOL_005964, mbd:MEBOL_007830) (mbd:MEBOL_005988, mbd:MEBOL_007910) (mbd:MEBOL_006001, mbd:MEBOL_008079) (mbd:MEBOL_006515, mbd:MEBOL_007650) (mbd:MEBOL_006600, mbd:MEBOL_007560) (mbd:MEBOL_006810, mbd:MEBOL_006971) (mbd:MEBOL_006836, mbd:MEBOL_006837) (mbd:MEBOL_006836, mbd:MEBOL_007979) (mbd:MEBOL_006837, mbd:MEBOL_007627) (mbd:MEBOL_006837, mbd:MEBOL_007979) (mbd:MEBOL_006840, mbd:MEBOL_007700) (mbd:MEBOL_007199, mbd:MEBOL_007247) (mbd:MEBOL_007627, mbd:MEBOL_007979) (mbd:MEBOL_007699, mbd:MEBOL_007805) (mfu:LILAB_00500, mfu:LILAB_03385) (mfu:LILAB_00760, mfu:LILAB_17540) (mfu:LILAB_00760, mfu:LILAB_28260) (mfu:LILAB_00790, mfu:LILAB_15915) (mfu:LILAB_00885, mfu:LILAB_03750) (mfu:LILAB_00885, mfu:LILAB_29010) (mfu:LILAB_01140, mfu:LILAB_11470) (mfu:LILAB_01140, mfu:LILAB_20360) (mfu:LILAB_01140, mfu:LILAB_22525) (mfu:LILAB_01140, mfu:LILAB_25560) (mfu:LILAB_01545, mfu:LILAB_10705) (mfu:LILAB_01860, mfu:LILAB_03115) (mfu:LILAB_01980, mfu:LILAB_06150) (mfu:LILAB_01980, mfu:LILAB_08200) (mfu:LILAB_01980, mfu:LILAB_14400) (mfu:LILAB_01980, mfu:LILAB_14860) (mfu:LILAB_02370, mfu:LILAB_21070) (mfu:LILAB_03490, mfu:LILAB_14035) (mfu:LILAB_03630, mfu:LILAB_08110) (mfu:LILAB_03750, mfu:LILAB_29010) (mfu:LILAB_04135, mfu:LILAB_11935) (mfu:LILAB_04135, mfu:LILAB_31800) (mfu:LILAB_04155, mfu:LILAB_35630) (mfu:LILAB_04510, mfu:LILAB_07620) (mfu:LILAB_06150, mfu:LILAB_08200) (mfu:LILAB_06150, mfu:LILAB_14400) (mfu:LILAB_06150, mfu:LILAB_14860) (mfu:LILAB_06190, mfu:LILAB_24705) (mfu:LILAB_06660, mfu:LILAB_25565) (mfu:LILAB_06720, mfu:LILAB_07065) (mfu:LILAB_06880, mfu:LILAB_15365) (mfu:LILAB_06880, mfu:LILAB_30430) (mfu:LILAB_06880, mfu:LILAB_31675) (mfu:LILAB_07165, mfu:LILAB_21465) (mfu:LILAB_07270, mfu:LILAB_29235) (mfu:LILAB_07680, mfu:LILAB_31800) (mfu:LILAB_07990, mfu:LILAB_24435) (mfu:LILAB_07990, mfu:LILAB_27945) (mfu:LILAB_08200, mfu:LILAB_14400) (mfu:LILAB_08200, mfu:LILAB_14860) (mfu:LILAB_09240, mfu:LILAB_29200) (mfu:LILAB_10620, mfu:LILAB_33330) (mfu:LILAB_11470, mfu:LILAB_20360) (mfu:LILAB_11470, mfu:LILAB_22525) (mfu:LILAB_11470, mfu:LILAB_25560) (mfu:LILAB_11935, mfu:LILAB_31800) (mfu:LILAB_12180, mfu:LILAB_15700) (mfu:LILAB_14400, mfu:LILAB_14860) (mfu:LILAB_14960, mfu:LILAB_25545) (mfu:LILAB_15365, mfu:LILAB_30430) (mfu:LILAB_15365, mfu:LILAB_31675) (mfu:LILAB_16115, mfu:LILAB_20770) (mfu:LILAB_16510, mfu:LILAB_28665) (mfu:LILAB_16510, mfu:LILAB_35470) (mfu:LILAB_16510, mfu:LILAB_36195) (mfu:LILAB_16625, mfu:LILAB_19495) (mfu:LILAB_17495, mfu:LILAB_21705) (mfu:LILAB_17540, mfu:LILAB_28260) (mfu:LILAB_19465, mfu:LILAB_25930) (mfu:LILAB_20360, mfu:LILAB_22525) (mfu:LILAB_20360, mfu:LILAB_25560) (mfu:LILAB_20395, mfu:LILAB_31810) (mfu:LILAB_22395, mfu:LILAB_33165) (mfu:LILAB_22525, mfu:LILAB_25560) (mfu:LILAB_22655, mfu:LILAB_32910) (mfu:LILAB_24435, mfu:LILAB_27945) (mfu:LILAB_24435, mfu:LILAB_35365) (mfu:LILAB_24700, mfu:LILAB_34620) (mfu:LILAB_24705, mfu:LILAB_28305) (mfu:LILAB_25075, mfu:LILAB_32345) (mfu:LILAB_25505, mfu:LILAB_25510) (mfu:LILAB_25505, mfu:LILAB_28080) (mfu:LILAB_25505, mfu:LILAB_31010) (mfu:LILAB_25510, mfu:LILAB_28080) (mfu:LILAB_25510, mfu:LILAB_31010) (mfu:LILAB_27945, mfu:LILAB_35365) (mfu:LILAB_28080, mfu:LILAB_31010) (mfu:LILAB_28305, mfu:LILAB_29280) (mfu:LILAB_28665, mfu:LILAB_35470) (mfu:LILAB_28665, mfu:LILAB_36195) (mfu:LILAB_29975, mfu:LILAB_31800) (mfu:LILAB_30430, mfu:LILAB_31675) (mfu:LILAB_31365, mfu:LILAB_31605) (mfu:LILAB_35470, mfu:LILAB_36195) (mfu:LILAB_35480, mfu:LILAB_35505) (mmas:MYMAC_000124, mmas:MYMAC_000552) (mmas:MYMAC_000124, mmas:MYMAC_001355) (mmas:MYMAC_000124, mmas:MYMAC_006053) (mmas:MYMAC_000124, mmas:MYMAC_006137) (mmas:MYMAC_000161, mmas:MYMAC_003287) (mmas:MYMAC_000161, mmas:MYMAC_003879) (mmas:MYMAC_000220, mmas:MYMAC_004668) (mmas:MYMAC_000232, mmas:MYMAC_000869) (mmas:MYMAC_000305, mmas:MYMAC_004129) (mmas:MYMAC_000327, mmas:MYMAC_002715) (mmas:MYMAC_000346, mmas:MYMAC_000432) (mmas:MYMAC_000385, mmas:MYMAC_004643) (mmas:MYMAC_000385, mmas:MYMAC_005959) (mmas:MYMAC_000444, mmas:MYMAC_003460) (mmas:MYMAC_000545, mmas:MYMAC_003338) (mmas:MYMAC_000552, mmas:MYMAC_001355) (mmas:MYMAC_000552, mmas:MYMAC_006053) (mmas:MYMAC_000552, mmas:MYMAC_006137) (mmas:MYMAC_000935, mmas:MYMAC_005425) (mmas:MYMAC_000937, mmas:MYMAC_004291) (mmas:MYMAC_000937, mmas:MYMAC_004668) (mmas:MYMAC_000937, mmas:MYMAC_006600) (mmas:MYMAC_001009, mmas:MYMAC_001692) (mmas:MYMAC_001009, mmas:MYMAC_004085) (mmas:MYMAC_001062, mmas:MYMAC_006204) (mmas:MYMAC_001081, mmas:MYMAC_001767) (mmas:MYMAC_001135, mmas:MYMAC_001379) (mmas:MYMAC_001273, mmas:MYMAC_002638) (mmas:MYMAC_001355, mmas:MYMAC_006053) (mmas:MYMAC_001355, mmas:MYMAC_006137) (mmas:MYMAC_001440, mmas:MYMAC_006837) (mmas:MYMAC_001577, mmas:MYMAC_001939) (mmas:MYMAC_001644, mmas:MYMAC_002498) (mmas:MYMAC_001644, mmas:MYMAC_002908) (mmas:MYMAC_001644, mmas:MYMAC_003459) (mmas:MYMAC_001644, mmas:MYMAC_006691) (mmas:MYMAC_001692, mmas:MYMAC_004085) (mmas:MYMAC_001711, mmas:MYMAC_005856) (mmas:MYMAC_001717, mmas:MYMAC_002002) (mmas:MYMAC_001717, mmas:MYMAC_003937) (mmas:MYMAC_001988, mmas:MYMAC_002764) (mmas:MYMAC_002002, mmas:MYMAC_003937) (mmas:MYMAC_002320, mmas:MYMAC_003532) (mmas:MYMAC_002326, mmas:MYMAC_005716) (mmas:MYMAC_002498, mmas:MYMAC_002908) (mmas:MYMAC_002498, mmas:MYMAC_003459) (mmas:MYMAC_002498, mmas:MYMAC_006691) (mmas:MYMAC_002505, mmas:MYMAC_004670) (mmas:MYMAC_002881, mmas:MYMAC_004931) (mmas:MYMAC_002908, mmas:MYMAC_003459) (mmas:MYMAC_002908, mmas:MYMAC_006691) (mmas:MYMAC_002933, mmas:MYMAC_004879) (mmas:MYMAC_003287, mmas:MYMAC_003879) (mmas:MYMAC_003287, mmas:MYMAC_005375) (mmas:MYMAC_003337, mmas:MYMAC_005218) (mmas:MYMAC_003338, mmas:MYMAC_003947) (mmas:MYMAC_003407, mmas:MYMAC_004768) (mmas:MYMAC_003448, mmas:MYMAC_003449) (mmas:MYMAC_003448, mmas:MYMAC_003905) (mmas:MYMAC_003448, mmas:MYMAC_004501) (mmas:MYMAC_003449, mmas:MYMAC_003905) (mmas:MYMAC_003449, mmas:MYMAC_004501) (mmas:MYMAC_003456, mmas:MYMAC_006033) (mmas:MYMAC_003459, mmas:MYMAC_006691) (mmas:MYMAC_003879, mmas:MYMAC_005375) (mmas:MYMAC_003905, mmas:MYMAC_004501) (mmas:MYMAC_003947, mmas:MYMAC_004138) (mmas:MYMAC_004020, mmas:MYMAC_005396) (mmas:MYMAC_004020, mmas:MYMAC_005532) (mmas:MYMAC_004020, mmas:MYMAC_005739) (mmas:MYMAC_004122, mmas:MYMAC_007137) (mmas:MYMAC_004291, mmas:MYMAC_004668) (mmas:MYMAC_004575, mmas:MYMAC_004629) (mmas:MYMAC_004643, mmas:MYMAC_005959) (mmas:MYMAC_004668, mmas:MYMAC_006600) (mmas:MYMAC_004962, mmas:MYMAC_006854) (mmas:MYMAC_005396, mmas:MYMAC_005532) (mmas:MYMAC_005396, mmas:MYMAC_005739) (mmas:MYMAC_005398, mmas:MYMAC_005403) (mmas:MYMAC_005403, mmas:MYMAC_005404) (mmas:MYMAC_005532, mmas:MYMAC_005739) (mmas:MYMAC_005899, mmas:MYMAC_006554) (mmas:MYMAC_006053, mmas:MYMAC_006137) (mrm:A7982_00131, mrm:A7982_08578) (mrm:A7982_00170, mrm:A7982_01282) (mrm:A7982_00170, mrm:A7982_03403) (mrm:A7982_00170, mrm:A7982_04986) (mrm:A7982_00170, mrm:A7982_07818) (mrm:A7982_00170, mrm:A7982_09670) (mrm:A7982_00170, mrm:A7982_11353) (mrm:A7982_00288, mrm:A7982_05215) (mrm:A7982_00296, mrm:A7982_02950) (mrm:A7982_00296, mrm:A7982_05341) (mrm:A7982_00296, mrm:A7982_10667) (mrm:A7982_00309, mrm:A7982_09578) (mrm:A7982_00315, mrm:A7982_11144) (mrm:A7982_00371, mrm:A7982_04801) (mrm:A7982_00419, mrm:A7982_06545) (mrm:A7982_00419, mrm:A7982_06712) (mrm:A7982_00419, mrm:A7982_06716) (mrm:A7982_00419, mrm:A7982_08550) (mrm:A7982_00443, mrm:A7982_08822) (mrm:A7982_00857, mrm:A7982_01558) (mrm:A7982_00857, mrm:A7982_10241) (mrm:A7982_01128, mrm:A7982_02037) (mrm:A7982_01149, mrm:A7982_09970) (mrm:A7982_01228, mrm:A7982_02950) (mrm:A7982_01228, mrm:A7982_09573) (mrm:A7982_01282, mrm:A7982_03403) (mrm:A7982_01282, mrm:A7982_04986) (mrm:A7982_01282, mrm:A7982_07818) (mrm:A7982_01282, mrm:A7982_09670) (mrm:A7982_01282, mrm:A7982_11353) (mrm:A7982_01283, mrm:A7982_02966) (mrm:A7982_01283, mrm:A7982_04984) (mrm:A7982_01283, mrm:A7982_07817) (mrm:A7982_01283, mrm:A7982_12232) (mrm:A7982_01358, mrm:A7982_09718) (mrm:A7982_01390, mrm:A7982_02966) (mrm:A7982_01390, mrm:A7982_04984) (mrm:A7982_01390, mrm:A7982_05137) (mrm:A7982_01390, mrm:A7982_09318) (mrm:A7982_01390, mrm:A7982_12232) (mrm:A7982_01558, mrm:A7982_10241) (mrm:A7982_01769, mrm:A7982_02481) (mrm:A7982_01769, mrm:A7982_05402) (mrm:A7982_01898, mrm:A7982_07497) (mrm:A7982_01898, mrm:A7982_07501) (mrm:A7982_02117, mrm:A7982_12858) (mrm:A7982_02117, mrm:A7982_13556) (mrm:A7982_02397, mrm:A7982_02930) (mrm:A7982_02397, mrm:A7982_12819) (mrm:A7982_02481, mrm:A7982_05182) (mrm:A7982_02481, mrm:A7982_05402) (mrm:A7982_02481, mrm:A7982_05891) (mrm:A7982_02481, mrm:A7982_09160) (mrm:A7982_02519, mrm:A7982_02766) (mrm:A7982_02519, mrm:A7982_07443) (mrm:A7982_02519, mrm:A7982_08337) (mrm:A7982_02519, mrm:A7982_09042) (mrm:A7982_02519, mrm:A7982_09539) (mrm:A7982_02611, mrm:A7982_07040) (mrm:A7982_02751, mrm:A7982_09898) (mrm:A7982_02766, mrm:A7982_05339) (mrm:A7982_02766, mrm:A7982_07443) (mrm:A7982_02766, mrm:A7982_07690) (mrm:A7982_02766, mrm:A7982_08337) (mrm:A7982_02766, mrm:A7982_09042) (mrm:A7982_02766, mrm:A7982_09539) (mrm:A7982_02766, mrm:A7982_10601) (mrm:A7982_02766, mrm:A7982_12872) (mrm:A7982_02846, mrm:A7982_12969) (mrm:A7982_02892, mrm:A7982_03222) (mrm:A7982_02930, mrm:A7982_12819) (mrm:A7982_02946, mrm:A7982_06799) (mrm:A7982_02947, mrm:A7982_04886) (mrm:A7982_02947, mrm:A7982_06799) (mrm:A7982_02950, mrm:A7982_05341) (mrm:A7982_02950, mrm:A7982_08818) (mrm:A7982_02950, mrm:A7982_09573) (mrm:A7982_02950, mrm:A7982_10667) (mrm:A7982_02950, mrm:A7982_13482) (mrm:A7982_02966, mrm:A7982_04984) (mrm:A7982_02966, mrm:A7982_05137) (mrm:A7982_02966, mrm:A7982_07817) (mrm:A7982_02966, mrm:A7982_08798) (mrm:A7982_02966, mrm:A7982_09318) (mrm:A7982_02966, mrm:A7982_12232) (mrm:A7982_03001, mrm:A7982_04312) (mrm:A7982_03001, mrm:A7982_10763) (mrm:A7982_03017, mrm:A7982_08253) (mrm:A7982_03046, mrm:A7982_03371) (mrm:A7982_03046, mrm:A7982_06576) (mrm:A7982_03051, mrm:A7982_06344) (mrm:A7982_03225, mrm:A7982_05274) (mrm:A7982_03238, mrm:A7982_03263) (mrm:A7982_03238, mrm:A7982_08416) (mrm:A7982_03263, mrm:A7982_08416) (mrm:A7982_03263, mrm:A7982_08417) (mrm:A7982_03371, mrm:A7982_06576) (mrm:A7982_03403, mrm:A7982_04986) (mrm:A7982_03403, mrm:A7982_07818) (mrm:A7982_03403, mrm:A7982_09670) (mrm:A7982_03403, mrm:A7982_11353) (mrm:A7982_03732, mrm:A7982_05342) (mrm:A7982_04070, mrm:A7982_09588) (mrm:A7982_04070, 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(pprf:DPRO_1502, pprf:DPRO_2174) (pprf:DPRO_1557, pprf:DPRO_2629) (pprf:DPRO_1577, pprf:DPRO_2329) (pprf:DPRO_1581, pprf:DPRO_4008) (pprf:DPRO_1583, pprf:DPRO_2705) (pprf:DPRO_1586, pprf:DPRO_2330) (pprf:DPRO_1802, pprf:DPRO_2174) (pprf:DPRO_1856, pprf:DPRO_2030) (pprf:DPRO_1856, pprf:DPRO_2643) (pprf:DPRO_2030, pprf:DPRO_2643) (pprf:DPRO_2239, pprf:DPRO_3321) (pprf:DPRO_2275, pprf:DPRO_3102) (pprf:DPRO_2444, pprf:DPRO_2976) (pprf:DPRO_2470, pprf:DPRO_2602) (pprf:DPRO_2555, pprf:DPRO_3829) (pprf:DPRO_2638, pprf:DPRO_3025) (pprf:DPRO_2839, pprf:DPRO_2881) (pprf:DPRO_3102, pprf:DPRO_3768) (pprf:DPRO_3319, pprf:DPRO_3425) (samy:DB32_000011, samy:DB32_008540) (samy:DB32_000011, samy:DB32_008959) (samy:DB32_000113, samy:DB32_006304) (samy:DB32_000113, samy:DB32_008649) (samy:DB32_000113, samy:DB32_008650) (samy:DB32_000220, samy:DB32_001412) (samy:DB32_000220, samy:DB32_001928) (samy:DB32_000220, samy:DB32_002239) (samy:DB32_000220, samy:DB32_003887) (samy:DB32_000279, samy:DB32_000657) (samy:DB32_000279, samy:DB32_001409) (samy:DB32_000279, samy:DB32_003889) (samy:DB32_000279, samy:DB32_004662) (samy:DB32_000329, samy:DB32_007373) (samy:DB32_000330, samy:DB32_005704) (samy:DB32_000455, samy:DB32_006503) (samy:DB32_000467, samy:DB32_004284) (samy:DB32_000470, samy:DB32_001908) (samy:DB32_000588, samy:DB32_004856) (samy:DB32_000588, samy:DB32_005289) (samy:DB32_000657, samy:DB32_001409) (samy:DB32_000657, samy:DB32_003889) (samy:DB32_000657, samy:DB32_004662) (samy:DB32_000680, samy:DB32_007648) (samy:DB32_000949, samy:DB32_001412) (samy:DB32_000949, samy:DB32_001928) (samy:DB32_000949, samy:DB32_002239) (samy:DB32_000949, samy:DB32_003887) (samy:DB32_000965, samy:DB32_004421) (samy:DB32_000992, samy:DB32_004319) (samy:DB32_001023, samy:DB32_005406) (samy:DB32_001141, samy:DB32_007188) (samy:DB32_001141, samy:DB32_007931) (samy:DB32_001141, samy:DB32_008367) (samy:DB32_001261, samy:DB32_008592) (samy:DB32_001353, samy:DB32_003546) (samy:DB32_001353, samy:DB32_006421) (samy:DB32_001409, samy:DB32_003889) (samy:DB32_001409, samy:DB32_004662) (samy:DB32_001412, samy:DB32_001928) (samy:DB32_001412, samy:DB32_002239) (samy:DB32_001412, samy:DB32_003887) (samy:DB32_001415, samy:DB32_002924) (samy:DB32_001613, samy:DB32_001636) (samy:DB32_001613, samy:DB32_004998) (samy:DB32_001613, samy:DB32_005885) (samy:DB32_001636, samy:DB32_004998) (samy:DB32_001636, samy:DB32_005885) (samy:DB32_001667, samy:DB32_002947) (samy:DB32_001708, samy:DB32_003678) (samy:DB32_001708, samy:DB32_005205) (samy:DB32_001770, samy:DB32_006309) (samy:DB32_001845, samy:DB32_004155) (samy:DB32_001928, samy:DB32_002239) (samy:DB32_001928, samy:DB32_003887) (samy:DB32_002077, samy:DB32_005118) (samy:DB32_002077, samy:DB32_007837) (samy:DB32_002225, samy:DB32_003101) (samy:DB32_002225, samy:DB32_003115) (samy:DB32_002225, samy:DB32_005212) (samy:DB32_002239, samy:DB32_003887) (samy:DB32_002265, samy:DB32_006894) (samy:DB32_002265, samy:DB32_008737) (samy:DB32_002497, samy:DB32_003877) (samy:DB32_002655, samy:DB32_004597) (samy:DB32_002852, samy:DB32_003477) (samy:DB32_002852, samy:DB32_003480) (samy:DB32_002852, samy:DB32_005734) (samy:DB32_002852, samy:DB32_007120) (samy:DB32_002852, samy:DB32_007268) (samy:DB32_002852, samy:DB32_007469) (samy:DB32_002852, samy:DB32_008364) (samy:DB32_002954, samy:DB32_008496) (samy:DB32_003077, samy:DB32_003961) (samy:DB32_003077, samy:DB32_003964) (samy:DB32_003077, samy:DB32_005101) (samy:DB32_003077, samy:DB32_006298) (samy:DB32_003101, samy:DB32_003115) (samy:DB32_003101, samy:DB32_005212) (samy:DB32_003115, samy:DB32_005212) (samy:DB32_003116, samy:DB32_007931) (samy:DB32_003116, samy:DB32_008367) (samy:DB32_003149, samy:DB32_005686) (samy:DB32_003166, samy:DB32_005700) (samy:DB32_003170, samy:DB32_004608) (samy:DB32_003477, samy:DB32_003480) (samy:DB32_003477, samy:DB32_005734) (samy:DB32_003477, samy:DB32_007120) (samy:DB32_003477, samy:DB32_007469) (samy:DB32_003477, samy:DB32_008364) (samy:DB32_003480, samy:DB32_005734) (samy:DB32_003480, samy:DB32_007120) (samy:DB32_003480, samy:DB32_007469) (samy:DB32_003480, samy:DB32_008364) (samy:DB32_003518, samy:DB32_007196) (samy:DB32_003546, samy:DB32_006421) (samy:DB32_003553, samy:DB32_003711) (samy:DB32_003553, samy:DB32_003728) (samy:DB32_003583, samy:DB32_004060) (samy:DB32_003678, samy:DB32_005205) (samy:DB32_003711, samy:DB32_003728) (samy:DB32_003841, samy:DB32_003842) (samy:DB32_003889, samy:DB32_004662) (samy:DB32_003941, samy:DB32_006326) (samy:DB32_003961, samy:DB32_003964) (samy:DB32_003961, samy:DB32_005101) (samy:DB32_003961, samy:DB32_006298) (samy:DB32_003964, samy:DB32_005101) (samy:DB32_003964, samy:DB32_006298) (samy:DB32_003973, samy:DB32_008649) (samy:DB32_004039, samy:DB32_004546) (samy:DB32_004093, samy:DB32_004711) (samy:DB32_004135, samy:DB32_004322) (samy:DB32_004135, samy:DB32_006581) (samy:DB32_004322, samy:DB32_006581) (samy:DB32_004394, samy:DB32_006869) (samy:DB32_004445, samy:DB32_004448) (samy:DB32_004856, samy:DB32_005289) (samy:DB32_004998, samy:DB32_005885) (samy:DB32_005052, samy:DB32_005931) (samy:DB32_005101, samy:DB32_006298) (samy:DB32_005105, samy:DB32_007124) (samy:DB32_005118, samy:DB32_007837) (samy:DB32_005118, samy:DB32_008655) (samy:DB32_005206, samy:DB32_005209) (samy:DB32_005206, samy:DB32_006761) (samy:DB32_005209, samy:DB32_006761) (samy:DB32_005734, samy:DB32_007120) (samy:DB32_005734, samy:DB32_007469) (samy:DB32_005734, samy:DB32_008364) (samy:DB32_005996, samy:DB32_008570) (samy:DB32_006304, samy:DB32_008650) (samy:DB32_006309, samy:DB32_006310) (samy:DB32_006894, samy:DB32_008737) (samy:DB32_007120, samy:DB32_007469) (samy:DB32_007120, samy:DB32_008364) (samy:DB32_007188, samy:DB32_007931) (samy:DB32_007188, samy:DB32_008367) (samy:DB32_007469, samy:DB32_008364) (samy:DB32_007585, samy:DB32_008421) (samy:DB32_007837, samy:DB32_008655) (samy:DB32_007931, samy:DB32_008367) (samy:DB32_008540, samy:DB32_008959) (samy:DB32_008649, samy:DB32_008650) (sat:SYN_00001, sat:SYN_02502) (sat:SYN_00075, sat:SYN_00446) (sat:SYN_00075, sat:SYN_01253) (sat:SYN_00075, sat:SYN_03026) (sat:SYN_00090, sat:SYN_02194) (sat:SYN_00163, sat:SYN_02985) (sat:SYN_00211, sat:SYN_02884) (sat:SYN_00231, sat:SYN_00298) (sat:SYN_00231, sat:SYN_02761) (sat:SYN_00231, sat:SYN_02880) (sat:SYN_00266, sat:SYN_00267) (sat:SYN_00266, sat:SYN_00272) (sat:SYN_00266, sat:SYN_02148) (sat:SYN_00267, sat:SYN_00272) (sat:SYN_00267, sat:SYN_02148) (sat:SYN_00272, sat:SYN_02148) (sat:SYN_00298, sat:SYN_01331) (sat:SYN_00298, sat:SYN_02600) (sat:SYN_00298, sat:SYN_02761) (sat:SYN_00298, sat:SYN_02880) (sat:SYN_00302, sat:SYN_00442) (sat:SYN_00381, sat:SYN_01960) (sat:SYN_00412, sat:SYN_01483) (sat:SYN_00424, sat:SYN_00729) (sat:SYN_00446, sat:SYN_01253) (sat:SYN_00583, sat:SYN_02563) (sat:SYN_00621, sat:SYN_00891) (sat:SYN_00621, sat:SYN_02641) (sat:SYN_00761, sat:SYN_01451) (sat:SYN_00891, sat:SYN_02641) (sat:SYN_00904, sat:SYN_01901) (sat:SYN_00907, sat:SYN_01624) (sat:SYN_00908, sat:SYN_02937) (sat:SYN_01112, sat:SYN_01130) (sat:SYN_01112, sat:SYN_02661) (sat:SYN_01112, sat:SYN_02866) (sat:SYN_01125, sat:SYN_01130) (sat:SYN_01125, sat:SYN_02661) (sat:SYN_01130, sat:SYN_02661) (sat:SYN_01130, sat:SYN_02866) (sat:SYN_01149, sat:SYN_01150) (sat:SYN_01164, sat:SYN_01517) (sat:SYN_01184, sat:SYN_01365) (sat:SYN_01184, sat:SYN_01577) (sat:SYN_01209, sat:SYN_01226) (sat:SYN_01223, sat:SYN_02635) (sat:SYN_01223, sat:SYN_02640) (sat:SYN_01223, sat:SYN_02643) (sat:SYN_01223, sat:SYN_03128) (sat:SYN_01231, sat:SYN_02496) (sat:SYN_01251, sat:SYN_02126) (sat:SYN_01258, sat:SYN_02758) (sat:SYN_01331, sat:SYN_02600) (sat:SYN_01331, sat:SYN_02761) (sat:SYN_01365, sat:SYN_01577) (sat:SYN_01451, sat:SYN_01684) (sat:SYN_01454, sat:SYN_02374) (sat:SYN_01454, sat:SYN_02886) (sat:SYN_01532, sat:SYN_02156) (sat:SYN_01625, sat:SYN_02589) (sat:SYN_01680, sat:SYN_01696) (sat:SYN_01680, sat:SYN_02127) (sat:SYN_01696, sat:SYN_02127) (sat:SYN_01710, sat:SYN_01712) (sat:SYN_01711, sat:SYN_01713) (sat:SYN_01711, sat:SYN_01965) (sat:SYN_01713, sat:SYN_01965) (sat:SYN_01740, sat:SYN_01747) (sat:SYN_01742, sat:SYN_01747) (sat:SYN_01942, sat:SYN_01988) (sat:SYN_01943, sat:SYN_02592) (sat:SYN_01944, sat:SYN_02591) (sat:SYN_01945, sat:SYN_02590) (sat:SYN_02188, sat:SYN_02538) (sat:SYN_02365, sat:SYN_02566) (sat:SYN_02374, sat:SYN_02886) (sat:SYN_02501, sat:SYN_03227) (sat:SYN_02535, sat:SYN_02602) (sat:SYN_02578, sat:SYN_02778) (sat:SYN_02635, sat:SYN_02640) (sat:SYN_02635, sat:SYN_02643) (sat:SYN_02635, sat:SYN_03128) (sat:SYN_02640, sat:SYN_02643) (sat:SYN_02640, sat:SYN_03128) (sat:SYN_02643, sat:SYN_03128) (sat:SYN_02661, sat:SYN_02866) (sat:SYN_02666, sat:SYN_02678) (scl:sce0088, scl:sce1032) (scl:sce0127, scl:sce7883) (scl:sce0176, scl:sce0253) (scl:sce0379, scl:sce3875) (scl:sce0564, scl:sce6856) (scl:sce0616, scl:sce5320) (scl:sce0693, scl:sce9167) (scl:sce0752, scl:sce5078) (scl:sce0903, scl:sce5271) (scl:sce0903, scl:sce8012) (scl:sce0903, scl:sce8696) (scl:sce1044, scl:sce4502) (scl:sce1063, scl:sce3161) (scl:sce1175, scl:sce8683) (scl:sce1213, scl:sce3817) (scl:sce1214, scl:sce3730) (scl:sce1214, scl:sce8127) (scl:sce1214, scl:sce8755) (scl:sce1639, scl:sce2226) (scl:sce1646, scl:sce3354) (scl:sce1646, scl:sce3815) (scl:sce1646, scl:sce5302) (scl:sce1736, scl:sce1738) (scl:sce1736, scl:sce8281) (scl:sce1738, scl:sce8281) (scl:sce2402, scl:sce9309) (scl:sce2526, scl:sce3351) (scl:sce2526, scl:sce3813) (scl:sce2526, scl:sce5922) (scl:sce2535, scl:sce6246) (scl:sce2535, scl:sce9261) (scl:sce2553, scl:sce6193) (scl:sce2600, scl:sce3817) (scl:sce2600, scl:sce5053) (scl:sce2813, scl:sce5886) (scl:sce3018, scl:sce3432) (scl:sce3018, scl:sce4359) (scl:sce3035, scl:sce6876) (scl:sce3187, scl:sce3826) (scl:sce3187, scl:sce4939) (scl:sce3187, scl:sce8804) (scl:sce3273, scl:sce3354) (scl:sce3273, scl:sce3815) (scl:sce3273, scl:sce5302) (scl:sce3351, scl:sce3813) (scl:sce3351, scl:sce5922) (scl:sce3354, scl:sce3815) (scl:sce3354, scl:sce5302) (scl:sce3432, scl:sce4359) (scl:sce3447, scl:sce3760) (scl:sce3526, scl:sce4640) (scl:sce3703, scl:sce7329) (scl:sce3730, scl:sce8127) (scl:sce3730, scl:sce8755) (scl:sce3733, scl:sce3734) (scl:sce3733, scl:sce4883) (scl:sce3733, scl:sce8174) (scl:sce3735, scl:sce8151) (scl:sce3813, scl:sce5922) (scl:sce3815, scl:sce5302) (scl:sce3817, scl:sce5053) (scl:sce3826, scl:sce4939) (scl:sce3826, scl:sce8804) (scl:sce3953, scl:sce7210) (scl:sce3987, scl:sce8467) (scl:sce4177, scl:sce4570) (scl:sce4177, scl:sce7847) (scl:sce4215, scl:sce8855) (scl:sce4215, scl:sce8915) (scl:sce4236, scl:sce5134) (scl:sce4236, scl:sce7417) (scl:sce4259, scl:sce4283) (scl:sce4320, scl:sce7407) (scl:sce4540, scl:sce5197) (scl:sce4570, scl:sce7847) (scl:sce4641, scl:sce4786) (scl:sce4641, scl:sce5753) (scl:sce4641, scl:sce5757) (scl:sce4641, scl:sce7375) (scl:sce4786, scl:sce5753) (scl:sce4786, scl:sce5757) (scl:sce4786, scl:sce7375) (scl:sce4939, scl:sce8804) (scl:sce5134, scl:sce7417) (scl:sce5271, scl:sce8012) (scl:sce5271, scl:sce8696) (scl:sce5556, scl:sce7038) (scl:sce5753, scl:sce5757) (scl:sce5753, scl:sce7375) (scl:sce5757, scl:sce7375) (scl:sce5871, scl:sce7733) (scl:sce6246, scl:sce9261) (scl:sce6540, scl:sce6934) (scl:sce7844, scl:sce8601) (scl:sce7844, scl:sce8917) (scl:sce7883, scl:sce8081) (scl:sce7883, scl:sce8230) (scl:sce7927, scl:sce8012) (scl:sce8012, scl:sce8696) (scl:sce8081, scl:sce8230) (scl:sce8127, scl:sce8755) (scl:sce8601, scl:sce8917) (scl:sce8671, scl:sce8676) (scl:sce8855, scl:sce8915) (scl:sce9115, scl:sce9130) (sfu:Sfum_0007, sfu:Sfum_0268) (sfu:Sfum_0007, sfu:Sfum_2580) (sfu:Sfum_0008, sfu:Sfum_3911) (sfu:Sfum_0062, sfu:Sfum_2090) (sfu:Sfum_0108, sfu:Sfum_0745) (sfu:Sfum_0108, sfu:Sfum_3454) (sfu:Sfum_0112, sfu:Sfum_1374) (sfu:Sfum_0113, sfu:Sfum_0933) (sfu:Sfum_0122, sfu:Sfum_0192) (sfu:Sfum_0122, sfu:Sfum_2084) (sfu:Sfum_0156, sfu:Sfum_2789) (sfu:Sfum_0179, sfu:Sfum_2264) (sfu:Sfum_0192, sfu:Sfum_2084) (sfu:Sfum_0296, sfu:Sfum_2981) (sfu:Sfum_0296, sfu:Sfum_2982) (sfu:Sfum_0296, sfu:Sfum_3023) (sfu:Sfum_0296, sfu:Sfum_3024) (sfu:Sfum_0379, sfu:Sfum_0382) (sfu:Sfum_0379, sfu:Sfum_1676) (sfu:Sfum_0379, sfu:Sfum_1683) (sfu:Sfum_0382, sfu:Sfum_1676) (sfu:Sfum_0382, sfu:Sfum_1683) (sfu:Sfum_0392, sfu:Sfum_0534) (sfu:Sfum_0478, sfu:Sfum_1634) (sfu:Sfum_0478, sfu:Sfum_2681) (sfu:Sfum_0483, sfu:Sfum_1215) (sfu:Sfum_0483, sfu:Sfum_3692) (sfu:Sfum_0605, sfu:Sfum_4095) (sfu:Sfum_0615, sfu:Sfum_1700) (sfu:Sfum_0615, sfu:Sfum_3076) (sfu:Sfum_0630, sfu:Sfum_0634) (sfu:Sfum_0630, sfu:Sfum_0649) (sfu:Sfum_0630, sfu:Sfum_2666) (sfu:Sfum_0634, sfu:Sfum_0649) (sfu:Sfum_0634, sfu:Sfum_2666) (sfu:Sfum_0649, sfu:Sfum_2666) (sfu:Sfum_0698, sfu:Sfum_1709) (sfu:Sfum_0745, sfu:Sfum_3454) (sfu:Sfum_0769, sfu:Sfum_1774) (sfu:Sfum_0841, sfu:Sfum_1844) (sfu:Sfum_0871, sfu:Sfum_1596) (sfu:Sfum_0934, sfu:Sfum_1376) (sfu:Sfum_0937, sfu:Sfum_1596) (sfu:Sfum_0983, sfu:Sfum_2111) (sfu:Sfum_1039, sfu:Sfum_2669) (sfu:Sfum_1171, sfu:Sfum_1665) (sfu:Sfum_1208, sfu:Sfum_3652) (sfu:Sfum_1215, sfu:Sfum_3692) (sfu:Sfum_1302, sfu:Sfum_1418) (sfu:Sfum_1375, sfu:Sfum_3714) (sfu:Sfum_1468, sfu:Sfum_2061) (sfu:Sfum_1468, sfu:Sfum_2062) (sfu:Sfum_1470, sfu:Sfum_2957) (sfu:Sfum_1475, sfu:Sfum_2959) (sfu:Sfum_1533, sfu:Sfum_2105) (sfu:Sfum_1538, sfu:Sfum_2262) (sfu:Sfum_1608, sfu:Sfum_3719) (sfu:Sfum_1676, sfu:Sfum_1683) (sfu:Sfum_1700, sfu:Sfum_3076) (sfu:Sfum_1771, sfu:Sfum_2404) (sfu:Sfum_1824, sfu:Sfum_3508) (sfu:Sfum_1913, sfu:Sfum_1953) (sfu:Sfum_2015, sfu:Sfum_2116) (sfu:Sfum_2061, sfu:Sfum_2062) (sfu:Sfum_2123, sfu:Sfum_3619) (sfu:Sfum_2263, sfu:Sfum_3965) (sfu:Sfum_2610, sfu:Sfum_3720) (sfu:Sfum_2645, sfu:Sfum_3549) (sfu:Sfum_2980, sfu:Sfum_2983) (sfu:Sfum_2980, sfu:Sfum_3022) (sfu:Sfum_2980, sfu:Sfum_3025) (sfu:Sfum_2981, sfu:Sfum_2982) (sfu:Sfum_2981, sfu:Sfum_3023) (sfu:Sfum_2981, sfu:Sfum_3024) (sfu:Sfum_2982, sfu:Sfum_3023) (sfu:Sfum_2982, sfu:Sfum_3024) (sfu:Sfum_2983, sfu:Sfum_3022) (sfu:Sfum_2983, sfu:Sfum_3025) (sfu:Sfum_2984, sfu:Sfum_3026) (sfu:Sfum_2985, sfu:Sfum_3027) (sfu:Sfum_2986, sfu:Sfum_3028) (sfu:Sfum_2989, sfu:Sfum_3031) (sfu:Sfum_2989, sfu:Sfum_3896) (sfu:Sfum_2990, sfu:Sfum_3032) (sfu:Sfum_2992, sfu:Sfum_3034) (sfu:Sfum_3010, sfu:Sfum_3052) (sfu:Sfum_3022, sfu:Sfum_3025) (sfu:Sfum_3023, sfu:Sfum_3024) (sfu:Sfum_3031, sfu:Sfum_3896) (sfu:Sfum_3302, sfu:Sfum_3365) (sfu:Sfum_3365, sfu:Sfum_3742) (sur:STAUR_0056, sur:STAUR_5425) (sur:STAUR_0276, sur:STAUR_5620) (sur:STAUR_0279, sur:STAUR_5622) (sur:STAUR_0299, sur:STAUR_4663) (sur:STAUR_0404, sur:STAUR_7259) (sur:STAUR_0531, sur:STAUR_4815) (sur:STAUR_0531, sur:STAUR_5595) (sur:STAUR_0531, sur:STAUR_5774) (sur:STAUR_0636, sur:STAUR_2240) (sur:STAUR_0672, sur:STAUR_3316) (sur:STAUR_0782, sur:STAUR_6764) (sur:STAUR_0784, sur:STAUR_6096) (sur:STAUR_0784, sur:STAUR_6098) (sur:STAUR_0785, sur:STAUR_5122) (sur:STAUR_0785, sur:STAUR_6805) (sur:STAUR_1091, sur:STAUR_6761) (sur:STAUR_1573, sur:STAUR_5621) (sur:STAUR_1653, sur:STAUR_8110) (sur:STAUR_1671, sur:STAUR_2146) (sur:STAUR_1904, sur:STAUR_3412) (sur:STAUR_2087, sur:STAUR_2729) (sur:STAUR_2087, sur:STAUR_5620) (sur:STAUR_2087, sur:STAUR_7849) (sur:STAUR_2116, sur:STAUR_7168) (sur:STAUR_2146, sur:STAUR_5309) (sur:STAUR_2244, sur:STAUR_3769) (sur:STAUR_2244, sur:STAUR_4439) (sur:STAUR_2244, sur:STAUR_6979) (sur:STAUR_2302, sur:STAUR_3279) (sur:STAUR_2302, sur:STAUR_3296) (sur:STAUR_2302, sur:STAUR_4038) (sur:STAUR_2302, sur:STAUR_5152) (sur:STAUR_2302, sur:STAUR_7055) (sur:STAUR_2346, sur:STAUR_4852) (sur:STAUR_2346, sur:STAUR_5285) (sur:STAUR_2346, sur:STAUR_7012) (sur:STAUR_2543, sur:STAUR_2647) (sur:STAUR_2699, sur:STAUR_5252) (sur:STAUR_2714, sur:STAUR_4493) (sur:STAUR_2729, sur:STAUR_5620) (sur:STAUR_2729, sur:STAUR_7849) (sur:STAUR_3111, sur:STAUR_6597) (sur:STAUR_3279, sur:STAUR_3296) (sur:STAUR_3279, sur:STAUR_5152) (sur:STAUR_3279, sur:STAUR_7055) (sur:STAUR_3296, sur:STAUR_7055) (sur:STAUR_3348, sur:STAUR_7939) (sur:STAUR_3549, sur:STAUR_4027) (sur:STAUR_3549, sur:STAUR_4028) (sur:STAUR_3605, sur:STAUR_4874) (sur:STAUR_3608, sur:STAUR_4873) (sur:STAUR_3769, sur:STAUR_4439) (sur:STAUR_3769, sur:STAUR_6979) (sur:STAUR_3779, sur:STAUR_4567) (sur:STAUR_3779, sur:STAUR_6406) (sur:STAUR_3779, sur:STAUR_6616) (sur:STAUR_3846, sur:STAUR_6310) (sur:STAUR_3888, sur:STAUR_6468) (sur:STAUR_3898, sur:STAUR_4273) (sur:STAUR_3898, sur:STAUR_5482) (sur:STAUR_3946, sur:STAUR_6060) (sur:STAUR_3991, sur:STAUR_5666) (sur:STAUR_4027, sur:STAUR_4028) (sur:STAUR_4035, sur:STAUR_6858) (sur:STAUR_4038, sur:STAUR_5152) (sur:STAUR_4039, sur:STAUR_6701) (sur:STAUR_4050, sur:STAUR_4874) (sur:STAUR_4128, sur:STAUR_6684) (sur:STAUR_4273, sur:STAUR_5482) (sur:STAUR_4439, sur:STAUR_6979) (sur:STAUR_4567, sur:STAUR_6259) (sur:STAUR_4567, sur:STAUR_6406) (sur:STAUR_4567, sur:STAUR_6616) (sur:STAUR_4684, sur:STAUR_4869) (sur:STAUR_4743, sur:STAUR_5620) (sur:STAUR_4815, sur:STAUR_5595) (sur:STAUR_4815, sur:STAUR_5774) (sur:STAUR_4815, sur:STAUR_8129) (sur:STAUR_4852, sur:STAUR_5285) (sur:STAUR_4852, sur:STAUR_7012) (sur:STAUR_4853, sur:STAUR_5872) (sur:STAUR_5122, sur:STAUR_6805) (sur:STAUR_5127, sur:STAUR_5813) (sur:STAUR_5155, sur:STAUR_7912) (sur:STAUR_5175, sur:STAUR_5839) (sur:STAUR_5197, sur:STAUR_5845) (sur:STAUR_5285, sur:STAUR_7012) (sur:STAUR_5339, sur:STAUR_5618) (sur:STAUR_5347, sur:STAUR_6803) (sur:STAUR_5486, sur:STAUR_5581) (sur:STAUR_5595, sur:STAUR_5774) (sur:STAUR_5620, sur:STAUR_7849) (sur:STAUR_5774, sur:STAUR_8129) (sur:STAUR_5870, sur:STAUR_7164) (sur:STAUR_5875, sur:STAUR_7165) (sur:STAUR_6096, sur:STAUR_6098) (sur:STAUR_6259, sur:STAUR_6406) (sur:STAUR_6266, sur:STAUR_6267) (sur:STAUR_6310, sur:STAUR_6830) (sur:STAUR_6406, sur:STAUR_6616) (sur:STAUR_8101, sur:STAUR_8226) (vin:AKJ08_0033, vin:AKJ08_0035) (vin:AKJ08_0051, vin:AKJ08_2528) (vin:AKJ08_0067, vin:AKJ08_0779) (vin:AKJ08_0163, vin:AKJ08_1411) (vin:AKJ08_0182, vin:AKJ08_2231) (vin:AKJ08_0229, vin:AKJ08_0242) (vin:AKJ08_0304, vin:AKJ08_2325) (vin:AKJ08_0448, vin:AKJ08_0452) (vin:AKJ08_0448, vin:AKJ08_0517) (vin:AKJ08_0452, vin:AKJ08_0517) (vin:AKJ08_0452, vin:AKJ08_1829) (vin:AKJ08_0452, vin:AKJ08_1884) (vin:AKJ08_0498, vin:AKJ08_1633) (vin:AKJ08_0507, vin:AKJ08_1488) (vin:AKJ08_0517, vin:AKJ08_1829) (vin:AKJ08_0517, vin:AKJ08_1884) (vin:AKJ08_0647, vin:AKJ08_2124) (vin:AKJ08_0731, vin:AKJ08_1262) (vin:AKJ08_0879, vin:AKJ08_1847) (vin:AKJ08_0977, vin:AKJ08_1190) (vin:AKJ08_0977, vin:AKJ08_2065) (vin:AKJ08_0977, vin:AKJ08_3214) (vin:AKJ08_1030, vin:AKJ08_2290) (vin:AKJ08_1046, vin:AKJ08_2528) (vin:AKJ08_1190, vin:AKJ08_2065) (vin:AKJ08_1190, vin:AKJ08_3214) (vin:AKJ08_1405, vin:AKJ08_1882) (vin:AKJ08_1409, vin:AKJ08_1848) (vin:AKJ08_1410, vin:AKJ08_3662) (vin:AKJ08_1417, vin:AKJ08_2627) (vin:AKJ08_1488, vin:AKJ08_2247) (vin:AKJ08_1509, vin:AKJ08_3161) (vin:AKJ08_1631, vin:AKJ08_2336) (vin:AKJ08_1631, vin:AKJ08_2585) (vin:AKJ08_1908, vin:AKJ08_3614) (vin:AKJ08_2065, vin:AKJ08_3214) (vin:AKJ08_2249, vin:AKJ08_2252) (vin:AKJ08_2249, vin:AKJ08_2254) (vin:AKJ08_2254, vin:AKJ08_2255) (vin:AKJ08_2274, vin:AKJ08_3459) (vin:AKJ08_2747, vin:AKJ08_2890) (vin:AKJ08_2748, vin:AKJ08_3025) (vin:AKJ08_2749, vin:AKJ08_3025)

gene-duplicated enzymes: 5868 (27%) ade:Adeh_0005 (1108 target-flexibility) (319 robustness) ade:Adeh_0012 (222 target-flexibility) (83 robustness) ade:Adeh_0036 (0 target-flexibility) (0 robustness) ade:Adeh_0038 (0 target-flexibility) (0 robustness) ade:Adeh_0069 (0 target-flexibility) (0 robustness) ade:Adeh_0171 (0 target-flexibility) (0 robustness) ade:Adeh_0221 (0 target-flexibility) (0 robustness) ade:Adeh_0255 (343 target-flexibility) (180 robustness) ade:Adeh_0295 (357 target-flexibility) (102 robustness) ade:Adeh_0533 (1385 target-flexibility) (204 robustness) ade:Adeh_0588 (0 target-flexibility) (0 robustness) ade:Adeh_0592 (358 target-flexibility) (124 robustness) ade:Adeh_0768 (691 target-flexibility) (528 robustness) ade:Adeh_0821 (700 target-flexibility) (89 robustness) ade:Adeh_0925 (0 target-flexibility) (0 robustness) ade:Adeh_1015 (902 target-flexibility) (228 robustness) ade:Adeh_1048 (358 target-flexibility) (124 robustness) ade:Adeh_1052 (855 target-flexibility) (138 robustness) ade:Adeh_1057 (0 target-flexibility) (0 robustness) ade:Adeh_1078 (71 target-flexibility) (71 robustness) ade:Adeh_1165 (0 target-flexibility) (0 robustness) ade:Adeh_1280 (528 target-flexibility) (157 robustness) ade:Adeh_1312 (691 target-flexibility) (528 robustness) ade:Adeh_1334 (0 target-flexibility) (0 robustness) ade:Adeh_1600 (343 target-flexibility) (180 robustness) ade:Adeh_1613 (734 target-flexibility) (110 robustness) ade:Adeh_1618 (897 target-flexibility) (71 robustness) ade:Adeh_1638 (245 target-flexibility) (66 robustness) ade:Adeh_1729 (405 target-flexibility) (169 robustness) ade:Adeh_1731 (1385 target-flexibility) (204 robustness) ade:Adeh_1830 (700 target-flexibility) (89 robustness) ade:Adeh_1954 (0 target-flexibility) (0 robustness) ade:Adeh_1955 (0 target-flexibility) (0 robustness) ade:Adeh_1963 (0 target-flexibility) (0 robustness) ade:Adeh_1978 (902 target-flexibility) (228 robustness) ade:Adeh_1981 (841 target-flexibility) (126 robustness) ade:Adeh_1994 (75 target-flexibility) (75 robustness) ade:Adeh_2047 (790 target-flexibility) (134 robustness) ade:Adeh_2057 (0 target-flexibility) (0 robustness) ade:Adeh_2071 (841 target-flexibility) (126 robustness) ade:Adeh_2078 (343 target-flexibility) (180 robustness) ade:Adeh_2315 (1385 target-flexibility) (204 robustness) ade:Adeh_2316 (528 target-flexibility) (157 robustness) ade:Adeh_2345 (0 target-flexibility) (0 robustness) ade:Adeh_2349 (423 target-flexibility) (81 robustness) ade:Adeh_2359 (0 target-flexibility) (0 robustness) ade:Adeh_2390 (212 target-flexibility) (73 robustness) ade:Adeh_2434 (0 target-flexibility) (0 robustness) ade:Adeh_2449 (231 target-flexibility) (158 robustness) ade:Adeh_2484 (734 target-flexibility) (110 robustness) ade:Adeh_2493 (75 target-flexibility) (75 robustness) ade:Adeh_2533 (752 target-flexibility) (76 robustness) ade:Adeh_2597 (357 target-flexibility) (102 robustness) ade:Adeh_2619 (790 target-flexibility) (134 robustness) ade:Adeh_2654 (855 target-flexibility) (138 robustness) ade:Adeh_2668 (528 target-flexibility) (157 robustness) ade:Adeh_2691 (138 target-flexibility) (66 robustness) ade:Adeh_2727 (0 target-flexibility) (0 robustness) ade:Adeh_2728 (206 target-flexibility) (68 robustness) ade:Adeh_2748 (659 target-flexibility) (240 robustness) ade:Adeh_2750 (1108 target-flexibility) (319 robustness) ade:Adeh_2760 (659 target-flexibility) (240 robustness) ade:Adeh_2780 (821 target-flexibility) (137 robustness) ade:Adeh_2789 (821 target-flexibility) (137 robustness) ade:Adeh_2867 (0 target-flexibility) (0 robustness) ade:Adeh_2886 (0 target-flexibility) (0 robustness) ade:Adeh_3037 (841 target-flexibility) (126 robustness) ade:Adeh_3135 (423 target-flexibility) (81 robustness) ade:Adeh_3141 (659 target-flexibility) (240 robustness) ade:Adeh_3396 (790 target-flexibility) (134 robustness) ade:Adeh_3428 (855 target-flexibility) (138 robustness) ade:Adeh_3514 (405 target-flexibility) (169 robustness) ade:Adeh_3637 (691 target-flexibility) (528 robustness) ade:Adeh_3694 (691 target-flexibility) (528 robustness) ade:Adeh_3748 (686 target-flexibility) (192 robustness) ade:Adeh_3766 (239 target-flexibility) (67 robustness) ade:Adeh_3767 (67 target-flexibility) (67 robustness) ade:Adeh_3769 (140 target-flexibility) (71 robustness) ade:Adeh_3772 (70 target-flexibility) (70 robustness) ade:Adeh_3774 (231 target-flexibility) (158 robustness) ade:Adeh_3784 (228 target-flexibility) (83 robustness) ade:Adeh_3927 (343 target-flexibility) (180 robustness) ade:Adeh_3931 (245 target-flexibility) (66 robustness) ade:Adeh_3959 (796 target-flexibility) (85 robustness) ade:Adeh_4057 (686 target-flexibility) (192 robustness) ade:Adeh_4206 (732 target-flexibility) (78 robustness) ade:Adeh_4220 (228 target-flexibility) (83 robustness) ade:Adeh_4242 (0 target-flexibility) (0 robustness) ade:Adeh_4288 (0 target-flexibility) (0 robustness) ade:Adeh_4305 (0 target-flexibility) (0 robustness) ade:Adeh_4344 (80 target-flexibility) (80 robustness) afw:Anae109_0005 (1108 target-flexibility) (319 robustness) afw:Anae109_0013 (222 target-flexibility) (83 robustness) afw:Anae109_0039 (0 target-flexibility) (0 robustness) afw:Anae109_0070 (0 target-flexibility) (0 robustness) afw:Anae109_0075 (0 target-flexibility) (0 robustness) afw:Anae109_0087 (350 target-flexibility) (84 robustness) afw:Anae109_0125 (657 target-flexibility) (95 robustness) afw:Anae109_0180 (0 target-flexibility) (0 robustness) afw:Anae109_0276 (343 target-flexibility) (180 robustness) afw:Anae109_0315 (1041 target-flexibility) (243 robustness) afw:Anae109_0319 (357 target-flexibility) (102 robustness) afw:Anae109_0323 (0 target-flexibility) (0 robustness) afw:Anae109_0371 (686 target-flexibility) (192 robustness) afw:Anae109_0462 (796 target-flexibility) (85 robustness) afw:Anae109_0473 (138 target-flexibility) (138 robustness) afw:Anae109_0508 (343 target-flexibility) (180 robustness) afw:Anae109_0637 (358 target-flexibility) (124 robustness) afw:Anae109_0814 (691 target-flexibility) (528 robustness) afw:Anae109_0859 (700 target-flexibility) (89 robustness) afw:Anae109_0968 (0 target-flexibility) (0 robustness) afw:Anae109_1089 (902 target-flexibility) (228 robustness) afw:Anae109_1102 (855 target-flexibility) (138 robustness) afw:Anae109_1117 (71 target-flexibility) (71 robustness) afw:Anae109_1136 (1169 target-flexibility) (76 robustness) afw:Anae109_1212 (0 target-flexibility) (0 robustness) afw:Anae109_1374 (75 target-flexibility) (75 robustness) afw:Anae109_1384 (734 target-flexibility) (110 robustness) afw:Anae109_1418 (231 target-flexibility) (158 robustness) afw:Anae109_1445 (0 target-flexibility) (0 robustness) afw:Anae109_1477 (212 target-flexibility) (73 robustness) afw:Anae109_1510 (0 target-flexibility) (0 robustness) afw:Anae109_1524 (423 target-flexibility) (81 robustness) afw:Anae109_1753 (841 target-flexibility) (126 robustness) afw:Anae109_1767 (790 target-flexibility) (134 robustness) afw:Anae109_1890 (0 target-flexibility) (0 robustness) afw:Anae109_1900 (0 target-flexibility) (0 robustness) afw:Anae109_1901 (0 target-flexibility) (0 robustness) afw:Anae109_2025 (1041 target-flexibility) (243 robustness) afw:Anae109_2026 (486 target-flexibility) (89 robustness) afw:Anae109_2033 (659 target-flexibility) (240 robustness) afw:Anae109_2078 (0 target-flexibility) (0 robustness) afw:Anae109_2183 (0 target-flexibility) (0 robustness) afw:Anae109_2184 (0 target-flexibility) (0 robustness) afw:Anae109_2193 (897 target-flexibility) (71 robustness) afw:Anae109_2361 (138 target-flexibility) (138 robustness) afw:Anae109_2449 (175 target-flexibility) (78 robustness) afw:Anae109_2451 (691 target-flexibility) (528 robustness) afw:Anae109_2487 (528 target-flexibility) (157 robustness) afw:Anae109_2552 (659 target-flexibility) (240 robustness) afw:Anae109_2555 (0 target-flexibility) (0 robustness) afw:Anae109_2586 (790 target-flexibility) (134 robustness) afw:Anae109_2647 (528 target-flexibility) (157 robustness) afw:Anae109_2737 (659 target-flexibility) (240 robustness) afw:Anae109_3065 (0 target-flexibility) (0 robustness) afw:Anae109_3137 (691 target-flexibility) (528 robustness) afw:Anae109_3159 (854 target-flexibility) (204 robustness) afw:Anae109_3170 (790 target-flexibility) (134 robustness) afw:Anae109_3213 (0 target-flexibility) (0 robustness) afw:Anae109_3255 (659 target-flexibility) (240 robustness) afw:Anae109_3313 (138 target-flexibility) (138 robustness) afw:Anae109_3601 (659 target-flexibility) (240 robustness) afw:Anae109_3608 (528 target-flexibility) (157 robustness) afw:Anae109_3721 (0 target-flexibility) (0 robustness) afw:Anae109_3732 (0 target-flexibility) (0 robustness) afw:Anae109_3879 (239 target-flexibility) (67 robustness) afw:Anae109_3882 (140 target-flexibility) (71 robustness) afw:Anae109_3904 (228 target-flexibility) (83 robustness) afw:Anae109_4196 (0 target-flexibility) (0 robustness) age:AA314_00262 (0 target-flexibility) (0 robustness) age:AA314_00693 (528 target-flexibility) (157 robustness) age:AA314_00717 (0 target-flexibility) (0 robustness) age:AA314_00859 (659 target-flexibility) (240 robustness) age:AA314_00861 (1108 target-flexibility) (319 robustness) age:AA314_00918 (528 target-flexibility) (157 robustness) age:AA314_00945 (659 target-flexibility) (240 robustness) age:AA314_01105 (0 target-flexibility) (0 robustness) age:AA314_01165 (222 target-flexibility) (83 robustness) age:AA314_01181 (73 target-flexibility) (73 robustness) age:AA314_01193 (80 target-flexibility) (80 robustness) age:AA314_01271 (924 target-flexibility) (101 robustness) age:AA314_01338 (659 target-flexibility) (240 robustness) age:AA314_01471 (1385 target-flexibility) (204 robustness) age:AA314_01479 (0 target-flexibility) (0 robustness) age:AA314_01699 (140 target-flexibility) (74 robustness) age:AA314_01881 (902 target-flexibility) (228 robustness) age:AA314_01912 (790 target-flexibility) (134 robustness) age:AA314_01954 (231 target-flexibility) (158 robustness) age:AA314_02279 (73 target-flexibility) (73 robustness) age:AA314_02310 (732 target-flexibility) (78 robustness) age:AA314_02336 (1183 target-flexibility) (114 robustness) age:AA314_02543 (357 target-flexibility) (102 robustness) age:AA314_02619 (377 target-flexibility) (117 robustness) age:AA314_02661 (0 target-flexibility) (0 robustness) age:AA314_02664 (790 target-flexibility) (134 robustness) age:AA314_02687 (659 target-flexibility) (240 robustness) age:AA314_02714 (796 target-flexibility) (85 robustness) age:AA314_02716 (734 target-flexibility) (110 robustness) age:AA314_02777 (350 target-flexibility) (189 robustness) age:AA314_02872 (0 target-flexibility) (0 robustness) age:AA314_02889 (336 target-flexibility) (81 robustness) age:AA314_02893 (343 target-flexibility) (180 robustness) age:AA314_02979 (343 target-flexibility) (180 robustness) age:AA314_03054 (0 target-flexibility) (0 robustness) age:AA314_03086 (75 target-flexibility) (75 robustness) age:AA314_03097 (0 target-flexibility) (0 robustness) age:AA314_03158 (358 target-flexibility) (124 robustness) age:AA314_03216 (691 target-flexibility) (528 robustness) age:AA314_03227 (0 target-flexibility) (0 robustness) age:AA314_03252 (138 target-flexibility) (138 robustness) age:AA314_03289 (0 target-flexibility) (0 robustness) age:AA314_03514 (0 target-flexibility) (0 robustness) age:AA314_03550 (1183 target-flexibility) (114 robustness) age:AA314_03763 (0 target-flexibility) (0 robustness) age:AA314_03773 (657 target-flexibility) (95 robustness) age:AA314_03826 (358 target-flexibility) (124 robustness) age:AA314_04024 (752 target-flexibility) (105 robustness) age:AA314_04141 (530 target-flexibility) (162 robustness) age:AA314_04142 (1108 target-flexibility) (319 robustness) age:AA314_04144 (659 target-flexibility) (240 robustness) age:AA314_04146 (703 target-flexibility) (319 robustness) age:AA314_04189 (0 target-flexibility) (0 robustness) age:AA314_04205 (71 target-flexibility) (71 robustness) age:AA314_04258 (752 target-flexibility) (76 robustness) age:AA314_04323 (659 target-flexibility) (240 robustness) age:AA314_04350 (0 target-flexibility) (0 robustness) age:AA314_04447 (212 target-flexibility) (73 robustness) age:AA314_04456 (1183 target-flexibility) (114 robustness) age:AA314_04554 (703 target-flexibility) (319 robustness) age:AA314_04555 (659 target-flexibility) (240 robustness) age:AA314_04761 (343 target-flexibility) (180 robustness) age:AA314_04783 (0 target-flexibility) (0 robustness) age:AA314_04817 (228 target-flexibility) (83 robustness) age:AA314_04822 (0 target-flexibility) (0 robustness) age:AA314_04924 (231 target-flexibility) (158 robustness) age:AA314_04935 (752 target-flexibility) (105 robustness) age:AA314_04970 (0 target-flexibility) (0 robustness) age:AA314_04985 (659 target-flexibility) (240 robustness) age:AA314_05002 (0 target-flexibility) (0 robustness) age:AA314_05003 (0 target-flexibility) (0 robustness) age:AA314_05007 (897 target-flexibility) (71 robustness) age:AA314_05011 (1784 target-flexibility) (162 robustness) age:AA314_05014 (0 target-flexibility) (0 robustness) age:AA314_05015 (924 target-flexibility) (101 robustness) age:AA314_05117 (74 target-flexibility) (74 robustness) age:AA314_05145 (0 target-flexibility) (0 robustness) age:AA314_05182 (212 target-flexibility) (73 robustness) age:AA314_05227 (138 target-flexibility) (138 robustness) age:AA314_05245 (1108 target-flexibility) (319 robustness) age:AA314_05446 (706 target-flexibility) (173 robustness) age:AA314_05477 (423 target-flexibility) (81 robustness) age:AA314_05512 (423 target-flexibility) (81 robustness) age:AA314_05564 (1385 target-flexibility) (204 robustness) age:AA314_05583 (377 target-flexibility) (117 robustness) age:AA314_05795 (343 target-flexibility) (180 robustness) age:AA314_05840 (0 target-flexibility) (0 robustness) age:AA314_05876 (0 target-flexibility) (0 robustness) age:AA314_05880 (138 target-flexibility) (66 robustness) age:AA314_05889 (1385 target-flexibility) (204 robustness) age:AA314_05890 (0 target-flexibility) (0 robustness) age:AA314_05977 (0 target-flexibility) (0 robustness) age:AA314_06016 (231 target-flexibility) (158 robustness) age:AA314_06106 (659 target-flexibility) (240 robustness) age:AA314_06198 (0 target-flexibility) (0 robustness) age:AA314_06206 (323 target-flexibility) (101 robustness) age:AA314_06223 (0 target-flexibility) (0 robustness) age:AA314_06374 (659 target-flexibility) (240 robustness) age:AA314_06470 (659 target-flexibility) (240 robustness) age:AA314_06684 (358 target-flexibility) (124 robustness) age:AA314_06718 (0 target-flexibility) (0 robustness) age:AA314_06720 (0 target-flexibility) (0 robustness) age:AA314_06748 (902 target-flexibility) (228 robustness) age:AA314_06754 (734 target-flexibility) (110 robustness) age:AA314_06815 (902 target-flexibility) (228 robustness) age:AA314_06851 (691 target-flexibility) (528 robustness) age:AA314_06989 (323 target-flexibility) (101 robustness) age:AA314_07032 (0 target-flexibility) (0 robustness) age:AA314_07077 (357 target-flexibility) (102 robustness) age:AA314_07107 (75 target-flexibility) (75 robustness) age:AA314_07149 (1022 target-flexibility) (80 robustness) age:AA314_07154 (1108 target-flexibility) (319 robustness) age:AA314_07241 (140 target-flexibility) (74 robustness) age:AA314_07252 (924 target-flexibility) (101 robustness) age:AA314_07285 (530 target-flexibility) (162 robustness) age:AA314_07327 (703 target-flexibility) (319 robustness) age:AA314_07475 (0 target-flexibility) (0 robustness) age:AA314_07499 (0 target-flexibility) (0 robustness) age:AA314_07568 (528 target-flexibility) (157 robustness) age:AA314_07592 (0 target-flexibility) (0 robustness) age:AA314_07741 (706 target-flexibility) (173 robustness) age:AA314_07751 (0 target-flexibility) (0 robustness) age:AA314_08005 (231 target-flexibility) (158 robustness) age:AA314_08007 (70 target-flexibility) (70 robustness) age:AA314_08012 (67 target-flexibility) (67 robustness) age:AA314_08032 (357 target-flexibility) (115 robustness) age:AA314_08206 (231 target-flexibility) (158 robustness) age:AA314_08225 (0 target-flexibility) (0 robustness) age:AA314_08305 (228 target-flexibility) (83 robustness) age:AA314_08421 (790 target-flexibility) (134 robustness) age:AA314_08455 (796 target-flexibility) (85 robustness) age:AA314_08462 (703 target-flexibility) (319 robustness) age:AA314_08615 (231 target-flexibility) (158 robustness) age:AA314_08648 (1108 target-flexibility) (319 robustness) age:AA314_08751 (226 target-flexibility) (85 robustness) age:AA314_08837 (1784 target-flexibility) (162 robustness) age:AA314_09003 (0 target-flexibility) (0 robustness) age:AA314_09026 (350 target-flexibility) (189 robustness) age:AA314_09027 (0 target-flexibility) (0 robustness) age:AA314_09029 (0 target-flexibility) (0 robustness) age:AA314_09030 (0 target-flexibility) (0 robustness) age:AA314_09037 (0 target-flexibility) (0 robustness) age:AA314_09050 (0 target-flexibility) (0 robustness) age:AA314_09055 (1183 target-flexibility) (114 robustness) age:AA314_09208 (74 target-flexibility) (74 robustness) age:AA314_09276 (1022 target-flexibility) (80 robustness) age:AA314_09460 (357 target-flexibility) (115 robustness) age:AA314_09587 (0 target-flexibility) (0 robustness) age:AA314_09664 (0 target-flexibility) (0 robustness) age:AA314_09705 (226 target-flexibility) (85 robustness) age:AA314_09937 (336 target-flexibility) (81 robustness) age:AA314_09947 (657 target-flexibility) (95 robustness) ank:AnaeK_0005 (1108 target-flexibility) (319 robustness) ank:AnaeK_0012 (222 target-flexibility) (83 robustness) ank:AnaeK_0040 (0 target-flexibility) (0 robustness) ank:AnaeK_0075 (0 target-flexibility) (0 robustness) ank:AnaeK_0081 (0 target-flexibility) (0 robustness) ank:AnaeK_0092 (350 target-flexibility) (84 robustness) ank:AnaeK_0180 (0 target-flexibility) (0 robustness) ank:AnaeK_0232 (0 target-flexibility) (0 robustness) ank:AnaeK_0265 (343 target-flexibility) (180 robustness) ank:AnaeK_0306 (357 target-flexibility) (102 robustness) ank:AnaeK_0565 (1385 target-flexibility) (204 robustness) ank:AnaeK_0627 (358 target-flexibility) (124 robustness) ank:AnaeK_0816 (691 target-flexibility) (528 robustness) ank:AnaeK_0869 (700 target-flexibility) (89 robustness) ank:AnaeK_0984 (0 target-flexibility) (0 robustness) ank:AnaeK_1073 (902 target-flexibility) (228 robustness) ank:AnaeK_1108 (855 target-flexibility) (138 robustness) ank:AnaeK_1116 (0 target-flexibility) (0 robustness) ank:AnaeK_1137 (71 target-flexibility) (71 robustness) ank:AnaeK_1224 (0 target-flexibility) (0 robustness) ank:AnaeK_1362 (75 target-flexibility) (75 robustness) ank:AnaeK_1374 (734 target-flexibility) (110 robustness) ank:AnaeK_1410 (231 target-flexibility) (158 robustness) ank:AnaeK_1429 (0 target-flexibility) (0 robustness) ank:AnaeK_1474 (212 target-flexibility) (73 robustness) ank:AnaeK_1505 (0 target-flexibility) (0 robustness) ank:AnaeK_1520 (423 target-flexibility) (81 robustness) ank:AnaeK_1557 (528 target-flexibility) (157 robustness) ank:AnaeK_1799 (343 target-flexibility) (180 robustness) ank:AnaeK_1806 (841 target-flexibility) (126 robustness) ank:AnaeK_1821 (0 target-flexibility) (0 robustness) ank:AnaeK_1897 (841 target-flexibility) (126 robustness) ank:AnaeK_1915 (0 target-flexibility) (0 robustness) ank:AnaeK_1924 (0 target-flexibility) (0 robustness) ank:AnaeK_1925 (0 target-flexibility) (0 robustness) ank:AnaeK_2118 (405 target-flexibility) (169 robustness) ank:AnaeK_2124 (0 target-flexibility) (0 robustness) ank:AnaeK_2222 (245 target-flexibility) (66 robustness) ank:AnaeK_2242 (897 target-flexibility) (71 robustness) ank:AnaeK_2263 (343 target-flexibility) (180 robustness) ank:AnaeK_2548 (691 target-flexibility) (528 robustness) ank:AnaeK_2581 (528 target-flexibility) (157 robustness) ank:AnaeK_2649 (659 target-flexibility) (240 robustness) ank:AnaeK_2705 (790 target-flexibility) (134 robustness) ank:AnaeK_2840 (659 target-flexibility) (240 robustness) ank:AnaeK_2852 (659 target-flexibility) (240 robustness) ank:AnaeK_3452 (0 target-flexibility) (0 robustness) ank:AnaeK_3805 (686 target-flexibility) (192 robustness) ank:AnaeK_3822 (239 target-flexibility) (67 robustness) ank:AnaeK_3825 (140 target-flexibility) (71 robustness) ank:AnaeK_3839 (228 target-flexibility) (83 robustness) ank:AnaeK_4069 (796 target-flexibility) (85 robustness) ccro:CMC5_000130 (212 target-flexibility) (73 robustness) ccro:CMC5_000390 (780 target-flexibility) (243 robustness) ccro:CMC5_000580 (1385 target-flexibility) (204 robustness) ccro:CMC5_000670 (343 target-flexibility) (180 robustness) ccro:CMC5_001320 (0 target-flexibility) (0 robustness) ccro:CMC5_002670 (0 target-flexibility) (0 robustness) ccro:CMC5_003310 (697 target-flexibility) (78 robustness) ccro:CMC5_003550 (691 target-flexibility) (528 robustness) ccro:CMC5_004340 (752 target-flexibility) (73 robustness) ccro:CMC5_006070 (924 target-flexibility) (101 robustness) ccro:CMC5_006290 (902 target-flexibility) (228 robustness) ccro:CMC5_007320 (350 target-flexibility) (189 robustness) ccro:CMC5_007720 (790 target-flexibility) (134 robustness) ccro:CMC5_007870 (0 target-flexibility) (0 robustness) ccro:CMC5_008250 (1108 target-flexibility) (319 robustness) ccro:CMC5_009420 (790 target-flexibility) (134 robustness) ccro:CMC5_010330 (1022 target-flexibility) (80 robustness) ccro:CMC5_011120 (1108 target-flexibility) (319 robustness) ccro:CMC5_011270 (0 target-flexibility) (0 robustness) ccro:CMC5_011280 (0 target-flexibility) (0 robustness) ccro:CMC5_011930 (80 target-flexibility) (80 robustness) ccro:CMC5_012020 (0 target-flexibility) (0 robustness) ccro:CMC5_012200 (423 target-flexibility) (81 robustness) ccro:CMC5_012370 (706 target-flexibility) (173 robustness) ccro:CMC5_012520 (0 target-flexibility) (0 robustness) ccro:CMC5_013340 (0 target-flexibility) (0 robustness) ccro:CMC5_014820 (231 target-flexibility) (158 robustness) ccro:CMC5_014950 (734 target-flexibility) (110 robustness) ccro:CMC5_016590 (358 target-flexibility) (124 robustness) ccro:CMC5_016930 (821 target-flexibility) (137 robustness) ccro:CMC5_017220 (821 target-flexibility) (137 robustness) ccro:CMC5_017680 (752 target-flexibility) (105 robustness) ccro:CMC5_017710 (0 target-flexibility) (0 robustness) ccro:CMC5_017730 (0 target-flexibility) (0 robustness) ccro:CMC5_018350 (71 target-flexibility) (71 robustness) ccro:CMC5_019230 (0 target-flexibility) (0 robustness) ccro:CMC5_019550 (231 target-flexibility) (158 robustness) ccro:CMC5_020730 (423 target-flexibility) (81 robustness) ccro:CMC5_021680 (0 target-flexibility) (0 robustness) ccro:CMC5_021730 (706 target-flexibility) (173 robustness) ccro:CMC5_021740 (706 target-flexibility) (173 robustness) ccro:CMC5_021880 (528 target-flexibility) (157 robustness) ccro:CMC5_022050 (358 target-flexibility) (104 robustness) ccro:CMC5_024200 (1022 target-flexibility) (80 robustness) ccro:CMC5_024590 (377 target-flexibility) (117 robustness) ccro:CMC5_024620 (377 target-flexibility) (117 robustness) ccro:CMC5_024850 (734 target-flexibility) (110 robustness) ccro:CMC5_024890 (752 target-flexibility) (105 robustness) ccro:CMC5_025200 (140 target-flexibility) (74 robustness) ccro:CMC5_029220 (691 target-flexibility) (528 robustness) ccro:CMC5_030280 (350 target-flexibility) (189 robustness) ccro:CMC5_030970 (146 target-flexibility) (75 robustness) ccro:CMC5_031580 (1108 target-flexibility) (319 robustness) ccro:CMC5_032100 (528 target-flexibility) (157 robustness) ccro:CMC5_032690 (528 target-flexibility) (157 robustness) ccro:CMC5_032920 (528 target-flexibility) (157 robustness) ccro:CMC5_032960 (528 target-flexibility) (157 robustness) ccro:CMC5_034090 (0 target-flexibility) (0 robustness) ccro:CMC5_038260 (0 target-flexibility) (0 robustness) ccro:CMC5_038680 (0 target-flexibility) (0 robustness) ccro:CMC5_041050 (821 target-flexibility) (137 robustness) ccro:CMC5_041140 (1108 target-flexibility) (319 robustness) ccro:CMC5_041160 (659 target-flexibility) (240 robustness) ccro:CMC5_041180 (703 target-flexibility) (319 robustness) ccro:CMC5_041690 (343 target-flexibility) (180 robustness) ccro:CMC5_042410 (0 target-flexibility) (0 robustness) ccro:CMC5_043060 (752 target-flexibility) (73 robustness) ccro:CMC5_043090 (0 target-flexibility) (0 robustness) ccro:CMC5_043210 (1183 target-flexibility) (114 robustness) ccro:CMC5_043620 (343 target-flexibility) (180 robustness) ccro:CMC5_044530 (222 target-flexibility) (83 robustness) ccro:CMC5_045520 (697 target-flexibility) (78 robustness) ccro:CMC5_045840 (780 target-flexibility) (243 robustness) ccro:CMC5_046360 (358 target-flexibility) (124 robustness) ccro:CMC5_046730 (497 target-flexibility) (186 robustness) ccro:CMC5_047480 (706 target-flexibility) (173 robustness) ccro:CMC5_047550 (706 target-flexibility) (173 robustness) ccro:CMC5_048220 (0 target-flexibility) (0 robustness) ccro:CMC5_049140 (146 target-flexibility) (75 robustness) ccro:CMC5_049960 (0 target-flexibility) (0 robustness) ccro:CMC5_050070 (1041 target-flexibility) (243 robustness) ccro:CMC5_051960 (0 target-flexibility) (0 robustness) ccro:CMC5_052220 (0 target-flexibility) (0 robustness) ccro:CMC5_053140 (0 target-flexibility) (0 robustness) ccro:CMC5_053620 (659 target-flexibility) (240 robustness) ccro:CMC5_053730 (1041 target-flexibility) (243 robustness) ccro:CMC5_057100 (706 target-flexibility) (173 robustness) ccro:CMC5_059120 (1385 target-flexibility) (204 robustness) ccro:CMC5_059220 (0 target-flexibility) (0 robustness) ccro:CMC5_060030 (1108 target-flexibility) (319 robustness) ccro:CMC5_060070 (1022 target-flexibility) (80 robustness) ccro:CMC5_060910 (1108 target-flexibility) (319 robustness) ccro:CMC5_061110 (140 target-flexibility) (74 robustness) ccro:CMC5_061320 (358 target-flexibility) (104 robustness) ccro:CMC5_061620 (752 target-flexibility) (105 robustness) ccro:CMC5_061720 (703 target-flexibility) (319 robustness) ccro:CMC5_064330 (358 target-flexibility) (124 robustness) ccro:CMC5_064420 (902 target-flexibility) (228 robustness) ccro:CMC5_064710 (924 target-flexibility) (101 robustness) ccro:CMC5_064720 (924 target-flexibility) (101 robustness) ccro:CMC5_065360 (70 target-flexibility) (70 robustness) ccro:CMC5_065390 (140 target-flexibility) (71 robustness) ccro:CMC5_065510 (659 target-flexibility) (240 robustness) ccro:CMC5_065650 (71 target-flexibility) (71 robustness) ccro:CMC5_068840 (0 target-flexibility) (0 robustness) ccro:CMC5_069050 (231 target-flexibility) (158 robustness) ccro:CMC5_069660 (0 target-flexibility) (0 robustness) ccro:CMC5_070310 (657 target-flexibility) (95 robustness) ccro:CMC5_071350 (1183 target-flexibility) (114 robustness) ccro:CMC5_072280 (855 target-flexibility) (138 robustness) ccro:CMC5_074240 (703 target-flexibility) (319 robustness) ccro:CMC5_075250 (706 target-flexibility) (173 robustness) ccro:CMC5_076410 (497 target-flexibility) (186 robustness) ccro:CMC5_078390 (657 target-flexibility) (95 robustness) ccro:CMC5_078580 (790 target-flexibility) (134 robustness) ccro:CMC5_082820 (706 target-flexibility) (173 robustness) ccro:CMC5_084110 (0 target-flexibility) (0 robustness) ccro:CMC5_084320 (855 target-flexibility) (138 robustness) ccx:COCOR_00090 (0 target-flexibility) (0 robustness) ccx:COCOR_00142 (0 target-flexibility) (0 robustness) ccx:COCOR_00249 (657 target-flexibility) (95 robustness) ccx:COCOR_00269 (336 target-flexibility) (81 robustness) ccx:COCOR_00470 (1385 target-flexibility) (204 robustness) ccx:COCOR_00572 (0 target-flexibility) (0 robustness) ccx:COCOR_00825 (357 target-flexibility) (115 robustness) ccx:COCOR_00865 (659 target-flexibility) (240 robustness) ccx:COCOR_00905 (790 target-flexibility) (134 robustness) ccx:COCOR_00928 (528 target-flexibility) (157 robustness) ccx:COCOR_00984 (154 target-flexibility) (80 robustness) ccx:COCOR_00988 (0 target-flexibility) (0 robustness) ccx:COCOR_01033 (73 target-flexibility) (73 robustness) ccx:COCOR_01049 (732 target-flexibility) (78 robustness) ccx:COCOR_01180 (357 target-flexibility) (102 robustness) ccx:COCOR_01252 (0 target-flexibility) (0 robustness) ccx:COCOR_01272 (796 target-flexibility) (85 robustness) ccx:COCOR_01301 (350 target-flexibility) (189 robustness) ccx:COCOR_01340 (336 target-flexibility) (81 robustness) ccx:COCOR_01538 (0 target-flexibility) (0 robustness) ccx:COCOR_01588 (528 target-flexibility) (157 robustness) ccx:COCOR_01667 (0 target-flexibility) (0 robustness) ccx:COCOR_01693 (0 target-flexibility) (0 robustness) ccx:COCOR_01916 (1183 target-flexibility) (114 robustness) ccx:COCOR_01974 (0 target-flexibility) (0 robustness) ccx:COCOR_01982 (138 target-flexibility) (138 robustness) ccx:COCOR_02062 (1041 target-flexibility) (243 robustness) ccx:COCOR_02063 (1041 target-flexibility) (243 robustness) ccx:COCOR_02069 (659 target-flexibility) (240 robustness) ccx:COCOR_02172 (0 target-flexibility) (0 robustness) ccx:COCOR_02213 (0 target-flexibility) (0 robustness) ccx:COCOR_02243 (1183 target-flexibility) (114 robustness) ccx:COCOR_02279 (902 target-flexibility) (228 robustness) ccx:COCOR_02328 (0 target-flexibility) (0 robustness) ccx:COCOR_02414 (657 target-flexibility) (95 robustness) ccx:COCOR_02422 (734 target-flexibility) (110 robustness) ccx:COCOR_02459 (358 target-flexibility) (124 robustness) ccx:COCOR_02496 (703 target-flexibility) (319 robustness) ccx:COCOR_02555 (752 target-flexibility) (105 robustness) ccx:COCOR_02623 (530 target-flexibility) (162 robustness) ccx:COCOR_02624 (1108 target-flexibility) (319 robustness) ccx:COCOR_02626 (659 target-flexibility) (240 robustness) ccx:COCOR_02628 (703 target-flexibility) (319 robustness) ccx:COCOR_02650 (0 target-flexibility) (0 robustness) ccx:COCOR_02664 (71 target-flexibility) (71 robustness) ccx:COCOR_02713 (752 target-flexibility) (76 robustness) ccx:COCOR_02773 (528 target-flexibility) (157 robustness) ccx:COCOR_02898 (343 target-flexibility) (180 robustness) ccx:COCOR_02980 (0 target-flexibility) (0 robustness) ccx:COCOR_03005 (701 target-flexibility) (106 robustness) ccx:COCOR_03074 (343 target-flexibility) (180 robustness) ccx:COCOR_03165 (706 target-flexibility) (173 robustness) ccx:COCOR_03252 (0 target-flexibility) (0 robustness) ccx:COCOR_03253 (1385 target-flexibility) (204 robustness) ccx:COCOR_03319 (212 target-flexibility) (73 robustness) ccx:COCOR_03448 (239 target-flexibility) (99 robustness) ccx:COCOR_03497 (0 target-flexibility) (0 robustness) ccx:COCOR_03532 (659 target-flexibility) (240 robustness) ccx:COCOR_03708 (0 target-flexibility) (0 robustness) ccx:COCOR_03717 (323 target-flexibility) (101 robustness) ccx:COCOR_03732 (0 target-flexibility) (0 robustness) ccx:COCOR_03787 (902 target-flexibility) (228 robustness) ccx:COCOR_03852 (231 target-flexibility) (158 robustness) ccx:COCOR_03904 (0 target-flexibility) (0 robustness) ccx:COCOR_03913 (0 target-flexibility) (0 robustness) ccx:COCOR_03939 (0 target-flexibility) (0 robustness) ccx:COCOR_03963 (343 target-flexibility) (180 robustness) ccx:COCOR_04442 (0 target-flexibility) (0 robustness) ccx:COCOR_04525 (0 target-flexibility) (0 robustness) ccx:COCOR_04528 (1784 target-flexibility) (162 robustness) ccx:COCOR_04535 (0 target-flexibility) (0 robustness) ccx:COCOR_04536 (0 target-flexibility) (0 robustness) ccx:COCOR_04577 (659 target-flexibility) (240 robustness) ccx:COCOR_04599 (138 target-flexibility) (138 robustness) ccx:COCOR_04658 (752 target-flexibility) (105 robustness) ccx:COCOR_04690 (0 target-flexibility) (0 robustness) ccx:COCOR_04815 (0 target-flexibility) (0 robustness) ccx:COCOR_04847 (1169 target-flexibility) (76 robustness) ccx:COCOR_05075 (358 target-flexibility) (124 robustness) ccx:COCOR_05103 (0 target-flexibility) (0 robustness) ccx:COCOR_05120 (0 target-flexibility) (0 robustness) ccx:COCOR_05137 (734 target-flexibility) (110 robustness) ccx:COCOR_05182 (231 target-flexibility) (158 robustness) ccx:COCOR_05367 (357 target-flexibility) (102 robustness) ccx:COCOR_05520 (790 target-flexibility) (134 robustness) ccx:COCOR_05546 (530 target-flexibility) (162 robustness) ccx:COCOR_05708 (239 target-flexibility) (99 robustness) ccx:COCOR_05716 (0 target-flexibility) (0 robustness) ccx:COCOR_05866 (659 target-flexibility) (240 robustness) ccx:COCOR_05867 (703 target-flexibility) (319 robustness) ccx:COCOR_05901 (924 target-flexibility) (101 robustness) ccx:COCOR_06071 (343 target-flexibility) (180 robustness) ccx:COCOR_06092 (231 target-flexibility) (158 robustness) ccx:COCOR_06120 (357 target-flexibility) (115 robustness) ccx:COCOR_06234 (231 target-flexibility) (158 robustness) ccx:COCOR_06306 (701 target-flexibility) (106 robustness) ccx:COCOR_06380 (790 target-flexibility) (134 robustness) ccx:COCOR_06476 (239 target-flexibility) (99 robustness) ccx:COCOR_06497 (231 target-flexibility) (158 robustness) ccx:COCOR_06506 (706 target-flexibility) (173 robustness) ccx:COCOR_06667 (222 target-flexibility) (83 robustness) ccx:COCOR_06732 (706 target-flexibility) (173 robustness) ccx:COCOR_06741 (1041 target-flexibility) (243 robustness) ccx:COCOR_06913 (1784 target-flexibility) (162 robustness) ccx:COCOR_07018 (0 target-flexibility) (0 robustness) ccx:COCOR_07023 (1183 target-flexibility) (114 robustness) ccx:COCOR_07093 (154 target-flexibility) (80 robustness) ccx:COCOR_07115 (350 target-flexibility) (189 robustness) ccx:COCOR_07437 (0 target-flexibility) (0 robustness) ccx:COCOR_07492 (659 target-flexibility) (240 robustness) ccx:COCOR_07598 (924 target-flexibility) (101 robustness) ccx:COCOR_07628 (73 target-flexibility) (73 robustness) ccx:COCOR_07636 (222 target-flexibility) (83 robustness) ccx:COCOR_07767 (323 target-flexibility) (101 robustness) ccx:COCOR_07826 (1108 target-flexibility) (319 robustness) ccx:COCOR_07830 (659 target-flexibility) (240 robustness) ccx:COCOR_07894 (659 target-flexibility) (240 robustness) ccx:COCOR_07941 (1041 target-flexibility) (243 robustness) ccx:COCOR_08029 (0 target-flexibility) (0 robustness) cfus:CYFUS_000149 (0 target-flexibility) (0 robustness) cfus:CYFUS_000192 (821 target-flexibility) (137 robustness) cfus:CYFUS_000307 (659 target-flexibility) (240 robustness) cfus:CYFUS_000313 (387 target-flexibility) (72 robustness) cfus:CYFUS_000404 (528 target-flexibility) (157 robustness) cfus:CYFUS_000458 (657 target-flexibility) (95 robustness) cfus:CYFUS_000596 (706 target-flexibility) (173 robustness) cfus:CYFUS_000638 (222 target-flexibility) (83 robustness) cfus:CYFUS_000671 (73 target-flexibility) (73 robustness) cfus:CYFUS_000730 (924 target-flexibility) (101 robustness) cfus:CYFUS_000821 (1385 target-flexibility) (204 robustness) cfus:CYFUS_001050 (796 target-flexibility) (85 robustness) cfus:CYFUS_001074 (146 target-flexibility) (75 robustness) cfus:CYFUS_001210 (790 target-flexibility) (134 robustness) cfus:CYFUS_001258 (686 target-flexibility) (192 robustness) cfus:CYFUS_001270 (343 target-flexibility) (180 robustness) cfus:CYFUS_001311 (0 target-flexibility) (0 robustness) cfus:CYFUS_001388 (0 target-flexibility) (0 robustness) cfus:CYFUS_001400 (821 target-flexibility) (137 robustness) cfus:CYFUS_001448 (73 target-flexibility) (73 robustness) cfus:CYFUS_001459 (732 target-flexibility) (78 robustness) cfus:CYFUS_001521 (231 target-flexibility) (158 robustness) cfus:CYFUS_001768 (215 target-flexibility) (142 robustness) cfus:CYFUS_001817 (659 target-flexibility) (240 robustness) cfus:CYFUS_001840 (357 target-flexibility) (102 robustness) cfus:CYFUS_001955 (0 target-flexibility) (0 robustness) cfus:CYFUS_001961 (262 target-flexibility) (86 robustness) cfus:CYFUS_002029 (796 target-flexibility) (85 robustness) cfus:CYFUS_002032 (734 target-flexibility) (110 robustness) cfus:CYFUS_002120 (336 target-flexibility) (81 robustness) cfus:CYFUS_002221 (0 target-flexibility) (0 robustness) cfus:CYFUS_002267 (659 target-flexibility) (240 robustness) cfus:CYFUS_002275 (343 target-flexibility) (180 robustness) cfus:CYFUS_002369 (526 target-flexibility) (95 robustness) cfus:CYFUS_002381 (0 target-flexibility) (0 robustness) cfus:CYFUS_002434 (691 target-flexibility) (528 robustness) cfus:CYFUS_002450 (0 target-flexibility) (0 robustness) cfus:CYFUS_002606 (0 target-flexibility) (0 robustness) cfus:CYFUS_002610 (0 target-flexibility) (0 robustness) cfus:CYFUS_002692 (0 target-flexibility) (0 robustness) cfus:CYFUS_002820 (530 target-flexibility) (162 robustness) cfus:CYFUS_002842 (166 target-flexibility) (99 robustness) cfus:CYFUS_002855 (790 target-flexibility) (134 robustness) cfus:CYFUS_002856 (336 target-flexibility) (81 robustness) cfus:CYFUS_002879 (526 target-flexibility) (95 robustness) cfus:CYFUS_002936 (659 target-flexibility) (240 robustness) cfus:CYFUS_002943 (706 target-flexibility) (173 robustness) cfus:CYFUS_002949 (1022 target-flexibility) (80 robustness) cfus:CYFUS_003023 (357 target-flexibility) (102 robustness) cfus:CYFUS_003160 (166 target-flexibility) (99 robustness) cfus:CYFUS_003161 (752 target-flexibility) (105 robustness) cfus:CYFUS_003276 (222 target-flexibility) (83 robustness) cfus:CYFUS_003324 (691 target-flexibility) (528 robustness) cfus:CYFUS_003468 (530 target-flexibility) (162 robustness) cfus:CYFUS_003469 (503 target-flexibility) (78 robustness) cfus:CYFUS_003470 (659 target-flexibility) (240 robustness) cfus:CYFUS_003472 (703 target-flexibility) (319 robustness) cfus:CYFUS_003510 (0 target-flexibility) (0 robustness) cfus:CYFUS_003523 (71 target-flexibility) (71 robustness) cfus:CYFUS_003761 (0 target-flexibility) (0 robustness) cfus:CYFUS_003871 (231 target-flexibility) (158 robustness) cfus:CYFUS_003986 (0 target-flexibility) (0 robustness) cfus:CYFUS_004176 (146 target-flexibility) (75 robustness) cfus:CYFUS_004217 (343 target-flexibility) (180 robustness) cfus:CYFUS_004248 (0 target-flexibility) (0 robustness) cfus:CYFUS_004265 (228 target-flexibility) (83 robustness) cfus:CYFUS_004276 (0 target-flexibility) (0 robustness) cfus:CYFUS_004307 (752 target-flexibility) (105 robustness) cfus:CYFUS_004387 (212 target-flexibility) (73 robustness) cfus:CYFUS_004460 (706 target-flexibility) (173 robustness) cfus:CYFUS_004499 (0 target-flexibility) (0 robustness) cfus:CYFUS_004500 (0 target-flexibility) (0 robustness) cfus:CYFUS_004504 (897 target-flexibility) (71 robustness) cfus:CYFUS_004522 (902 target-flexibility) (228 robustness) cfus:CYFUS_004536 (1784 target-flexibility) (162 robustness) cfus:CYFUS_004539 (924 target-flexibility) (101 robustness) cfus:CYFUS_004606 (659 target-flexibility) (240 robustness) cfus:CYFUS_004618 (262 target-flexibility) (86 robustness) cfus:CYFUS_004674 (0 target-flexibility) (0 robustness) cfus:CYFUS_004693 (686 target-flexibility) (192 robustness) cfus:CYFUS_004932 (659 target-flexibility) (240 robustness) cfus:CYFUS_004967 (0 target-flexibility) (0 robustness) cfus:CYFUS_005031 (377 target-flexibility) (117 robustness) cfus:CYFUS_005114 (703 target-flexibility) (319 robustness) cfus:CYFUS_005273 (924 target-flexibility) (101 robustness) cfus:CYFUS_005417 (343 target-flexibility) (180 robustness) cfus:CYFUS_005491 (0 target-flexibility) (0 robustness) cfus:CYFUS_005495 (0 target-flexibility) (0 robustness) cfus:CYFUS_005532 (301 target-flexibility) (74 robustness) cfus:CYFUS_005533 (138 target-flexibility) (66 robustness) cfus:CYFUS_005572 (821 target-flexibility) (137 robustness) cfus:CYFUS_005582 (1385 target-flexibility) (204 robustness) cfus:CYFUS_005589 (706 target-flexibility) (173 robustness) cfus:CYFUS_005693 (659 target-flexibility) (240 robustness) cfus:CYFUS_005776 (902 target-flexibility) (228 robustness) cfus:CYFUS_006014 (0 target-flexibility) (0 robustness) cfus:CYFUS_006116 (752 target-flexibility) (76 robustness) cfus:CYFUS_006401 (503 target-flexibility) (78 robustness) cfus:CYFUS_006411 (752 target-flexibility) (105 robustness) cfus:CYFUS_006415 (0 target-flexibility) (0 robustness) cfus:CYFUS_006464 (855 target-flexibility) (138 robustness) cfus:CYFUS_006469 (358 target-flexibility) (124 robustness) cfus:CYFUS_006478 (0 target-flexibility) (0 robustness) cfus:CYFUS_006545 (0 target-flexibility) (0 robustness) cfus:CYFUS_006565 (734 target-flexibility) (110 robustness) cfus:CYFUS_006568 (301 target-flexibility) (74 robustness) cfus:CYFUS_006579 (528 target-flexibility) (157 robustness) cfus:CYFUS_006640 (752 target-flexibility) (105 robustness) cfus:CYFUS_006704 (697 target-flexibility) (78 robustness) cfus:CYFUS_006707 (902 target-flexibility) (228 robustness) cfus:CYFUS_006709 (855 target-flexibility) (138 robustness) cfus:CYFUS_006715 (359 target-flexibility) (65 robustness) cfus:CYFUS_006729 (359 target-flexibility) (65 robustness) cfus:CYFUS_006834 (358 target-flexibility) (124 robustness) cfus:CYFUS_006893 (657 target-flexibility) (95 robustness) cfus:CYFUS_007043 (336 target-flexibility) (81 robustness) cfus:CYFUS_007112 (1183 target-flexibility) (114 robustness) cfus:CYFUS_007177 (0 target-flexibility) (0 robustness) cfus:CYFUS_007179 (0 target-flexibility) (0 robustness) cfus:CYFUS_007182 (752 target-flexibility) (105 robustness) cfus:CYFUS_007242 (821 target-flexibility) (137 robustness) cfus:CYFUS_007353 (0 target-flexibility) (0 robustness) cfus:CYFUS_007387 (528 target-flexibility) (157 robustness) cfus:CYFUS_007446 (0 target-flexibility) (0 robustness) cfus:CYFUS_007657 (821 target-flexibility) (137 robustness) cfus:CYFUS_007663 (902 target-flexibility) (228 robustness) cfus:CYFUS_007827 (231 target-flexibility) (158 robustness) cfus:CYFUS_007834 (67 target-flexibility) (67 robustness) cfus:CYFUS_007835 (239 target-flexibility) (67 robustness) cfus:CYFUS_007908 (0 target-flexibility) (0 robustness) cfus:CYFUS_007984 (231 target-flexibility) (158 robustness) cfus:CYFUS_007998 (0 target-flexibility) (0 robustness) cfus:CYFUS_008059 (228 target-flexibility) (83 robustness) cfus:CYFUS_008079 (358 target-flexibility) (124 robustness) cfus:CYFUS_008254 (697 target-flexibility) (78 robustness) cfus:CYFUS_008295 (231 target-flexibility) (158 robustness) cfus:CYFUS_008485 (686 target-flexibility) (192 robustness) cfus:CYFUS_008499 (215 target-flexibility) (142 robustness) cfus:CYFUS_008610 (1784 target-flexibility) (162 robustness) cfus:CYFUS_008791 (0 target-flexibility) (0 robustness) cfus:CYFUS_008837 (0 target-flexibility) (0 robustness) cfus:CYFUS_008840 (0 target-flexibility) (0 robustness) cfus:CYFUS_008843 (1183 target-flexibility) (114 robustness) cfus:CYFUS_009033 (387 target-flexibility) (72 robustness) cfus:CYFUS_009048 (377 target-flexibility) (117 robustness) cfus:CYFUS_009170 (1022 target-flexibility) (80 robustness) cfus:CYFUS_009173 (0 target-flexibility) (0 robustness) cfus:CYFUS_009210 (231 target-flexibility) (158 robustness) cfus:CYFUS_009233 (1183 target-flexibility) (114 robustness) cfus:CYFUS_009429 (0 target-flexibility) (0 robustness) cfus:CYFUS_009460 (0 target-flexibility) (0 robustness) cfus:CYFUS_009491 (0 target-flexibility) (0 robustness) cfus:CYFUS_009647 (659 target-flexibility) (240 robustness) cfus:CYFUS_009732 (0 target-flexibility) (0 robustness) cfus:CYFUS_009744 (0 target-flexibility) (0 robustness) cfus:CYFUS_009834 (855 target-flexibility) (138 robustness) daf:Desaf_0028 (855 target-flexibility) (138 robustness) daf:Desaf_0050 (855 target-flexibility) (138 robustness) daf:Desaf_0090 (1041 target-flexibility) (243 robustness) daf:Desaf_0111 (732 target-flexibility) (78 robustness) daf:Desaf_0187 (600 target-flexibility) (126 robustness) daf:Desaf_0304 (1041 target-flexibility) (243 robustness) daf:Desaf_0322 (790 target-flexibility) (134 robustness) daf:Desaf_0342 (0 target-flexibility) (0 robustness) daf:Desaf_0400 (0 target-flexibility) (0 robustness) daf:Desaf_0457 (0 target-flexibility) (0 robustness) daf:Desaf_0470 (468 target-flexibility) (75 robustness) daf:Desaf_0481 (0 target-flexibility) (0 robustness) daf:Desaf_0721 (706 target-flexibility) (173 robustness) daf:Desaf_0810 (1108 target-flexibility) (319 robustness) daf:Desaf_0812 (600 target-flexibility) (126 robustness) daf:Desaf_0930 (0 target-flexibility) (0 robustness) daf:Desaf_0973 (1385 target-flexibility) (204 robustness) daf:Desaf_0993 (0 target-flexibility) (0 robustness) daf:Desaf_1004 (0 target-flexibility) (0 robustness) daf:Desaf_1013 (0 target-flexibility) (0 robustness) daf:Desaf_1014 (0 target-flexibility) (0 robustness) daf:Desaf_1015 (0 target-flexibility) (0 robustness) daf:Desaf_1207 (357 target-flexibility) (102 robustness) daf:Desaf_1251 (790 target-flexibility) (134 robustness) daf:Desaf_1274 (528 target-flexibility) (157 robustness) daf:Desaf_1280 (0 target-flexibility) (0 robustness) daf:Desaf_1333 (0 target-flexibility) (0 robustness) daf:Desaf_1391 (790 target-flexibility) (134 robustness) daf:Desaf_1392 (821 target-flexibility) (137 robustness) daf:Desaf_1457 (212 target-flexibility) (73 robustness) daf:Desaf_1508 (0 target-flexibility) (0 robustness) daf:Desaf_1564 (796 target-flexibility) (85 robustness) daf:Desaf_1603 (0 target-flexibility) (0 robustness) daf:Desaf_1752 (1385 target-flexibility) (204 robustness) daf:Desaf_1776 (80 target-flexibility) (80 robustness) daf:Desaf_1964 (0 target-flexibility) (0 robustness) daf:Desaf_2034 (0 target-flexibility) (0 robustness) daf:Desaf_2132 (0 target-flexibility) (0 robustness) daf:Desaf_2183 (0 target-flexibility) (0 robustness) daf:Desaf_2261 (358 target-flexibility) (104 robustness) daf:Desaf_2280 (706 target-flexibility) (173 robustness) daf:Desaf_2305 (0 target-flexibility) (0 robustness) daf:Desaf_2308 (657 target-flexibility) (95 robustness) daf:Desaf_2339 (0 target-flexibility) (0 robustness) daf:Desaf_2347 (703 target-flexibility) (319 robustness) daf:Desaf_2349 (659 target-flexibility) (240 robustness) daf:Desaf_2350 (1108 target-flexibility) (319 robustness) daf:Desaf_2369 (357 target-flexibility) (102 robustness) daf:Desaf_2392 (600 target-flexibility) (126 robustness) daf:Desaf_2415 (0 target-flexibility) (0 robustness) daf:Desaf_2455 (1041 target-flexibility) (243 robustness) daf:Desaf_2481 (358 target-flexibility) (104 robustness) daf:Desaf_2490 (138 target-flexibility) (138 robustness) daf:Desaf_2502 (138 target-flexibility) (138 robustness) daf:Desaf_2509 (289 target-flexibility) (73 robustness) daf:Desaf_2698 (657 target-flexibility) (95 robustness) daf:Desaf_2718 (841 target-flexibility) (126 robustness) daf:Desaf_2806 (343 target-flexibility) (180 robustness) daf:Desaf_2884 (0 target-flexibility) (0 robustness) daf:Desaf_2887 (0 target-flexibility) (0 robustness) daf:Desaf_2906 (75 target-flexibility) (75 robustness) daf:Desaf_2907 (75 target-flexibility) (75 robustness) daf:Desaf_2909 (0 target-flexibility) (0 robustness) daf:Desaf_2926 (222 target-flexibility) (83 robustness) daf:Desaf_2946 (706 target-flexibility) (173 robustness) daf:Desaf_2970 (1169 target-flexibility) (76 robustness) daf:Desaf_2972 (0 target-flexibility) (0 robustness) daf:Desaf_3002 (902 target-flexibility) (228 robustness) daf:Desaf_3113 (138 target-flexibility) (138 robustness) daf:Desaf_3133 (706 target-flexibility) (173 robustness) daf:Desaf_3210 (0 target-flexibility) (0 robustness) daf:Desaf_3260 (434 target-flexibility) (67 robustness) daf:Desaf_3263 (841 target-flexibility) (126 robustness) daf:Desaf_3311 (0 target-flexibility) (0 robustness) daf:Desaf_3315 (0 target-flexibility) (0 robustness) daf:Desaf_3326 (902 target-flexibility) (228 robustness) daf:Desaf_3337 (706 target-flexibility) (173 robustness) daf:Desaf_3600 (468 target-flexibility) (75 robustness) daf:Desaf_3662 (659 target-flexibility) (240 robustness) daf:Desaf_3665 (703 target-flexibility) (319 robustness) daf:Desaf_3667 (343 target-flexibility) (180 robustness) daf:Desaf_3668 (0 target-flexibility) (0 robustness) daf:Desaf_3676 (703 target-flexibility) (319 robustness) daf:Desaf_3712 (821 target-flexibility) (137 robustness) dak:DaAHT2_0034 (600 target-flexibility) (126 robustness) dak:DaAHT2_0075 (138 target-flexibility) (138 robustness) dak:DaAHT2_0099 (1385 target-flexibility) (204 robustness) dak:DaAHT2_0100 (0 target-flexibility) (0 robustness) dak:DaAHT2_0107 (0 target-flexibility) (0 robustness) dak:DaAHT2_0190 (821 target-flexibility) (137 robustness) dak:DaAHT2_0251 (700 target-flexibility) (80 robustness) dak:DaAHT2_0308 (138 target-flexibility) (138 robustness) dak:DaAHT2_0356 (1385 target-flexibility) (204 robustness) dak:DaAHT2_0430 (607 target-flexibility) (75 robustness) dak:DaAHT2_0472 (0 target-flexibility) (0 robustness) dak:DaAHT2_0507 (357 target-flexibility) (102 robustness) dak:DaAHT2_0543 (841 target-flexibility) (126 robustness) dak:DaAHT2_0807 (841 target-flexibility) (126 robustness) dak:DaAHT2_0884 (279 target-flexibility) (126 robustness) dak:DaAHT2_0891 (706 target-flexibility) (173 robustness) dak:DaAHT2_0908 (686 target-flexibility) (192 robustness) dak:DaAHT2_1051 (212 target-flexibility) (73 robustness) dak:DaAHT2_1113 (703 target-flexibility) (319 robustness) dak:DaAHT2_1120 (659 target-flexibility) (240 robustness) dak:DaAHT2_1131 (0 target-flexibility) (0 robustness) dak:DaAHT2_1134 (703 target-flexibility) (319 robustness) dak:DaAHT2_1178 (222 target-flexibility) (83 robustness) dak:DaAHT2_1248 (691 target-flexibility) (528 robustness) dak:DaAHT2_1284 (703 target-flexibility) (319 robustness) dak:DaAHT2_1286 (659 target-flexibility) (240 robustness) dak:DaAHT2_1365 (686 target-flexibility) (192 robustness) dak:DaAHT2_1389 (0 target-flexibility) (0 robustness) dak:DaAHT2_1390 (0 target-flexibility) (0 robustness) dak:DaAHT2_1480 (70 target-flexibility) (70 robustness) dak:DaAHT2_1482 (140 target-flexibility) (71 robustness) dak:DaAHT2_1512 (607 target-flexibility) (75 robustness) dak:DaAHT2_1551 (91 target-flexibility) (91 robustness) dak:DaAHT2_1596 (91 target-flexibility) (91 robustness) dak:DaAHT2_1636 (732 target-flexibility) (78 robustness) dak:DaAHT2_1753 (821 target-flexibility) (137 robustness) dak:DaAHT2_1790 (0 target-flexibility) (0 robustness) dak:DaAHT2_1791 (0 target-flexibility) (0 robustness) dak:DaAHT2_1792 (0 target-flexibility) (0 robustness) dak:DaAHT2_1793 (0 target-flexibility) (0 robustness) dak:DaAHT2_1794 (0 target-flexibility) (0 robustness) dak:DaAHT2_1830 (0 target-flexibility) (0 robustness) dak:DaAHT2_1831 (0 target-flexibility) (0 robustness) dak:DaAHT2_1833 (0 target-flexibility) (0 robustness) dak:DaAHT2_1885 (691 target-flexibility) (528 robustness) dak:DaAHT2_1968 (0 target-flexibility) (0 robustness) dak:DaAHT2_1995 (357 target-flexibility) (102 robustness) dak:DaAHT2_2095 (600 target-flexibility) (126 robustness) dak:DaAHT2_2211 (138 target-flexibility) (66 robustness) dak:DaAHT2_2315 (897 target-flexibility) (71 robustness) dak:DaAHT2_2371 (796 target-flexibility) (85 robustness) dak:DaAHT2_2482 (821 target-flexibility) (137 robustness) dak:DaAHT2_2512 (706 target-flexibility) (173 robustness) dak:DaAHT2_2537 (80 target-flexibility) (80 robustness) dak:DaAHT2_2561 (0 target-flexibility) (0 robustness) dak:DaAHT2_2607 (700 target-flexibility) (80 robustness) dak:DaAHT2_2657 (279 target-flexibility) (126 robustness) dal:Dalk_0003 (0 target-flexibility) (0 robustness) dal:Dalk_0016 (732 target-flexibility) (78 robustness) dal:Dalk_0017 (405 target-flexibility) (169 robustness) dal:Dalk_0024 (691 target-flexibility) (528 robustness) dal:Dalk_0066 (0 target-flexibility) (0 robustness) dal:Dalk_0177 (0 target-flexibility) (0 robustness) dal:Dalk_0244 (330 target-flexibility) (76 robustness) dal:Dalk_0412 (239 target-flexibility) (99 robustness) dal:Dalk_0439 (91 target-flexibility) (91 robustness) dal:Dalk_0475 (0 target-flexibility) (0 robustness) dal:Dalk_0497 (212 target-flexibility) (73 robustness) dal:Dalk_0559 (269 target-flexibility) (64 robustness) dal:Dalk_0560 (902 target-flexibility) (228 robustness) dal:Dalk_0564 (841 target-flexibility) (126 robustness) dal:Dalk_0565 (841 target-flexibility) (126 robustness) dal:Dalk_0567 (1385 target-flexibility) (204 robustness) dal:Dalk_0568 (1108 target-flexibility) (319 robustness) dal:Dalk_0617 (330 target-flexibility) (76 robustness) dal:Dalk_0634 (0 target-flexibility) (0 robustness) dal:Dalk_0635 (0 target-flexibility) (0 robustness) dal:Dalk_0769 (358 target-flexibility) (104 robustness) dal:Dalk_0836 (1169 target-flexibility) (76 robustness) dal:Dalk_0853 (0 target-flexibility) (0 robustness) dal:Dalk_0888 (0 target-flexibility) (0 robustness) dal:Dalk_0935 (0 target-flexibility) (0 robustness) dal:Dalk_0939 (0 target-flexibility) (0 robustness) dal:Dalk_0954 (0 target-flexibility) (0 robustness) dal:Dalk_1064 (1041 target-flexibility) (243 robustness) dal:Dalk_1065 (1041 target-flexibility) (243 robustness) dal:Dalk_1066 (80 target-flexibility) (80 robustness) dal:Dalk_1076 (343 target-flexibility) (180 robustness) dal:Dalk_1103 (91 target-flexibility) (91 robustness) dal:Dalk_1159 (0 target-flexibility) (0 robustness) dal:Dalk_1193 (0 target-flexibility) (0 robustness) dal:Dalk_1228 (215 target-flexibility) (142 robustness) dal:Dalk_1240 (434 target-flexibility) (67 robustness) dal:Dalk_1314 (0 target-flexibility) (0 robustness) dal:Dalk_1315 (0 target-flexibility) (0 robustness) dal:Dalk_1397 (902 target-flexibility) (228 robustness) dal:Dalk_1414 (239 target-flexibility) (99 robustness) dal:Dalk_1434 (686 target-flexibility) (192 robustness) dal:Dalk_1438 (215 target-flexibility) (142 robustness) dal:Dalk_1587 (0 target-flexibility) (0 robustness) dal:Dalk_1693 (0 target-flexibility) (0 robustness) dal:Dalk_1699 (0 target-flexibility) (0 robustness) dal:Dalk_1700 (0 target-flexibility) (0 robustness) dal:Dalk_1704 (0 target-flexibility) (0 robustness) dal:Dalk_1711 (0 target-flexibility) (0 robustness) dal:Dalk_1752 (1108 target-flexibility) (319 robustness) dal:Dalk_1754 (503 target-flexibility) (78 robustness) dal:Dalk_1770 (222 target-flexibility) (83 robustness) dal:Dalk_1784 (71 target-flexibility) (71 robustness) dal:Dalk_1825 (269 target-flexibility) (64 robustness) dal:Dalk_1934 (289 target-flexibility) (73 robustness) dal:Dalk_1998 (691 target-flexibility) (528 robustness) dal:Dalk_2329 (790 target-flexibility) (134 robustness) dal:Dalk_2393 (0 target-flexibility) (0 robustness) dal:Dalk_2445 (0 target-flexibility) (0 robustness) dal:Dalk_2506 (175 target-flexibility) (96 robustness) dal:Dalk_2541 (0 target-flexibility) (0 robustness) dal:Dalk_2573 (497 target-flexibility) (186 robustness) dal:Dalk_2581 (0 target-flexibility) (0 robustness) dal:Dalk_2649 (358 target-flexibility) (124 robustness) dal:Dalk_2651 (528 target-flexibility) (157 robustness) dal:Dalk_2721 (1108 target-flexibility) (319 robustness) dal:Dalk_2752 (1041 target-flexibility) (243 robustness) dal:Dalk_2756 (752 target-flexibility) (76 robustness) dal:Dalk_2855 (80 target-flexibility) (80 robustness) dal:Dalk_2928 (0 target-flexibility) (0 robustness) dal:Dalk_2984 (0 target-flexibility) (0 robustness) dal:Dalk_3130 (70 target-flexibility) (70 robustness) dal:Dalk_3133 (140 target-flexibility) (71 robustness) dal:Dalk_3135 (67 target-flexibility) (67 robustness) dal:Dalk_3136 (239 target-flexibility) (67 robustness) dal:Dalk_3177 (497 target-flexibility) (186 robustness) dal:Dalk_3253 (175 target-flexibility) (96 robustness) dal:Dalk_3307 (659 target-flexibility) (240 robustness) dal:Dalk_3333 (0 target-flexibility) (0 robustness) dal:Dalk_3370 (1385 target-flexibility) (204 robustness) dal:Dalk_3440 (503 target-flexibility) (78 robustness) dal:Dalk_3481 (405 target-flexibility) (169 robustness) dal:Dalk_3482 (732 target-flexibility) (78 robustness) dal:Dalk_3651 (0 target-flexibility) (0 robustness) dal:Dalk_3803 (0 target-flexibility) (0 robustness) dal:Dalk_3820 (358 target-flexibility) (104 robustness) dal:Dalk_3872 (0 target-flexibility) (0 robustness) dal:Dalk_3886 (0 target-flexibility) (0 robustness) dal:Dalk_3893 (343 target-flexibility) (180 robustness) dal:Dalk_3901 (0 target-flexibility) (0 robustness) dal:Dalk_3912 (659 target-flexibility) (240 robustness) dal:Dalk_3962 (686 target-flexibility) (192 robustness) dal:Dalk_4029 (239 target-flexibility) (99 robustness) dal:Dalk_4104 (0 target-flexibility) (0 robustness) dal:Dalk_4163 (902 target-flexibility) (228 robustness) dal:Dalk_4201 (0 target-flexibility) (0 robustness) dal:Dalk_4640 (0 target-flexibility) (0 robustness) dal:Dalk_4695 (0 target-flexibility) (0 robustness) dal:Dalk_4696 (0 target-flexibility) (0 robustness) dal:Dalk_4854 (659 target-flexibility) (240 robustness) dal:Dalk_5019 (902 target-flexibility) (228 robustness) dal:Dalk_5220 (358 target-flexibility) (124 robustness) dao:Desac_0009 (897 target-flexibility) (71 robustness) dao:Desac_0097 (0 target-flexibility) (0 robustness) dao:Desac_0099 (0 target-flexibility) (0 robustness) dao:Desac_0208 (175 target-flexibility) (96 robustness) dao:Desac_0239 (0 target-flexibility) (0 robustness) dao:Desac_0259 (358 target-flexibility) (104 robustness) dao:Desac_0291 (0 target-flexibility) (0 robustness) dao:Desac_0292 (0 target-flexibility) (0 robustness) dao:Desac_0299 (706 target-flexibility) (173 robustness) dao:Desac_0380 (1385 target-flexibility) (204 robustness) dao:Desac_0436 (706 target-flexibility) (173 robustness) dao:Desac_0448 (0 target-flexibility) (0 robustness) dao:Desac_0519 (732 target-flexibility) (78 robustness) dao:Desac_0596 (70 target-flexibility) (70 robustness) dao:Desac_0599 (140 target-flexibility) (71 robustness) dao:Desac_0601 (67 target-flexibility) (67 robustness) dao:Desac_0602 (239 target-flexibility) (67 robustness) dao:Desac_0671 (600 target-flexibility) (126 robustness) dao:Desac_0739 (686 target-flexibility) (192 robustness) dao:Desac_0932 (821 target-flexibility) (137 robustness) dao:Desac_0945 (139 target-flexibility) (66 robustness) dao:Desac_0972 (206 target-flexibility) (68 robustness) dao:Desac_1050 (405 target-flexibility) (169 robustness) dao:Desac_1090 (358 target-flexibility) (104 robustness) dao:Desac_1107 (0 target-flexibility) (0 robustness) dao:Desac_1133 (706 target-flexibility) (173 robustness) dao:Desac_1164 (350 target-flexibility) (189 robustness) dao:Desac_1186 (0 target-flexibility) (0 robustness) dao:Desac_1281 (657 target-flexibility) (95 robustness) dao:Desac_1300 (289 target-flexibility) (73 robustness) dao:Desac_1335 (821 target-flexibility) (137 robustness) dao:Desac_1395 (175 target-flexibility) (96 robustness) dao:Desac_1415 (212 target-flexibility) (73 robustness) dao:Desac_1501 (0 target-flexibility) (0 robustness) dao:Desac_1607 (706 target-flexibility) (173 robustness) dao:Desac_1631 (0 target-flexibility) (0 robustness) dao:Desac_1664 (821 target-flexibility) (137 robustness) dao:Desac_1681 (350 target-flexibility) (189 robustness) dao:Desac_1741 (0 target-flexibility) (0 robustness) dao:Desac_1774 (706 target-flexibility) (173 robustness) dao:Desac_1831 (215 target-flexibility) (142 robustness) dao:Desac_1840 (0 target-flexibility) (0 robustness) dao:Desac_1859 (657 target-flexibility) (95 robustness) dao:Desac_1883 (0 target-flexibility) (0 robustness) dao:Desac_1973 (600 target-flexibility) (126 robustness) dao:Desac_2015 (0 target-flexibility) (0 robustness) dao:Desac_2143 (691 target-flexibility) (528 robustness) dao:Desac_2147 (405 target-flexibility) (169 robustness) dao:Desac_2262 (0 target-flexibility) (0 robustness) dao:Desac_2332 (841 target-flexibility) (126 robustness) dao:Desac_2394 (706 target-flexibility) (173 robustness) dao:Desac_2412 (0 target-flexibility) (0 robustness) dao:Desac_2427 (1385 target-flexibility) (204 robustness) dao:Desac_2446 (691 target-flexibility) (528 robustness) dao:Desac_2462 (796 target-flexibility) (85 robustness) dao:Desac_2478 (138 target-flexibility) (66 robustness) dao:Desac_2517 (0 target-flexibility) (0 robustness) dao:Desac_2526 (841 target-flexibility) (126 robustness) dao:Desac_2541 (0 target-flexibility) (0 robustness) dao:Desac_2544 (0 target-flexibility) (0 robustness) dao:Desac_2573 (215 target-flexibility) (142 robustness) dao:Desac_2593 (80 target-flexibility) (80 robustness) dao:Desac_2664 (821 target-flexibility) (137 robustness) dao:Desac_2676 (634 target-flexibility) (72 robustness) dao:Desac_2680 (686 target-flexibility) (192 robustness) dao:Desac_2702 (634 target-flexibility) (72 robustness) dao:Desac_2715 (139 target-flexibility) (66 robustness) dao:Desac_2722 (71 target-flexibility) (71 robustness) dao:Desac_2817 (0 target-flexibility) (0 robustness) dao:Desac_2831 (350 target-flexibility) (189 robustness) dao:Desac_2837 (0 target-flexibility) (0 robustness) dao:Desac_2908 (222 target-flexibility) (83 robustness) dao:Desac_2922 (434 target-flexibility) (67 robustness) das:Daes_0042 (902 target-flexibility) (228 robustness) das:Daes_0076 (1041 target-flexibility) (243 robustness) das:Daes_0077 (1041 target-flexibility) (243 robustness) das:Daes_0119 (706 target-flexibility) (173 robustness) das:Daes_0128 (706 target-flexibility) (173 robustness) das:Daes_0165 (0 target-flexibility) (0 robustness) das:Daes_0202 (790 target-flexibility) (134 robustness) das:Daes_0235 (752 target-flexibility) (76 robustness) das:Daes_0296 (0 target-flexibility) (0 robustness) das:Daes_0316 (358 target-flexibility) (104 robustness) das:Daes_0542 (790 target-flexibility) (134 robustness) das:Daes_0593 (0 target-flexibility) (0 robustness) das:Daes_0665 (790 target-flexibility) (134 robustness) das:Daes_0687 (1385 target-flexibility) (204 robustness) das:Daes_0700 (821 target-flexibility) (137 robustness) das:Daes_0715 (821 target-flexibility) (137 robustness) das:Daes_0716 (821 target-flexibility) (137 robustness) das:Daes_0744 (212 target-flexibility) (73 robustness) das:Daes_0753 (80 target-flexibility) (80 robustness) das:Daes_0791 (0 target-flexibility) (0 robustness) das:Daes_0911 (1169 target-flexibility) (76 robustness) das:Daes_0937 (0 target-flexibility) (0 robustness) das:Daes_0961 (0 target-flexibility) (0 robustness) das:Daes_1012 (706 target-flexibility) (173 robustness) das:Daes_1070 (0 target-flexibility) (0 robustness) das:Daes_1136 (357 target-flexibility) (115 robustness) das:Daes_1192 (706 target-flexibility) (173 robustness) das:Daes_1225 (0 target-flexibility) (0 robustness) das:Daes_1318 (0 target-flexibility) (0 robustness) das:Daes_1343 (138 target-flexibility) (138 robustness) das:Daes_1374 (0 target-flexibility) (0 robustness) das:Daes_1375 (0 target-flexibility) (0 robustness) das:Daes_1396 (71 target-flexibility) (71 robustness) das:Daes_1451 (711 target-flexibility) (104 robustness) das:Daes_1558 (330 target-flexibility) (76 robustness) das:Daes_1679 (706 target-flexibility) (173 robustness) das:Daes_1696 (902 target-flexibility) (228 robustness) das:Daes_1706 (528 target-flexibility) (157 robustness) das:Daes_1709 (222 target-flexibility) (83 robustness) das:Daes_1744 (841 target-flexibility) (126 robustness) das:Daes_1746 (600 target-flexibility) (126 robustness) das:Daes_1774 (902 target-flexibility) (228 robustness) das:Daes_1775 (902 target-flexibility) (228 robustness) das:Daes_1798 (0 target-flexibility) (0 robustness) das:Daes_1823 (138 target-flexibility) (138 robustness) das:Daes_1850 (206 target-flexibility) (68 robustness) das:Daes_1909 (434 target-flexibility) (67 robustness) das:Daes_1912 (841 target-flexibility) (126 robustness) das:Daes_1972 (1041 target-flexibility) (243 robustness) das:Daes_1973 (1041 target-flexibility) (243 robustness) das:Daes_1991 (0 target-flexibility) (0 robustness) das:Daes_1992 (0 target-flexibility) (0 robustness) das:Daes_2032 (0 target-flexibility) (0 robustness) das:Daes_2080 (711 target-flexibility) (104 robustness) das:Daes_2107 (0 target-flexibility) (0 robustness) das:Daes_2166 (659 target-flexibility) (240 robustness) das:Daes_2209 (390 target-flexibility) (74 robustness) das:Daes_2276 (231 target-flexibility) (158 robustness) das:Daes_2350 (358 target-flexibility) (104 robustness) das:Daes_2546 (414 target-flexibility) (96 robustness) das:Daes_2549 (600 target-flexibility) (126 robustness) das:Daes_2550 (390 target-flexibility) (74 robustness) das:Daes_2552 (1784 target-flexibility) (162 robustness) das:Daes_2553 (330 target-flexibility) (76 robustness) das:Daes_2554 (1041 target-flexibility) (243 robustness) das:Daes_2654 (0 target-flexibility) (0 robustness) das:Daes_2678 (289 target-flexibility) (73 robustness) das:Daes_2714 (231 target-flexibility) (158 robustness) das:Daes_2770 (1784 target-flexibility) (162 robustness) das:Daes_2796 (659 target-flexibility) (240 robustness) das:Daes_2821 (0 target-flexibility) (0 robustness) das:Daes_2846 (0 target-flexibility) (0 robustness) das:Daes_2852 (0 target-flexibility) (0 robustness) das:Daes_2857 (0 target-flexibility) (0 robustness) das:Daes_2884 (0 target-flexibility) (0 robustness) das:Daes_2972 (0 target-flexibility) (0 robustness) das:Daes_3018 (0 target-flexibility) (0 robustness) das:Daes_3100 (1385 target-flexibility) (204 robustness) das:Daes_3138 (1041 target-flexibility) (243 robustness) das:Daes_3139 (414 target-flexibility) (96 robustness) das:Daes_3214 (0 target-flexibility) (0 robustness) das:Daes_3270 (0 target-flexibility) (0 robustness) das:Daes_3284 (357 target-flexibility) (115 robustness) das:Daes_3309 (821 target-flexibility) (137 robustness) das:Daes_3345 (0 target-flexibility) (0 robustness) dat:HRM2_00520 (350 target-flexibility) (84 robustness) dat:HRM2_00970 (657 target-flexibility) (95 robustness) dat:HRM2_01190 (269 target-flexibility) (64 robustness) dat:HRM2_01900 (103 target-flexibility) (103 robustness) dat:HRM2_02030 (0 target-flexibility) (0 robustness) dat:HRM2_02690 (0 target-flexibility) (0 robustness) dat:HRM2_02700 (0 target-flexibility) (0 robustness) dat:HRM2_02710 (924 target-flexibility) (101 robustness) dat:HRM2_03210 (497 target-flexibility) (186 robustness) dat:HRM2_03220 (497 target-flexibility) (186 robustness) dat:HRM2_04430 (434 target-flexibility) (67 robustness) dat:HRM2_06820 (357 target-flexibility) (115 robustness) dat:HRM2_06910 (528 target-flexibility) (157 robustness) dat:HRM2_07180 (706 target-flexibility) (173 robustness) dat:HRM2_07280 (323 target-flexibility) (101 robustness) dat:HRM2_07460 (350 target-flexibility) (84 robustness) dat:HRM2_07760 (497 target-flexibility) (186 robustness) dat:HRM2_07770 (497 target-flexibility) (186 robustness) dat:HRM2_08100 (215 target-flexibility) (142 robustness) dat:HRM2_08490 (0 target-flexibility) (0 robustness) dat:HRM2_08630 (600 target-flexibility) (126 robustness) dat:HRM2_08850 (790 target-flexibility) (134 robustness) dat:HRM2_10630 (239 target-flexibility) (99 robustness) dat:HRM2_11950 (790 target-flexibility) (134 robustness) dat:HRM2_12400 (600 target-flexibility) (126 robustness) dat:HRM2_12660 (239 target-flexibility) (67 robustness) dat:HRM2_12670 (67 target-flexibility) (67 robustness) dat:HRM2_13230 (231 target-flexibility) (158 robustness) dat:HRM2_13240 (231 target-flexibility) (158 robustness) dat:HRM2_13680 (0 target-flexibility) (0 robustness) dat:HRM2_14270 (700 target-flexibility) (89 robustness) dat:HRM2_15420 (0 target-flexibility) (0 robustness) dat:HRM2_15450 (0 target-flexibility) (0 robustness) dat:HRM2_16000 (634 target-flexibility) (72 robustness) dat:HRM2_16260 (706 target-flexibility) (173 robustness) dat:HRM2_16810 (657 target-flexibility) (95 robustness) dat:HRM2_17690 (634 target-flexibility) (72 robustness) dat:HRM2_17700 (215 target-flexibility) (142 robustness) dat:HRM2_17850 (64 target-flexibility) (64 robustness) dat:HRM2_18570 (0 target-flexibility) (0 robustness) dat:HRM2_20030 (0 target-flexibility) (0 robustness) dat:HRM2_20130 (358 target-flexibility) (104 robustness) dat:HRM2_20900 (212 target-flexibility) (73 robustness) dat:HRM2_20960 (841 target-flexibility) (126 robustness) dat:HRM2_20970 (841 target-flexibility) (126 robustness) dat:HRM2_20990 (902 target-flexibility) (228 robustness) dat:HRM2_21000 (269 target-flexibility) (64 robustness) dat:HRM2_21490 (0 target-flexibility) (0 robustness) dat:HRM2_21650 (0 target-flexibility) (0 robustness) dat:HRM2_22520 (150 target-flexibility) (76 robustness) dat:HRM2_22630 (497 target-flexibility) (186 robustness) dat:HRM2_22950 (706 target-flexibility) (173 robustness) dat:HRM2_23040 (0 target-flexibility) (0 robustness) dat:HRM2_23300 (358 target-flexibility) (104 robustness) dat:HRM2_23600 (0 target-flexibility) (0 robustness) dat:HRM2_23610 (0 target-flexibility) (0 robustness) dat:HRM2_23910 (0 target-flexibility) (0 robustness) dat:HRM2_24160 (0 target-flexibility) (0 robustness) dat:HRM2_24750 (0 target-flexibility) (0 robustness) dat:HRM2_24890 (222 target-flexibility) (83 robustness) dat:HRM2_25010 (323 target-flexibility) (101 robustness) dat:HRM2_25160 (0 target-flexibility) (0 robustness) dat:HRM2_25240 (0 target-flexibility) (0 robustness) dat:HRM2_25270 (0 target-flexibility) (0 robustness) dat:HRM2_26740 (358 target-flexibility) (104 robustness) dat:HRM2_27190 (0 target-flexibility) (0 robustness) dat:HRM2_27560 (138 target-flexibility) (66 robustness) dat:HRM2_27780 (897 target-flexibility) (71 robustness) dat:HRM2_27920 (600 target-flexibility) (126 robustness) dat:HRM2_28280 (0 target-flexibility) (0 robustness) dat:HRM2_28700 (0 target-flexibility) (0 robustness) dat:HRM2_28720 (790 target-flexibility) (134 robustness) dat:HRM2_29000 (0 target-flexibility) (0 robustness) dat:HRM2_29030 (902 target-flexibility) (228 robustness) dat:HRM2_29750 (0 target-flexibility) (0 robustness) dat:HRM2_31180 (0 target-flexibility) (0 robustness) dat:HRM2_34830 (64 target-flexibility) (64 robustness) dat:HRM2_34850 (358 target-flexibility) (124 robustness) dat:HRM2_35730 (0 target-flexibility) (0 robustness) dat:HRM2_35740 (0 target-flexibility) (0 robustness) dat:HRM2_35870 (752 target-flexibility) (105 robustness) dat:HRM2_35970 (700 target-flexibility) (89 robustness) dat:HRM2_36790 (0 target-flexibility) (0 robustness) dat:HRM2_36840 (0 target-flexibility) (0 robustness) dat:HRM2_37410 (239 target-flexibility) (99 robustness) dat:HRM2_37910 (0 target-flexibility) (0 robustness) dat:HRM2_38170 (706 target-flexibility) (173 robustness) dat:HRM2_38500 (924 target-flexibility) (101 robustness) dat:HRM2_41030 (289 target-flexibility) (73 robustness) dat:HRM2_41050 (924 target-flexibility) (101 robustness) dat:HRM2_41130 (358 target-flexibility) (124 robustness) dat:HRM2_41270 (0 target-flexibility) (0 robustness) dat:HRM2_42310 (497 target-flexibility) (186 robustness) dat:HRM2_42320 (497 target-flexibility) (186 robustness) dat:HRM2_42990 (706 target-flexibility) (173 robustness) dat:HRM2_43380 (323 target-flexibility) (101 robustness) dat:HRM2_43510 (150 target-flexibility) (76 robustness) dat:HRM2_43540 (0 target-flexibility) (0 robustness) dat:HRM2_45040 (103 target-flexibility) (103 robustness) dat:HRM2_45740 (357 target-flexibility) (115 robustness) dat:HRM2_45800 (752 target-flexibility) (105 robustness) dat:HRM2_46050 (706 target-flexibility) (173 robustness) dat:HRM2_47210 (790 target-flexibility) (134 robustness) dat:HRM2_47820 (0 target-flexibility) (0 robustness) dat:HRM2_47830 (0 target-flexibility) (0 robustness) dav:DESACE_00060 (1041 target-flexibility) (243 robustness) dav:DESACE_00450 (262 target-flexibility) (86 robustness) dav:DESACE_00685 (0 target-flexibility) (0 robustness) dav:DESACE_01185 (212 target-flexibility) (73 robustness) dav:DESACE_01385 (841 target-flexibility) (126 robustness) dav:DESACE_02070 (0 target-flexibility) (0 robustness) dav:DESACE_02195 (0 target-flexibility) (0 robustness) dav:DESACE_02280 (686 target-flexibility) (192 robustness) dav:DESACE_02320 (222 target-flexibility) (83 robustness) dav:DESACE_03005 (67 target-flexibility) (67 robustness) dav:DESACE_03010 (239 target-flexibility) (67 robustness) dav:DESACE_03180 (1169 target-flexibility) (76 robustness) dav:DESACE_03245 (70 target-flexibility) (70 robustness) dav:DESACE_03335 (262 target-flexibility) (86 robustness) dav:DESACE_03540 (0 target-flexibility) (0 robustness) dav:DESACE_03685 (0 target-flexibility) (0 robustness) dav:DESACE_03690 (0 target-flexibility) (0 robustness) dav:DESACE_03885 (0 target-flexibility) (0 robustness) dav:DESACE_03890 (0 target-flexibility) (0 robustness) dav:DESACE_04505 (0 target-flexibility) (0 robustness) dav:DESACE_05445 (790 target-flexibility) (134 robustness) dav:DESACE_05855 (841 target-flexibility) (126 robustness) dav:DESACE_05935 (80 target-flexibility) (80 robustness) dav:DESACE_06220 (0 target-flexibility) (0 robustness) dav:DESACE_06395 (691 target-flexibility) (528 robustness) dav:DESACE_06745 (0 target-flexibility) (0 robustness) dav:DESACE_06750 (0 target-flexibility) (0 robustness) dav:DESACE_06860 (924 target-flexibility) (101 robustness) dav:DESACE_06865 (841 target-flexibility) (126 robustness) dav:DESACE_07825 (691 target-flexibility) (528 robustness) dav:DESACE_08090 (686 target-flexibility) (192 robustness) dav:DESACE_08345 (924 target-flexibility) (101 robustness) dav:DESACE_08465 (0 target-flexibility) (0 robustness) dav:DESACE_08495 (790 target-flexibility) (134 robustness) dav:DESACE_08570 (0 target-flexibility) (0 robustness) dav:DESACE_08765 (0 target-flexibility) (0 robustness) dav:DESACE_08825 (0 target-flexibility) (0 robustness) dav:DESACE_09325 (924 target-flexibility) (101 robustness) dba:Dbac_0057 (0 target-flexibility) (0 robustness) dba:Dbac_0065 (703 target-flexibility) (319 robustness) dba:Dbac_0075 (357 target-flexibility) (102 robustness) dba:Dbac_0093 (600 target-flexibility) (126 robustness) dba:Dbac_0109 (790 target-flexibility) (134 robustness) dba:Dbac_0125 (821 target-flexibility) (137 robustness) dba:Dbac_0193 (855 target-flexibility) (138 robustness) dba:Dbac_0212 (706 target-flexibility) (173 robustness) dba:Dbac_0246 (138 target-flexibility) (66 robustness) dba:Dbac_0265 (0 target-flexibility) (0 robustness) dba:Dbac_0408 (902 target-flexibility) (228 robustness) dba:Dbac_0409 (902 target-flexibility) (228 robustness) dba:Dbac_0488 (222 target-flexibility) (83 robustness) dba:Dbac_0489 (0 target-flexibility) (0 robustness) dba:Dbac_0773 (0 target-flexibility) (0 robustness) dba:Dbac_0780 (0 target-flexibility) (0 robustness) dba:Dbac_0797 (0 target-flexibility) (0 robustness) dba:Dbac_0874 (706 target-flexibility) (173 robustness) dba:Dbac_0912 (138 target-flexibility) (138 robustness) dba:Dbac_0961 (686 target-flexibility) (192 robustness) dba:Dbac_0984 (0 target-flexibility) (0 robustness) dba:Dbac_1000 (0 target-flexibility) (0 robustness) dba:Dbac_1036 (358 target-flexibility) (104 robustness) dba:Dbac_1178 (0 target-flexibility) (0 robustness) dba:Dbac_1438 (497 target-flexibility) (186 robustness) dba:Dbac_1478 (790 target-flexibility) (134 robustness) dba:Dbac_1498 (0 target-flexibility) (0 robustness) dba:Dbac_1611 (0 target-flexibility) (0 robustness) dba:Dbac_1690 (0 target-flexibility) (0 robustness) dba:Dbac_1740 (434 target-flexibility) (67 robustness) dba:Dbac_1743 (841 target-flexibility) (126 robustness) dba:Dbac_1754 (138 target-flexibility) (138 robustness) dba:Dbac_1826 (0 target-flexibility) (0 robustness) dba:Dbac_1870 (0 target-flexibility) (0 robustness) dba:Dbac_1886 (706 target-flexibility) (173 robustness) dba:Dbac_1951 (357 target-flexibility) (102 robustness) dba:Dbac_1988 (706 target-flexibility) (173 robustness) dba:Dbac_2044 (706 target-flexibility) (173 robustness) dba:Dbac_2287 (0 target-flexibility) (0 robustness) dba:Dbac_2388 (821 target-flexibility) (137 robustness) dba:Dbac_2557 (0 target-flexibility) (0 robustness) dba:Dbac_2558 (0 target-flexibility) (0 robustness) dba:Dbac_2718 (0 target-flexibility) (0 robustness) dba:Dbac_2833 (796 target-flexibility) (85 robustness) dba:Dbac_2884 (0 target-flexibility) (0 robustness) dba:Dbac_2987 (1385 target-flexibility) (204 robustness) dba:Dbac_3325 (0 target-flexibility) (0 robustness) dbr:Deba_0015 (0 target-flexibility) (0 robustness) dbr:Deba_0117 (330 target-flexibility) (76 robustness) dbr:Deba_0131 (343 target-flexibility) (180 robustness) dbr:Deba_0146 (0 target-flexibility) (0 robustness) dbr:Deba_0206 (91 target-flexibility) (91 robustness) dbr:Deba_0233 (691 target-flexibility) (528 robustness) dbr:Deba_0292 (796 target-flexibility) (85 robustness) dbr:Deba_0300 (686 target-flexibility) (192 robustness) dbr:Deba_0342 (434 target-flexibility) (67 robustness) dbr:Deba_0413 (222 target-flexibility) (83 robustness) dbr:Deba_0419 (0 target-flexibility) (0 robustness) dbr:Deba_0425 (0 target-flexibility) (0 robustness) dbr:Deba_0534 (358 target-flexibility) (104 robustness) dbr:Deba_0577 (80 target-flexibility) (80 robustness) dbr:Deba_0581 (0 target-flexibility) (0 robustness) dbr:Deba_0585 (790 target-flexibility) (134 robustness) dbr:Deba_0606 (0 target-flexibility) (0 robustness) dbr:Deba_0633 (686 target-flexibility) (192 robustness) dbr:Deba_0753 (841 target-flexibility) (126 robustness) dbr:Deba_0853 (0 target-flexibility) (0 robustness) dbr:Deba_0943 (841 target-flexibility) (126 robustness) dbr:Deba_0967 (361 target-flexibility) (101 robustness) dbr:Deba_0994 (0 target-flexibility) (0 robustness) dbr:Deba_1017 (0 target-flexibility) (0 robustness) dbr:Deba_1025 (80 target-flexibility) (80 robustness) dbr:Deba_1107 (343 target-flexibility) (180 robustness) dbr:Deba_1178 (528 target-flexibility) (157 robustness) dbr:Deba_1275 (289 target-flexibility) (73 robustness) dbr:Deba_1412 (0 target-flexibility) (0 robustness) dbr:Deba_1430 (659 target-flexibility) (240 robustness) dbr:Deba_1479 (0 target-flexibility) (0 robustness) dbr:Deba_1506 (497 target-flexibility) (186 robustness) dbr:Deba_1628 (0 target-flexibility) (0 robustness) dbr:Deba_1734 (1385 target-flexibility) (204 robustness) dbr:Deba_1780 (0 target-flexibility) (0 robustness) dbr:Deba_1849 (361 target-flexibility) (101 robustness) dbr:Deba_1882 (138 target-flexibility) (66 robustness) dbr:Deba_1967 (330 target-flexibility) (76 robustness) dbr:Deba_1979 (1385 target-flexibility) (204 robustness) dbr:Deba_2001 (212 target-flexibility) (73 robustness) dbr:Deba_2032 (91 target-flexibility) (91 robustness) dbr:Deba_2122 (790 target-flexibility) (134 robustness) dbr:Deba_2140 (0 target-flexibility) (0 robustness) dbr:Deba_2198 (323 target-flexibility) (101 robustness) dbr:Deba_2288 (0 target-flexibility) (0 robustness) dbr:Deba_2388 (659 target-flexibility) (240 robustness) dbr:Deba_2415 (691 target-flexibility) (528 robustness) dbr:Deba_2503 (790 target-flexibility) (134 robustness) dbr:Deba_2637 (0 target-flexibility) (0 robustness) dbr:Deba_2654 (897 target-flexibility) (71 robustness) dbr:Deba_2748 (0 target-flexibility) (0 robustness) dbr:Deba_2773 (0 target-flexibility) (0 robustness) dbr:Deba_2788 (239 target-flexibility) (67 robustness) dbr:Deba_2789 (67 target-flexibility) (67 robustness) dbr:Deba_2791 (140 target-flexibility) (71 robustness) dbr:Deba_2794 (70 target-flexibility) (70 robustness) dbr:Deba_2981 (323 target-flexibility) (101 robustness) dbr:Deba_3012 (497 target-flexibility) (186 robustness) dbr:Deba_3094 (0 target-flexibility) (0 robustness) dbr:Deba_3125 (732 target-flexibility) (78 robustness) dbr:Deba_3185 (215 target-flexibility) (142 robustness) dbr:Deba_3187 (790 target-flexibility) (134 robustness) dbr:Deba_3214 (215 target-flexibility) (142 robustness) dbr:Deba_3263 (358 target-flexibility) (104 robustness) dde:Dde_0033 (0 target-flexibility) (0 robustness) dde:Dde_0065 (855 target-flexibility) (138 robustness) dde:Dde_0079 (686 target-flexibility) (192 robustness) dde:Dde_0193 (0 target-flexibility) (0 robustness) dde:Dde_0210 (138 target-flexibility) (138 robustness) dde:Dde_0230 (0 target-flexibility) (0 robustness) dde:Dde_0255 (855 target-flexibility) (138 robustness) dde:Dde_0366 (231 target-flexibility) (158 robustness) dde:Dde_0398 (902 target-flexibility) (228 robustness) dde:Dde_0408 (497 target-flexibility) (186 robustness) dde:Dde_0427 (0 target-flexibility) (0 robustness) dde:Dde_0465 (138 target-flexibility) (138 robustness) dde:Dde_0540 (0 target-flexibility) (0 robustness) dde:Dde_0604 (706 target-flexibility) (173 robustness) dde:Dde_0626 (405 target-flexibility) (70 robustness) dde:Dde_0836 (0 target-flexibility) (0 robustness) dde:Dde_0972 (0 target-flexibility) (0 robustness) dde:Dde_1087 (0 target-flexibility) (0 robustness) dde:Dde_1103 (1385 target-flexibility) (204 robustness) dde:Dde_1203 (138 target-flexibility) (138 robustness) dde:Dde_1225 (350 target-flexibility) (189 robustness) dde:Dde_1254 (301 target-flexibility) (154 robustness) dde:Dde_1255 (301 target-flexibility) (154 robustness) dde:Dde_1379 (0 target-flexibility) (0 robustness) dde:Dde_1424 (0 target-flexibility) (0 robustness) dde:Dde_1558 (0 target-flexibility) (0 robustness) dde:Dde_1725 (0 target-flexibility) (0 robustness) dde:Dde_1978 (239 target-flexibility) (99 robustness) dde:Dde_2004 (357 target-flexibility) (102 robustness) dde:Dde_2049 (841 target-flexibility) (126 robustness) dde:Dde_2066 (138 target-flexibility) (138 robustness) dde:Dde_2080 (706 target-flexibility) (173 robustness) dde:Dde_2084 (0 target-flexibility) (0 robustness) dde:Dde_2142 (222 target-flexibility) (83 robustness) dde:Dde_2151 (138 target-flexibility) (138 robustness) dde:Dde_2168 (902 target-flexibility) (228 robustness) dde:Dde_2182 (0 target-flexibility) (0 robustness) dde:Dde_2187 (0 target-flexibility) (0 robustness) dde:Dde_2317 (790 target-flexibility) (134 robustness) dde:Dde_2342 (600 target-flexibility) (126 robustness) dde:Dde_2431 (703 target-flexibility) (319 robustness) dde:Dde_2439 (0 target-flexibility) (0 robustness) dde:Dde_2648 (357 target-flexibility) (102 robustness) dde:Dde_2656 (0 target-flexibility) (0 robustness) dde:Dde_2660 (703 target-flexibility) (319 robustness) dde:Dde_2664 (239 target-flexibility) (99 robustness) dde:Dde_2823 (790 target-flexibility) (134 robustness) dde:Dde_2839 (212 target-flexibility) (73 robustness) dde:Dde_2888 (0 target-flexibility) (0 robustness) dde:Dde_2891 (821 target-flexibility) (137 robustness) dde:Dde_3042 (231 target-flexibility) (158 robustness) dde:Dde_3062 (0 target-flexibility) (0 robustness) dde:Dde_3088 (0 target-flexibility) (0 robustness) dde:Dde_3126 (0 target-flexibility) (0 robustness) dde:Dde_3180 (80 target-flexibility) (80 robustness) dde:Dde_3207 (790 target-flexibility) (134 robustness) dde:Dde_3218 (841 target-flexibility) (126 robustness) dde:Dde_3222 (434 target-flexibility) (67 robustness) dde:Dde_3228 (0 target-flexibility) (0 robustness) dde:Dde_3239 (0 target-flexibility) (0 robustness) dde:Dde_3317 (821 target-flexibility) (137 robustness) dde:Dde_3397 (350 target-flexibility) (189 robustness) dde:Dde_3457 (0 target-flexibility) (0 robustness) dde:Dde_3476 (289 target-flexibility) (73 robustness) dde:Dde_3479 (686 target-flexibility) (192 robustness) dde:Dde_3523 (0 target-flexibility) (0 robustness) dde:Dde_3534 (0 target-flexibility) (0 robustness) dde:Dde_3596 (1385 target-flexibility) (204 robustness) dde:Dde_3638 (301 target-flexibility) (154 robustness) dde:Dde_3639 (301 target-flexibility) (154 robustness) dde:Dde_3647 (70 target-flexibility) (70 robustness) dde:Dde_3677 (821 target-flexibility) (137 robustness) dde:Dde_3687 (70 target-flexibility) (70 robustness) dde:Dde_3691 (0 target-flexibility) (0 robustness) dde:Dde_3733 (497 target-flexibility) (186 robustness) dde:Dde_3736 (600 target-flexibility) (126 robustness) dds:Ddes_0025 (0 target-flexibility) (0 robustness) dds:Ddes_0101 (289 target-flexibility) (73 robustness) dds:Ddes_0114 (138 target-flexibility) (138 robustness) dds:Ddes_0132 (600 target-flexibility) (126 robustness) dds:Ddes_0151 (323 target-flexibility) (101 robustness) dds:Ddes_0192 (357 target-flexibility) (102 robustness) dds:Ddes_0319 (0 target-flexibility) (0 robustness) dds:Ddes_0385 (222 target-flexibility) (83 robustness) dds:Ddes_0559 (0 target-flexibility) (0 robustness) dds:Ddes_0583 (686 target-flexibility) (192 robustness) dds:Ddes_0828 (0 target-flexibility) (0 robustness) dds:Ddes_0939 (0 target-flexibility) (0 robustness) dds:Ddes_1149 (357 target-flexibility) (115 robustness) dds:Ddes_1253 (0 target-flexibility) (0 robustness) dds:Ddes_1300 (0 target-flexibility) (0 robustness) dds:Ddes_1416 (323 target-flexibility) (101 robustness) dds:Ddes_1552 (706 target-flexibility) (173 robustness) dds:Ddes_1565 (706 target-flexibility) (173 robustness) dds:Ddes_1568 (706 target-flexibility) (173 robustness) dds:Ddes_1623 (0 target-flexibility) (0 robustness) dds:Ddes_1685 (697 target-flexibility) (78 robustness) dds:Ddes_1771 (0 target-flexibility) (0 robustness) dds:Ddes_2089 (1385 target-flexibility) (204 robustness) def:CNY67_00560 (289 target-flexibility) (73 robustness) def:CNY67_00625 (138 target-flexibility) (138 robustness) def:CNY67_00735 (600 target-flexibility) (126 robustness) def:CNY67_00845 (323 target-flexibility) (101 robustness) def:CNY67_00890 (600 target-flexibility) (126 robustness) def:CNY67_01635 (1385 target-flexibility) (204 robustness) def:CNY67_01730 (212 target-flexibility) (73 robustness) def:CNY67_01860 (0 target-flexibility) (0 robustness) def:CNY67_02160 (0 target-flexibility) (0 robustness) def:CNY67_02680 (902 target-flexibility) (228 robustness) def:CNY67_03590 (0 target-flexibility) (0 robustness) def:CNY67_03595 (0 target-flexibility) (0 robustness) def:CNY67_03610 (357 target-flexibility) (102 robustness) def:CNY67_03710 (790 target-flexibility) (134 robustness) def:CNY67_04680 (706 target-flexibility) (173 robustness) def:CNY67_04820 (0 target-flexibility) (0 robustness) def:CNY67_04975 (357 target-flexibility) (115 robustness) def:CNY67_05000 (686 target-flexibility) (192 robustness) def:CNY67_05120 (706 target-flexibility) (173 robustness) def:CNY67_05135 (706 target-flexibility) (173 robustness) def:CNY67_05215 (706 target-flexibility) (173 robustness) def:CNY67_05745 (0 target-flexibility) (0 robustness) def:CNY67_07200 (357 target-flexibility) (115 robustness) def:CNY67_07855 (138 target-flexibility) (138 robustness) def:CNY67_08360 (0 target-flexibility) (0 robustness) def:CNY67_08465 (405 target-flexibility) (70 robustness) def:CNY67_09265 (323 target-flexibility) (101 robustness) def:CNY67_09320 (902 target-flexibility) (228 robustness) def:CNY67_09770 (0 target-flexibility) (0 robustness) def:CNY67_10085 (0 target-flexibility) (0 robustness) def:CNY67_11360 (686 target-flexibility) (192 robustness) def:CNY67_11490 (0 target-flexibility) (0 robustness) def:CNY67_11835 (434 target-flexibility) (67 robustness) def:CNY67_12480 (0 target-flexibility) (0 robustness) def:CNY67_12850 (222 target-flexibility) (83 robustness) def:CNY67_13650 (405 target-flexibility) (70 robustness) def:CNY67_14075 (357 target-flexibility) (102 robustness) def:CNY67_14455 (1385 target-flexibility) (204 robustness) def:CNY67_15275 (0 target-flexibility) (0 robustness) def:CNY67_15330 (323 target-flexibility) (101 robustness) dej:AWY79_00420 (358 target-flexibility) (104 robustness) dej:AWY79_00595 (790 target-flexibility) (134 robustness) dej:AWY79_00730 (1385 target-flexibility) (204 robustness) dej:AWY79_00980 (790 target-flexibility) (134 robustness) dej:AWY79_01195 (790 target-flexibility) (134 robustness) dej:AWY79_01845 (0 target-flexibility) (0 robustness) dej:AWY79_01925 (0 target-flexibility) (0 robustness) dej:AWY79_02360 (357 target-flexibility) (115 robustness) dej:AWY79_02820 (0 target-flexibility) (0 robustness) dej:AWY79_03150 (902 target-flexibility) (228 robustness) dej:AWY79_03505 (0 target-flexibility) (0 robustness) dej:AWY79_03845 (0 target-flexibility) (0 robustness) dej:AWY79_03870 (752 target-flexibility) (76 robustness) dej:AWY79_04190 (0 target-flexibility) (0 robustness) dej:AWY79_04800 (212 target-flexibility) (73 robustness) dej:AWY79_04910 (780 target-flexibility) (243 robustness) dej:AWY79_05115 (0 target-flexibility) (0 robustness) dej:AWY79_05375 (1385 target-flexibility) (204 robustness) dej:AWY79_05490 (0 target-flexibility) (0 robustness) dej:AWY79_05515 (0 target-flexibility) (0 robustness) dej:AWY79_05625 (0 target-flexibility) (0 robustness) dej:AWY79_06240 (138 target-flexibility) (138 robustness) dej:AWY79_06655 (0 target-flexibility) (0 robustness) dej:AWY79_07380 (706 target-flexibility) (173 robustness) dej:AWY79_07505 (706 target-flexibility) (173 robustness) dej:AWY79_07980 (0 target-flexibility) (0 robustness) dej:AWY79_07985 (64 target-flexibility) (64 robustness) dej:AWY79_08145 (147 target-flexibility) (76 robustness) dej:AWY79_08325 (0 target-flexibility) (0 robustness) dej:AWY79_08405 (0 target-flexibility) (0 robustness) dej:AWY79_08700 (0 target-flexibility) (0 robustness) dej:AWY79_09165 (0 target-flexibility) (0 robustness) dej:AWY79_09610 (0 target-flexibility) (0 robustness) dej:AWY79_09690 (0 target-flexibility) (0 robustness) dej:AWY79_09715 (0 target-flexibility) (0 robustness) dej:AWY79_09945 (0 target-flexibility) (0 robustness) dej:AWY79_10175 (301 target-flexibility) (154 robustness) dej:AWY79_10180 (301 target-flexibility) (154 robustness) dej:AWY79_10340 (0 target-flexibility) (0 robustness) dej:AWY79_10345 (0 target-flexibility) (0 robustness) dej:AWY79_10770 (841 target-flexibility) (126 robustness) dej:AWY79_10785 (434 target-flexibility) (67 robustness) dej:AWY79_10850 (0 target-flexibility) (0 robustness) dej:AWY79_10975 (138 target-flexibility) (138 robustness) dej:AWY79_11045 (64 target-flexibility) (64 robustness) dej:AWY79_11135 (0 target-flexibility) (0 robustness) dej:AWY79_11140 (0 target-flexibility) (0 robustness) dej:AWY79_11170 (0 target-flexibility) (0 robustness) dej:AWY79_11185 (0 target-flexibility) (0 robustness) dej:AWY79_11535 (711 target-flexibility) (104 robustness) dej:AWY79_11830 (0 target-flexibility) (0 robustness) dej:AWY79_12270 (706 target-flexibility) (173 robustness) dej:AWY79_12390 (902 target-flexibility) (228 robustness) dej:AWY79_12435 (528 target-flexibility) (157 robustness) dej:AWY79_12450 (222 target-flexibility) (83 robustness) dej:AWY79_12645 (841 target-flexibility) (126 robustness) dej:AWY79_12835 (359 target-flexibility) (65 robustness) dej:AWY79_12840 (902 target-flexibility) (228 robustness) dej:AWY79_12845 (902 target-flexibility) (228 robustness) dej:AWY79_13090 (138 target-flexibility) (138 robustness) dej:AWY79_13255 (206 target-flexibility) (68 robustness) dej:AWY79_13735 (711 target-flexibility) (104 robustness) dej:AWY79_13845 (0 target-flexibility) (0 robustness) dej:AWY79_13920 (357 target-flexibility) (115 robustness) dej:AWY79_13965 (0 target-flexibility) (0 robustness) dej:AWY79_15280 (358 target-flexibility) (104 robustness) dej:AWY79_15440 (686 target-flexibility) (192 robustness) dej:AWY79_15450 (289 target-flexibility) (73 robustness) dej:AWY79_15735 (686 target-flexibility) (192 robustness) dej:AWY79_15760 (0 target-flexibility) (0 robustness) dej:AWY79_16080 (780 target-flexibility) (243 robustness) dej:AWY79_16725 (706 target-flexibility) (173 robustness) dej:AWY79_17490 (359 target-flexibility) (65 robustness) dej:AWY79_17500 (147 target-flexibility) (76 robustness) dej:AWY79_17535 (301 target-flexibility) (154 robustness) dej:AWY79_17540 (301 target-flexibility) (154 robustness) dej:AWY79_17820 (0 target-flexibility) (0 robustness) des:DSOUD_0047 (796 target-flexibility) (85 robustness) des:DSOUD_0107 (0 target-flexibility) (0 robustness) des:DSOUD_0161 (138 target-flexibility) (138 robustness) des:DSOUD_0206 (1108 target-flexibility) (319 robustness) des:DSOUD_0247 (80 target-flexibility) (80 robustness) des:DSOUD_0294 (691 target-flexibility) (528 robustness) des:DSOUD_0318 (0 target-flexibility) (0 robustness) des:DSOUD_0343 (1041 target-flexibility) (243 robustness) des:DSOUD_0363 (0 target-flexibility) (0 robustness) des:DSOUD_0378 (503 target-flexibility) (78 robustness) des:DSOUD_0407 (0 target-flexibility) (0 robustness) des:DSOUD_0484 (222 target-flexibility) (83 robustness) des:DSOUD_0593 (0 target-flexibility) (0 robustness) des:DSOUD_0612 (0 target-flexibility) (0 robustness) des:DSOUD_0618 (91 target-flexibility) (91 robustness) des:DSOUD_0656 (1041 target-flexibility) (243 robustness) des:DSOUD_0657 (1041 target-flexibility) (243 robustness) des:DSOUD_0751 (262 target-flexibility) (86 robustness) des:DSOUD_0765 (528 target-flexibility) (157 robustness) des:DSOUD_0923 (138 target-flexibility) (66 robustness) des:DSOUD_0953 (0 target-flexibility) (0 robustness) des:DSOUD_1069 (0 target-flexibility) (0 robustness) des:DSOUD_1127 (212 target-flexibility) (73 robustness) des:DSOUD_1171 (634 target-flexibility) (72 robustness) des:DSOUD_1214 (659 target-flexibility) (240 robustness) des:DSOUD_1217 (703 target-flexibility) (319 robustness) des:DSOUD_1220 (0 target-flexibility) (0 robustness) des:DSOUD_1228 (703 target-flexibility) (319 robustness) des:DSOUD_1236 (703 target-flexibility) (319 robustness) des:DSOUD_1340 (902 target-flexibility) (228 robustness) des:DSOUD_1345 (841 target-flexibility) (126 robustness) des:DSOUD_1475 (752 target-flexibility) (76 robustness) des:DSOUD_1660 (71 target-flexibility) (71 robustness) des:DSOUD_1686 (0 target-flexibility) (0 robustness) des:DSOUD_1728 (706 target-flexibility) (173 robustness) des:DSOUD_1777 (600 target-flexibility) (126 robustness) des:DSOUD_1782 (732 target-flexibility) (78 robustness) des:DSOUD_1879 (897 target-flexibility) (71 robustness) des:DSOUD_1892 (0 target-flexibility) (0 robustness) des:DSOUD_1894 (0 target-flexibility) (0 robustness) des:DSOUD_1909 (0 target-flexibility) (0 robustness) des:DSOUD_1920 (0 target-flexibility) (0 robustness) des:DSOUD_1940 (691 target-flexibility) (528 robustness) des:DSOUD_2009 (0 target-flexibility) (0 robustness) des:DSOUD_2030 (703 target-flexibility) (319 robustness) des:DSOUD_2032 (659 target-flexibility) (240 robustness) des:DSOUD_2033 (503 target-flexibility) (78 robustness) des:DSOUD_2034 (1108 target-flexibility) (319 robustness) des:DSOUD_2209 (358 target-flexibility) (124 robustness) des:DSOUD_2288 (0 target-flexibility) (0 robustness) des:DSOUD_2394 (1169 target-flexibility) (76 robustness) des:DSOUD_2450 (1108 target-flexibility) (319 robustness) des:DSOUD_2497 (902 target-flexibility) (228 robustness) des:DSOUD_2544 (0 target-flexibility) (0 robustness) des:DSOUD_2695 (231 target-flexibility) (158 robustness) des:DSOUD_2696 (231 target-flexibility) (158 robustness) des:DSOUD_2757 (262 target-flexibility) (86 robustness) des:DSOUD_2788 (841 target-flexibility) (126 robustness) des:DSOUD_2815 (686 target-flexibility) (192 robustness) des:DSOUD_2817 (686 target-flexibility) (192 robustness) des:DSOUD_2819 (634 target-flexibility) (72 robustness) des:DSOUD_2921 (231 target-flexibility) (158 robustness) des:DSOUD_2923 (70 target-flexibility) (70 robustness) des:DSOUD_2928 (67 target-flexibility) (67 robustness) des:DSOUD_2929 (239 target-flexibility) (67 robustness) des:DSOUD_2969 (91 target-flexibility) (91 robustness) des:DSOUD_2977 (600 target-flexibility) (126 robustness) des:DSOUD_3002 (0 target-flexibility) (0 robustness) des:DSOUD_3139 (138 target-flexibility) (138 robustness) des:DSOUD_3191 (0 target-flexibility) (0 robustness) des:DSOUD_3192 (0 target-flexibility) (0 robustness) des:DSOUD_3213 (528 target-flexibility) (157 robustness) des:DSOUD_3271 (358 target-flexibility) (124 robustness) des:DSOUD_3296 (706 target-flexibility) (173 robustness) des:DSOUD_3352 (0 target-flexibility) (0 robustness) des:DSOUD_3461 (0 target-flexibility) (0 robustness) deu:DBW_0034 (0 target-flexibility) (0 robustness) deu:DBW_0039 (0 target-flexibility) (0 robustness) deu:DBW_0130 (528 target-flexibility) (157 robustness) deu:DBW_0142 (600 target-flexibility) (126 robustness) deu:DBW_0156 (358 target-flexibility) (124 robustness) deu:DBW_0158 (0 target-flexibility) (0 robustness) deu:DBW_0252 (528 target-flexibility) (157 robustness) deu:DBW_0376 (138 target-flexibility) (138 robustness) deu:DBW_0404 (528 target-flexibility) (157 robustness) deu:DBW_0440 (80 target-flexibility) (80 robustness) deu:DBW_0441 (0 target-flexibility) (0 robustness) deu:DBW_0541 (691 target-flexibility) (528 robustness) deu:DBW_0616 (796 target-flexibility) (85 robustness) deu:DBW_0759 (222 target-flexibility) (83 robustness) deu:DBW_0805 (269 target-flexibility) (64 robustness) deu:DBW_0807 (902 target-flexibility) (228 robustness) deu:DBW_0911 (138 target-flexibility) (66 robustness) deu:DBW_0936 (0 target-flexibility) (0 robustness) deu:DBW_1201 (686 target-flexibility) (192 robustness) deu:DBW_1203 (686 target-flexibility) (192 robustness) deu:DBW_1238 (841 target-flexibility) (126 robustness) deu:DBW_1501 (0 target-flexibility) (0 robustness) deu:DBW_1630 (691 target-flexibility) (528 robustness) deu:DBW_1650 (0 target-flexibility) (0 robustness) deu:DBW_1740 (600 target-flexibility) (126 robustness) deu:DBW_1746 (732 target-flexibility) (78 robustness) deu:DBW_1757 (659 target-flexibility) (240 robustness) deu:DBW_1760 (703 target-flexibility) (319 robustness) deu:DBW_1763 (0 target-flexibility) (0 robustness) deu:DBW_1771 (703 target-flexibility) (319 robustness) deu:DBW_1818 (1108 target-flexibility) (319 robustness) deu:DBW_1820 (659 target-flexibility) (240 robustness) deu:DBW_1822 (703 target-flexibility) (319 robustness) deu:DBW_1838 (0 target-flexibility) (0 robustness) deu:DBW_1916 (0 target-flexibility) (0 robustness) deu:DBW_1931 (0 target-flexibility) (0 robustness) deu:DBW_1933 (0 target-flexibility) (0 robustness) deu:DBW_1942 (897 target-flexibility) (71 robustness) deu:DBW_2119 (358 target-flexibility) (124 robustness) deu:DBW_2132 (0 target-flexibility) (0 robustness) deu:DBW_2134 (0 target-flexibility) (0 robustness) deu:DBW_2192 (841 target-flexibility) (126 robustness) deu:DBW_2197 (902 target-flexibility) (228 robustness) deu:DBW_2198 (269 target-flexibility) (64 robustness) deu:DBW_2313 (0 target-flexibility) (0 robustness) deu:DBW_2383 (231 target-flexibility) (158 robustness) deu:DBW_2384 (231 target-flexibility) (158 robustness) deu:DBW_2425 (1169 target-flexibility) (76 robustness) deu:DBW_2529 (350 target-flexibility) (84 robustness) deu:DBW_2530 (350 target-flexibility) (84 robustness) deu:DBW_2541 (1041 target-flexibility) (243 robustness) deu:DBW_2639 (212 target-flexibility) (73 robustness) deu:DBW_2731 (1108 target-flexibility) (319 robustness) deu:DBW_2798 (231 target-flexibility) (158 robustness) deu:DBW_2799 (70 target-flexibility) (70 robustness) deu:DBW_2804 (67 target-flexibility) (67 robustness) deu:DBW_2805 (239 target-flexibility) (67 robustness) deu:DBW_2862 (91 target-flexibility) (91 robustness) deu:DBW_2871 (600 target-flexibility) (126 robustness) deu:DBW_3054 (1041 target-flexibility) (243 robustness) deu:DBW_3055 (1041 target-flexibility) (243 robustness) deu:DBW_3057 (350 target-flexibility) (84 robustness) deu:DBW_3101 (91 target-flexibility) (91 robustness) deu:DBW_3160 (262 target-flexibility) (86 robustness) deu:DBW_3162 (262 target-flexibility) (86 robustness) deu:DBW_3241 (138 target-flexibility) (138 robustness) deu:DBW_3264 (0 target-flexibility) (0 robustness) deu:DBW_3265 (0 target-flexibility) (0 robustness) deu:DBW_3285 (528 target-flexibility) (157 robustness) deu:DBW_3379 (0 target-flexibility) (0 robustness) deu:DBW_3516 (0 target-flexibility) (0 robustness) dfi:AXF13_00145 (212 target-flexibility) (73 robustness) dfi:AXF13_00200 (821 target-flexibility) (137 robustness) dfi:AXF13_00460 (434 target-flexibility) (67 robustness) dfi:AXF13_00525 (80 target-flexibility) (80 robustness) dfi:AXF13_00990 (222 target-flexibility) (83 robustness) dfi:AXF13_01640 (902 target-flexibility) (228 robustness) dfi:AXF13_01860 (357 target-flexibility) (102 robustness) dfi:AXF13_02225 (0 target-flexibility) (0 robustness) dfi:AXF13_02495 (0 target-flexibility) (0 robustness) dfi:AXF13_02595 (706 target-flexibility) (173 robustness) dfi:AXF13_02705 (0 target-flexibility) (0 robustness) dfi:AXF13_02840 (703 target-flexibility) (319 robustness) dfi:AXF13_03820 (0 target-flexibility) (0 robustness) dfi:AXF13_03855 (703 target-flexibility) (319 robustness) dfi:AXF13_03870 (1108 target-flexibility) (319 robustness) dfi:AXF13_04200 (357 target-flexibility) (115 robustness) dfi:AXF13_05010 (357 target-flexibility) (115 robustness) dfi:AXF13_05040 (686 target-flexibility) (192 robustness) dfi:AXF13_05160 (706 target-flexibility) (173 robustness) dfi:AXF13_05175 (706 target-flexibility) (173 robustness) dfi:AXF13_05725 (0 target-flexibility) (0 robustness) dfi:AXF13_05800 (1169 target-flexibility) (76 robustness) dfi:AXF13_05975 (0 target-flexibility) (0 robustness) dfi:AXF13_06295 (138 target-flexibility) (138 robustness) dfi:AXF13_06500 (706 target-flexibility) (173 robustness) dfi:AXF13_07230 (0 target-flexibility) (0 robustness) dfi:AXF13_09410 (821 target-flexibility) (137 robustness) dfi:AXF13_10380 (790 target-flexibility) (134 robustness) dfi:AXF13_10670 (686 target-flexibility) (192 robustness) dfi:AXF13_10905 (1041 target-flexibility) (243 robustness) dfi:AXF13_11195 (0 target-flexibility) (0 robustness) dfi:AXF13_11540 (468 target-flexibility) (75 robustness) dfi:AXF13_11695 (0 target-flexibility) (0 robustness) dfi:AXF13_12410 (357 target-flexibility) (102 robustness) dfi:AXF13_12555 (0 target-flexibility) (0 robustness) dfi:AXF13_12630 (1385 target-flexibility) (204 robustness) dfi:AXF13_12725 (138 target-flexibility) (138 robustness) dfi:AXF13_12855 (902 target-flexibility) (228 robustness) dfi:AXF13_13155 (289 target-flexibility) (73 robustness) dfi:AXF13_13325 (0 target-flexibility) (0 robustness) dfi:AXF13_13335 (1385 target-flexibility) (204 robustness) dfi:AXF13_13565 (301 target-flexibility) (154 robustness) dfi:AXF13_13900 (1108 target-flexibility) (319 robustness) dfi:AXF13_13965 (1041 target-flexibility) (243 robustness) dfi:AXF13_13970 (1041 target-flexibility) (243 robustness) dfi:AXF13_14405 (600 target-flexibility) (126 robustness) dfi:AXF13_14950 (600 target-flexibility) (126 robustness) dfi:AXF13_15030 (468 target-flexibility) (75 robustness) dfi:AXF13_15125 (301 target-flexibility) (154 robustness) dfi:AXF13_15545 (468 target-flexibility) (75 robustness) dgg:DGI_0026 (0 target-flexibility) (0 robustness) dgg:DGI_0069 (0 target-flexibility) (0 robustness) dgg:DGI_0194 (0 target-flexibility) (0 robustness) dgg:DGI_0259 (821 target-flexibility) (137 robustness) dgg:DGI_0581 (790 target-flexibility) (134 robustness) dgg:DGI_0644 (0 target-flexibility) (0 robustness) dgg:DGI_0677 (0 target-flexibility) (0 robustness) dgg:DGI_0738 (528 target-flexibility) (157 robustness) dgg:DGI_0864 (0 target-flexibility) (0 robustness) dgg:DGI_0873 (241 target-flexibility) (71 robustness) dgg:DGI_0878 (1385 target-flexibility) (204 robustness) dgg:DGI_0974 (138 target-flexibility) (138 robustness) dgg:DGI_1044 (0 target-flexibility) (0 robustness) dgg:DGI_1047 (0 target-flexibility) (0 robustness) dgg:DGI_1150 (357 target-flexibility) (115 robustness) dgg:DGI_1257 (357 target-flexibility) (115 robustness) dgg:DGI_1348 (1041 target-flexibility) (243 robustness) dgg:DGI_1422 (0 target-flexibility) (0 robustness) dgg:DGI_1438 (790 target-flexibility) (134 robustness) dgg:DGI_1581 (241 target-flexibility) (71 robustness) dgg:DGI_1613 (821 target-flexibility) (137 robustness) dgg:DGI_1648 (212 target-flexibility) (73 robustness) dgg:DGI_1654 (1385 target-flexibility) (204 robustness) dgg:DGI_1737 (790 target-flexibility) (134 robustness) dgg:DGI_1796 (879 target-flexibility) (71 robustness) dgg:DGI_1805 (700 target-flexibility) (77 robustness) dgg:DGI_1807 (350 target-flexibility) (189 robustness) dgg:DGI_1837 (357 target-flexibility) (102 robustness) dgg:DGI_1851 (289 target-flexibility) (73 robustness) dgg:DGI_1877 (350 target-flexibility) (189 robustness) dgg:DGI_1879 (700 target-flexibility) (77 robustness) dgg:DGI_1888 (879 target-flexibility) (71 robustness) dgg:DGI_1902 (0 target-flexibility) (0 robustness) dgg:DGI_2188 (600 target-flexibility) (126 robustness) dgg:DGI_2242 (0 target-flexibility) (0 robustness) dgg:DGI_2250 (706 target-flexibility) (173 robustness) dgg:DGI_2289 (0 target-flexibility) (0 robustness) dgg:DGI_2466 (0 target-flexibility) (0 robustness) dgg:DGI_2476 (0 target-flexibility) (0 robustness) dgg:DGI_2503 (841 target-flexibility) (126 robustness) dgg:DGI_2521 (138 target-flexibility) (138 robustness) dgg:DGI_2546 (600 target-flexibility) (126 robustness) dgg:DGI_2559 (0 target-flexibility) (0 robustness) dgg:DGI_2657 (0 target-flexibility) (0 robustness) dgg:DGI_2681 (358 target-flexibility) (104 robustness) dgg:DGI_2716 (0 target-flexibility) (0 robustness) dgg:DGI_2774 (222 target-flexibility) (83 robustness) dgg:DGI_2781 (138 target-flexibility) (138 robustness) dgg:DGI_2795 (1169 target-flexibility) (76 robustness) dgg:DGI_2876 (0 target-flexibility) (0 robustness) dgg:DGI_2938 (706 target-flexibility) (173 robustness) dgg:DGI_2942 (706 target-flexibility) (173 robustness) dgg:DGI_3014 (0 target-flexibility) (0 robustness) dgg:DGI_3030 (0 target-flexibility) (0 robustness) dgg:DGI_3042 (706 target-flexibility) (173 robustness) dgg:DGI_3046 (706 target-flexibility) (173 robustness) dgg:DGI_3110 (0 target-flexibility) (0 robustness) dgg:DGI_3140 (0 target-flexibility) (0 robustness) dgg:DGI_3260 (434 target-flexibility) (67 robustness) dgg:DGI_3263 (841 target-flexibility) (126 robustness) dgg:DGI_3398 (358 target-flexibility) (104 robustness) dgg:DGI_3482 (902 target-flexibility) (228 robustness) dgg:DGI_3493 (0 target-flexibility) (0 robustness) dgg:DGI_3507 (902 target-flexibility) (228 robustness) dgg:DGI_3520 (357 target-flexibility) (102 robustness) dgg:DGI_4014 (0 target-flexibility) (0 robustness) dgg:DGI_4019 (821 target-flexibility) (137 robustness) dhy:DESAM_10054 (71 target-flexibility) (71 robustness) dhy:DESAM_10059 (62 target-flexibility) (62 robustness) dhy:DESAM_10157 (358 target-flexibility) (104 robustness) dhy:DESAM_10178 (711 target-flexibility) (104 robustness) dhy:DESAM_10265 (0 target-flexibility) (0 robustness) dhy:DESAM_20002 (239 target-flexibility) (99 robustness) dhy:DESAM_20071 (0 target-flexibility) (0 robustness) dhy:DESAM_20072 (0 target-flexibility) (0 robustness) dhy:DESAM_20147 (80 target-flexibility) (80 robustness) dhy:DESAM_20155 (0 target-flexibility) (0 robustness) dhy:DESAM_20160 (1169 target-flexibility) (76 robustness) dhy:DESAM_20241 (1108 target-flexibility) (319 robustness) dhy:DESAM_20242 (659 target-flexibility) (240 robustness) dhy:DESAM_20244 (703 target-flexibility) (319 robustness) dhy:DESAM_20245 (1066 target-flexibility) (75 robustness) dhy:DESAM_20254 (0 target-flexibility) (0 robustness) dhy:DESAM_20295 (821 target-flexibility) (137 robustness) dhy:DESAM_20338 (796 target-flexibility) (85 robustness) dhy:DESAM_20373 (358 target-flexibility) (104 robustness) dhy:DESAM_20409 (0 target-flexibility) (0 robustness) dhy:DESAM_20444 (0 target-flexibility) (0 robustness) dhy:DESAM_20447 (0 target-flexibility) (0 robustness) dhy:DESAM_20480 (212 target-flexibility) (73 robustness) dhy:DESAM_20492 (0 target-flexibility) (0 robustness) dhy:DESAM_20564 (790 target-flexibility) (134 robustness) dhy:DESAM_20574 (752 target-flexibility) (76 robustness) dhy:DESAM_20586 (528 target-flexibility) (157 robustness) dhy:DESAM_20633 (790 target-flexibility) (134 robustness) dhy:DESAM_20683 (0 target-flexibility) (0 robustness) dhy:DESAM_20696 (821 target-flexibility) (137 robustness) dhy:DESAM_20710 (897 target-flexibility) (71 robustness) dhy:DESAM_20726 (0 target-flexibility) (0 robustness) dhy:DESAM_20796 (1385 target-flexibility) (204 robustness) dhy:DESAM_20814 (600 target-flexibility) (126 robustness) dhy:DESAM_20816 (138 target-flexibility) (138 robustness) dhy:DESAM_20863 (790 target-flexibility) (134 robustness) dhy:DESAM_20884 (1041 target-flexibility) (243 robustness) dhy:DESAM_20902 (1108 target-flexibility) (319 robustness) dhy:DESAM_20916 (0 target-flexibility) (0 robustness) dhy:DESAM_20933 (0 target-flexibility) (0 robustness) dhy:DESAM_20948 (62 target-flexibility) (62 robustness) dhy:DESAM_20949 (0 target-flexibility) (0 robustness) dhy:DESAM_20962 (821 target-flexibility) (137 robustness) dhy:DESAM_20985 (414 target-flexibility) (96 robustness) dhy:DESAM_21103 (1385 target-flexibility) (204 robustness) dhy:DESAM_21153 (703 target-flexibility) (319 robustness) dhy:DESAM_21156 (659 target-flexibility) (240 robustness) dhy:DESAM_21172 (1041 target-flexibility) (243 robustness) dhy:DESAM_21173 (1041 target-flexibility) (243 robustness) dhy:DESAM_21286 (0 target-flexibility) (0 robustness) dhy:DESAM_21414 (686 target-flexibility) (192 robustness) dhy:DESAM_21448 (706 target-flexibility) (173 robustness) dhy:DESAM_21558 (686 target-flexibility) (192 robustness) dhy:DESAM_21598 (0 target-flexibility) (0 robustness) dhy:DESAM_21612 (790 target-flexibility) (134 robustness) dhy:DESAM_21666 (0 target-flexibility) (0 robustness) dhy:DESAM_21680 (289 target-flexibility) (73 robustness) dhy:DESAM_21809 (206 target-flexibility) (68 robustness) dhy:DESAM_21837 (0 target-flexibility) (0 robustness) dhy:DESAM_21850 (706 target-flexibility) (173 robustness) dhy:DESAM_21922 (841 target-flexibility) (126 robustness) dhy:DESAM_21926 (434 target-flexibility) (67 robustness) dhy:DESAM_22043 (0 target-flexibility) (0 robustness) dhy:DESAM_22057 (0 target-flexibility) (0 robustness) dhy:DESAM_22128 (138 target-flexibility) (138 robustness) dhy:DESAM_22139 (0 target-flexibility) (0 robustness) dhy:DESAM_22144 (0 target-flexibility) (0 robustness) dhy:DESAM_22147 (659 target-flexibility) (240 robustness) dhy:DESAM_22210 (706 target-flexibility) (173 robustness) dhy:DESAM_22216 (0 target-flexibility) (0 robustness) dhy:DESAM_22222 (0 target-flexibility) (0 robustness) dhy:DESAM_22252 (222 target-flexibility) (83 robustness) dhy:DESAM_22258 (841 target-flexibility) (126 robustness) dhy:DESAM_22296 (239 target-flexibility) (99 robustness) dhy:DESAM_22317 (330 target-flexibility) (76 robustness) dhy:DESAM_22335 (0 target-flexibility) (0 robustness) dhy:DESAM_22360 (600 target-flexibility) (126 robustness) dhy:DESAM_22412 (138 target-flexibility) (66 robustness) dhy:DESAM_22427 (902 target-flexibility) (228 robustness) dhy:DESAM_22453 (138 target-flexibility) (138 robustness) dhy:DESAM_22470 (732 target-flexibility) (78 robustness) dhy:DESAM_22526 (711 target-flexibility) (104 robustness) dhy:DESAM_22537 (902 target-flexibility) (228 robustness) dhy:DESAM_22538 (902 target-flexibility) (228 robustness) dhy:DESAM_22632 (0 target-flexibility) (0 robustness) dhy:DESAM_22644 (1066 target-flexibility) (75 robustness) dhy:DESAM_22667 (0 target-flexibility) (0 robustness) dhy:DESAM_22801 (902 target-flexibility) (228 robustness) dhy:DESAM_22936 (390 target-flexibility) (74 robustness) dhy:DESAM_22951 (414 target-flexibility) (96 robustness) dhy:DESAM_22954 (600 target-flexibility) (126 robustness) dhy:DESAM_22955 (390 target-flexibility) (74 robustness) dhy:DESAM_22957 (330 target-flexibility) (76 robustness) dhy:DESAM_22958 (1041 target-flexibility) (243 robustness) dhy:DESAM_23096 (0 target-flexibility) (0 robustness) dma:DMR_00110 (0 target-flexibility) (0 robustness) dma:DMR_00430 (0 target-flexibility) (0 robustness) dma:DMR_00560 (821 target-flexibility) (137 robustness) dma:DMR_01800 (0 target-flexibility) (0 robustness) dma:DMR_01890 (0 target-flexibility) (0 robustness) dma:DMR_02050 (212 target-flexibility) (73 robustness) dma:DMR_02170 (76 target-flexibility) (76 robustness) dma:DMR_02380 (0 target-flexibility) (0 robustness) dma:DMR_04400 (0 target-flexibility) (0 robustness) dma:DMR_04560 (0 target-flexibility) (0 robustness) dma:DMR_05110 (0 target-flexibility) (0 robustness) dma:DMR_05260 (686 target-flexibility) (192 robustness) dma:DMR_05730 (301 target-flexibility) (154 robustness) dma:DMR_05740 (301 target-flexibility) (154 robustness) dma:DMR_06660 (790 target-flexibility) (134 robustness) dma:DMR_07470 (0 target-flexibility) (0 robustness) dma:DMR_09030 (0 target-flexibility) (0 robustness) dma:DMR_10970 (0 target-flexibility) (0 robustness) dma:DMR_11010 (0 target-flexibility) (0 robustness) dma:DMR_11340 (0 target-flexibility) (0 robustness) dma:DMR_13630 (138 target-flexibility) (138 robustness) dma:DMR_14920 (1066 target-flexibility) (75 robustness) dma:DMR_15980 (841 target-flexibility) (126 robustness) dma:DMR_16010 (434 target-flexibility) (67 robustness) dma:DMR_16700 (0 target-flexibility) (0 robustness) dma:DMR_16990 (0 target-flexibility) (0 robustness) dma:DMR_17120 (528 target-flexibility) (157 robustness) dma:DMR_17130 (701 target-flexibility) (106 robustness) dma:DMR_17770 (790 target-flexibility) (134 robustness) dma:DMR_17800 (138 target-flexibility) (138 robustness) dma:DMR_17880 (841 target-flexibility) (126 robustness) dma:DMR_18200 (334 target-flexibility) (71 robustness) dma:DMR_19210 (600 target-flexibility) (126 robustness) dma:DMR_19340 (0 target-flexibility) (0 robustness) dma:DMR_19490 (686 target-flexibility) (192 robustness) dma:DMR_19670 (790 target-flexibility) (134 robustness) dma:DMR_20060 (0 target-flexibility) (0 robustness) dma:DMR_21220 (239 target-flexibility) (99 robustness) dma:DMR_21290 (239 target-flexibility) (99 robustness) dma:DMR_21660 (138 target-flexibility) (138 robustness) dma:DMR_21830 (902 target-flexibility) (228 robustness) dma:DMR_22170 (222 target-flexibility) (83 robustness) dma:DMR_22790 (659 target-flexibility) (240 robustness) dma:DMR_23160 (358 target-flexibility) (104 robustness) dma:DMR_25440 (0 target-flexibility) (0 robustness) dma:DMR_27000 (0 target-flexibility) (0 robustness) dma:DMR_28090 (706 target-flexibility) (173 robustness) dma:DMR_28220 (289 target-flexibility) (73 robustness) dma:DMR_28600 (0 target-flexibility) (0 robustness) dma:DMR_28790 (600 target-flexibility) (126 robustness) dma:DMR_30710 (358 target-flexibility) (104 robustness) dma:DMR_33250 (76 target-flexibility) (76 robustness) dma:DMR_34180 (902 target-flexibility) (228 robustness) dma:DMR_34300 (301 target-flexibility) (154 robustness) dma:DMR_34310 (301 target-flexibility) (154 robustness) dma:DMR_34740 (1385 target-flexibility) (204 robustness) dma:DMR_35020 (706 target-flexibility) (173 robustness) dma:DMR_37080 (701 target-flexibility) (106 robustness) dma:DMR_37110 (334 target-flexibility) (71 robustness) dma:DMR_37140 (528 target-flexibility) (157 robustness) dma:DMR_37150 (0 target-flexibility) (0 robustness) dma:DMR_37260 (706 target-flexibility) (173 robustness) dma:DMR_38720 (706 target-flexibility) (173 robustness) dma:DMR_39240 (0 target-flexibility) (0 robustness) dma:DMR_39860 (357 target-flexibility) (102 robustness) dma:DMR_39960 (659 target-flexibility) (240 robustness) dma:DMR_39990 (1066 target-flexibility) (75 robustness) dma:DMR_42440 (706 target-flexibility) (173 robustness) dma:DMR_42760 (821 target-flexibility) (137 robustness) dma:DMR_44510 (405 target-flexibility) (70 robustness) dma:DMR_45660 (0 target-flexibility) (0 robustness) dma:DMR_45930 (1385 target-flexibility) (204 robustness) dml:Dmul_00120 (600 target-flexibility) (126 robustness) dml:Dmul_00400 (0 target-flexibility) (0 robustness) dml:Dmul_00440 (855 target-flexibility) (138 robustness) dml:Dmul_00590 (558 target-flexibility) (68 robustness) dml:Dmul_01560 (0 target-flexibility) (0 robustness) dml:Dmul_01640 (0 target-flexibility) (0 robustness) dml:Dmul_01800 (0 target-flexibility) (0 robustness) dml:Dmul_03450 (64 target-flexibility) (64 robustness) dml:Dmul_03970 (91 target-flexibility) (91 robustness) dml:Dmul_05580 (405 target-flexibility) (169 robustness) dml:Dmul_05590 (732 target-flexibility) (78 robustness) dml:Dmul_06060 (138 target-flexibility) (138 robustness) dml:Dmul_07460 (0 target-flexibility) (0 robustness) dml:Dmul_07490 (0 target-flexibility) (0 robustness) dml:Dmul_07680 (752 target-flexibility) (105 robustness) dml:Dmul_07750 (138 target-flexibility) (138 robustness) dml:Dmul_08540 (0 target-flexibility) (0 robustness) dml:Dmul_08800 (657 target-flexibility) (95 robustness) dml:Dmul_08960 (289 target-flexibility) (73 robustness) dml:Dmul_09400 (752 target-flexibility) (105 robustness) dml:Dmul_09580 (0 target-flexibility) (0 robustness) dml:Dmul_10150 (752 target-flexibility) (76 robustness) dml:Dmul_11080 (0 target-flexibility) (0 robustness) dml:Dmul_11190 (855 target-flexibility) (138 robustness) dml:Dmul_12180 (1108 target-flexibility) (319 robustness) dml:Dmul_14330 (358 target-flexibility) (104 robustness) dml:Dmul_14360 (1183 target-flexibility) (114 robustness) dml:Dmul_14400 (691 target-flexibility) (528 robustness) dml:Dmul_15200 (732 target-flexibility) (78 robustness) dml:Dmul_15210 (405 target-flexibility) (169 robustness) dml:Dmul_15350 (138 target-flexibility) (138 robustness) dml:Dmul_15430 (686 target-flexibility) (192 robustness) dml:Dmul_15560 (558 target-flexibility) (68 robustness) dml:Dmul_15600 (691 target-flexibility) (528 robustness) dml:Dmul_16000 (0 target-flexibility) (0 robustness) dml:Dmul_16500 (634 target-flexibility) (72 robustness) dml:Dmul_16810 (0 target-flexibility) (0 robustness) dml:Dmul_18930 (71 target-flexibility) (71 robustness) dml:Dmul_19320 (790 target-flexibility) (134 robustness) dml:Dmul_19830 (1385 target-flexibility) (204 robustness) dml:Dmul_20530 (377 target-flexibility) (117 robustness) dml:Dmul_20590 (222 target-flexibility) (83 robustness) dml:Dmul_20930 (323 target-flexibility) (101 robustness) dml:Dmul_21160 (634 target-flexibility) (72 robustness) dml:Dmul_21170 (215 target-flexibility) (142 robustness) dml:Dmul_21250 (0 target-flexibility) (0 robustness) dml:Dmul_21290 (0 target-flexibility) (0 robustness) dml:Dmul_21510 (659 target-flexibility) (240 robustness) dml:Dmul_21830 (790 target-flexibility) (134 robustness) dml:Dmul_22280 (0 target-flexibility) (0 robustness) dml:Dmul_22400 (358 target-flexibility) (104 robustness) dml:Dmul_22810 (0 target-flexibility) (0 robustness) dml:Dmul_22820 (377 target-flexibility) (117 robustness) dml:Dmul_22850 (752 target-flexibility) (76 robustness) dml:Dmul_22990 (0 target-flexibility) (0 robustness) dml:Dmul_23060 (0 target-flexibility) (0 robustness) dml:Dmul_23280 (0 target-flexibility) (0 robustness) dml:Dmul_23530 (841 target-flexibility) (126 robustness) dml:Dmul_23540 (841 target-flexibility) (126 robustness) dml:Dmul_23620 (790 target-flexibility) (134 robustness) dml:Dmul_24040 (0 target-flexibility) (0 robustness) dml:Dmul_24260 (0 target-flexibility) (0 robustness) dml:Dmul_24630 (0 target-flexibility) (0 robustness) dml:Dmul_24950 (659 target-flexibility) (240 robustness) dml:Dmul_25270 (64 target-flexibility) (64 robustness) dml:Dmul_25380 (528 target-flexibility) (157 robustness) dml:Dmul_26870 (138 target-flexibility) (138 robustness) dml:Dmul_27020 (0 target-flexibility) (0 robustness) dml:Dmul_27550 (657 target-flexibility) (95 robustness) dml:Dmul_27750 (70 target-flexibility) (70 robustness) dml:Dmul_27780 (140 target-flexibility) (71 robustness) dml:Dmul_27800 (67 target-flexibility) (67 robustness) dml:Dmul_27810 (239 target-flexibility) (67 robustness) dml:Dmul_28060 (659 target-flexibility) (240 robustness) dml:Dmul_28240 (0 target-flexibility) (0 robustness) dml:Dmul_28270 (0 target-flexibility) (0 robustness) dml:Dmul_28300 (0 target-flexibility) (0 robustness) dml:Dmul_28400 (686 target-flexibility) (192 robustness) dml:Dmul_30910 (600 target-flexibility) (126 robustness) dml:Dmul_31150 (0 target-flexibility) (0 robustness) dml:Dmul_31220 (924 target-flexibility) (101 robustness) dml:Dmul_31480 (659 target-flexibility) (240 robustness) dml:Dmul_32700 (0 target-flexibility) (0 robustness) dml:Dmul_32710 (0 target-flexibility) (0 robustness) dml:Dmul_34340 (0 target-flexibility) (0 robustness) dml:Dmul_34350 (0 target-flexibility) (0 robustness) dml:Dmul_34490 (1183 target-flexibility) (114 robustness) dml:Dmul_34830 (323 target-flexibility) (101 robustness) dml:Dmul_34880 (1385 target-flexibility) (204 robustness) dml:Dmul_35200 (924 target-flexibility) (101 robustness) dml:Dmul_35620 (434 target-flexibility) (67 robustness) dml:Dmul_36330 (1108 target-flexibility) (319 robustness) dml:Dmul_36880 (0 target-flexibility) (0 robustness) dml:Dmul_38190 (91 target-flexibility) (91 robustness) dml:Dmul_38690 (215 target-flexibility) (142 robustness) dml:Dmul_38810 (212 target-flexibility) (73 robustness) dml:Dmul_38840 (0 target-flexibility) (0 robustness) doa:AXF15_00335 (732 target-flexibility) (78 robustness) doa:AXF15_00575 (821 target-flexibility) (137 robustness) doa:AXF15_00690 (0 target-flexibility) (0 robustness) doa:AXF15_01445 (700 target-flexibility) (77 robustness) doa:AXF15_01830 (701 target-flexibility) (106 robustness) doa:AXF15_02145 (138 target-flexibility) (66 robustness) doa:AXF15_02215 (0 target-flexibility) (0 robustness) doa:AXF15_02480 (1385 target-flexibility) (204 robustness) doa:AXF15_02605 (821 target-flexibility) (137 robustness) doa:AXF15_03010 (1385 target-flexibility) (204 robustness) doa:AXF15_03265 (790 target-flexibility) (134 robustness) doa:AXF15_03465 (0 target-flexibility) (0 robustness) doa:AXF15_03650 (80 target-flexibility) (80 robustness) doa:AXF15_03730 (600 target-flexibility) (126 robustness) doa:AXF15_04035 (659 target-flexibility) (240 robustness) doa:AXF15_04135 (357 target-flexibility) (102 robustness) doa:AXF15_04310 (0 target-flexibility) (0 robustness) doa:AXF15_04445 (0 target-flexibility) (0 robustness) doa:AXF15_04685 (700 target-flexibility) (77 robustness) doa:AXF15_04690 (335 target-flexibility) (69 robustness) doa:AXF15_04820 (796 target-flexibility) (85 robustness) doa:AXF15_04965 (0 target-flexibility) (0 robustness) doa:AXF15_04970 (0 target-flexibility) (0 robustness) doa:AXF15_05040 (897 target-flexibility) (71 robustness) doa:AXF15_05165 (600 target-flexibility) (126 robustness) doa:AXF15_05690 (841 target-flexibility) (126 robustness) doa:AXF15_05735 (0 target-flexibility) (0 robustness) doa:AXF15_05770 (706 target-flexibility) (173 robustness) doa:AXF15_05775 (706 target-flexibility) (173 robustness) doa:AXF15_06215 (821 target-flexibility) (137 robustness) doa:AXF15_06240 (703 target-flexibility) (319 robustness) doa:AXF15_06350 (659 target-flexibility) (240 robustness) doa:AXF15_06360 (703 target-flexibility) (319 robustness) doa:AXF15_06400 (0 target-flexibility) (0 robustness) doa:AXF15_07580 (706 target-flexibility) (173 robustness) doa:AXF15_07625 (528 target-flexibility) (157 robustness) doa:AXF15_07630 (701 target-flexibility) (106 robustness) doa:AXF15_08605 (222 target-flexibility) (83 robustness) doa:AXF15_08610 (0 target-flexibility) (0 robustness) doa:AXF15_08670 (289 target-flexibility) (73 robustness) doa:AXF15_08785 (703 target-flexibility) (319 robustness) doa:AXF15_09000 (0 target-flexibility) (0 robustness) doa:AXF15_09390 (790 target-flexibility) (134 robustness) doa:AXF15_09515 (358 target-flexibility) (104 robustness) doa:AXF15_09785 (790 target-flexibility) (134 robustness) doa:AXF15_10405 (0 target-flexibility) (0 robustness) doa:AXF15_10595 (0 target-flexibility) (0 robustness) doa:AXF15_11000 (357 target-flexibility) (102 robustness) doa:AXF15_11370 (357 target-flexibility) (102 robustness) doa:AXF15_11375 (0 target-flexibility) (0 robustness) doa:AXF15_11595 (212 target-flexibility) (73 robustness) doa:AXF15_11865 (434 target-flexibility) (67 robustness) doa:AXF15_11880 (841 target-flexibility) (126 robustness) doa:AXF15_11960 (0 target-flexibility) (0 robustness) doa:AXF15_12135 (335 target-flexibility) (69 robustness) dol:Dole_0026 (924 target-flexibility) (101 robustness) dol:Dole_0063 (0 target-flexibility) (0 robustness) dol:Dole_0121 (405 target-flexibility) (169 robustness) dol:Dole_0122 (732 target-flexibility) (78 robustness) dol:Dole_0128 (343 target-flexibility) (180 robustness) dol:Dole_0164 (0 target-flexibility) (0 robustness) dol:Dole_0187 (700 target-flexibility) (89 robustness) dol:Dole_0202 (0 target-flexibility) (0 robustness) dol:Dole_0222 (600 target-flexibility) (126 robustness) dol:Dole_0261 (691 target-flexibility) (528 robustness) dol:Dole_0314 (0 target-flexibility) (0 robustness) dol:Dole_0337 (0 target-flexibility) (0 robustness) dol:Dole_0367 (1041 target-flexibility) (243 robustness) dol:Dole_0514 (897 target-flexibility) (71 robustness) dol:Dole_0542 (691 target-flexibility) (528 robustness) dol:Dole_0559 (0 target-flexibility) (0 robustness) dol:Dole_0582 (0 target-flexibility) (0 robustness) dol:Dole_0670 (752 target-flexibility) (76 robustness) dol:Dole_0679 (0 target-flexibility) (0 robustness) dol:Dole_0683 (0 target-flexibility) (0 robustness) dol:Dole_0756 (358 target-flexibility) (124 robustness) dol:Dole_0783 (0 target-flexibility) (0 robustness) dol:Dole_0838 (0 target-flexibility) (0 robustness) dol:Dole_0966 (377 target-flexibility) (117 robustness) dol:Dole_0983 (343 target-flexibility) (180 robustness) dol:Dole_1002 (0 target-flexibility) (0 robustness) dol:Dole_1010 (0 target-flexibility) (0 robustness) dol:Dole_1012 (0 target-flexibility) (0 robustness) dol:Dole_1021 (497 target-flexibility) (186 robustness) dol:Dole_1068 (879 target-flexibility) (71 robustness) dol:Dole_1107 (821 target-flexibility) (137 robustness) dol:Dole_1130 (1041 target-flexibility) (243 robustness) dol:Dole_1132 (80 target-flexibility) (80 robustness) dol:Dole_1166 (358 target-flexibility) (104 robustness) dol:Dole_1191 (222 target-flexibility) (83 robustness) dol:Dole_1326 (902 target-flexibility) (228 robustness) dol:Dole_1355 (706 target-flexibility) (173 robustness) dol:Dole_1426 (231 target-flexibility) (158 robustness) dol:Dole_1564 (686 target-flexibility) (192 robustness) dol:Dole_1608 (659 target-flexibility) (240 robustness) dol:Dole_1729 (212 target-flexibility) (73 robustness) dol:Dole_1848 (0 target-flexibility) (0 robustness) dol:Dole_1881 (343 target-flexibility) (180 robustness) dol:Dole_1908 (289 target-flexibility) (73 robustness) dol:Dole_1973 (790 target-flexibility) (134 robustness) dol:Dole_2040 (841 target-flexibility) (126 robustness) dol:Dole_2786 (70 target-flexibility) (70 robustness) dol:Dole_2791 (67 target-flexibility) (67 robustness) dpb:BABL1_gene_13 (0 target-flexibility) (0 robustness) dpb:BABL1_gene_199 (212 target-flexibility) (73 robustness) dpb:BABL1_gene_330 (752 target-flexibility) (76 robustness) dpb:BABL1_gene_5 (1935 target-flexibility) (162 robustness) dpb:BABL1_gene_545 (138 target-flexibility) (138 robustness) dpb:BABL1_gene_6 (1935 target-flexibility) (162 robustness) dpb:BABL1_gene_705 (71 target-flexibility) (71 robustness) dpb:BABL1_gene_809 (138 target-flexibility) (138 robustness) dpb:BABL1_gene_827 (138 target-flexibility) (138 robustness) dpb:BABL1_gene_858 (222 target-flexibility) (83 robustness) dpb:BABL1_gene_980 (138 target-flexibility) (138 robustness) dpg:DESPIGER_0283 (0 target-flexibility) (0 robustness) dpg:DESPIGER_0323 (0 target-flexibility) (0 robustness) dpg:DESPIGER_0326 (0 target-flexibility) (0 robustness) dpg:DESPIGER_0351 (357 target-flexibility) (115 robustness) dpg:DESPIGER_0488 (357 target-flexibility) (115 robustness) dpg:DESPIGER_0493 (686 target-flexibility) (192 robustness) dpg:DESPIGER_0549 (706 target-flexibility) (173 robustness) dpg:DESPIGER_0552 (706 target-flexibility) (173 robustness) dpg:DESPIGER_0559 (0 target-flexibility) (0 robustness) dpg:DESPIGER_0649 (706 target-flexibility) (173 robustness) dpg:DESPIGER_0682 (0 target-flexibility) (0 robustness) dpg:DESPIGER_0694 (138 target-flexibility) (138 robustness) dpg:DESPIGER_0969 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1072 (703 target-flexibility) (319 robustness) dpg:DESPIGER_1079 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1110 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1191 (357 target-flexibility) (102 robustness) dpg:DESPIGER_1250 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1284 (222 target-flexibility) (83 robustness) dpg:DESPIGER_1297 (790 target-flexibility) (134 robustness) dpg:DESPIGER_1352 (686 target-flexibility) (192 robustness) dpg:DESPIGER_1482 (706 target-flexibility) (173 robustness) dpg:DESPIGER_1531 (80 target-flexibility) (80 robustness) dpg:DESPIGER_1545 (434 target-flexibility) (67 robustness) dpg:DESPIGER_1552 (103 target-flexibility) (103 robustness) dpg:DESPIGER_1638 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1704 (1385 target-flexibility) (204 robustness) dpg:DESPIGER_1719 (357 target-flexibility) (102 robustness) dpg:DESPIGER_1797 (289 target-flexibility) (73 robustness) dpg:DESPIGER_1814 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1815 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1830 (1385 target-flexibility) (204 robustness) dpg:DESPIGER_1832 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1840 (600 target-flexibility) (126 robustness) dpg:DESPIGER_1913 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1949 (0 target-flexibility) (0 robustness) dpg:DESPIGER_2055 (103 target-flexibility) (103 robustness) dpg:DESPIGER_2071 (600 target-flexibility) (126 robustness) dpg:DESPIGER_2129 (212 target-flexibility) (73 robustness) dpg:DESPIGER_2402 (703 target-flexibility) (319 robustness) dpg:DESPIGER_2419 (0 target-flexibility) (0 robustness) dpg:DESPIGER_2427 (0 target-flexibility) (0 robustness) dpg:DESPIGER_2441 (138 target-flexibility) (138 robustness) dpi:BN4_10025 (301 target-flexibility) (154 robustness) dpi:BN4_10026 (301 target-flexibility) (154 robustness) dpi:BN4_10112 (841 target-flexibility) (126 robustness) dpi:BN4_10115 (434 target-flexibility) (67 robustness) dpi:BN4_10127 (0 target-flexibility) (0 robustness) dpi:BN4_10161 (138 target-flexibility) (138 robustness) dpi:BN4_10196 (71 target-flexibility) (71 robustness) dpi:BN4_10242 (279 target-flexibility) (126 robustness) dpi:BN4_10265 (711 target-flexibility) (104 robustness) dpi:BN4_10278 (0 target-flexibility) (0 robustness) dpi:BN4_10320 (138 target-flexibility) (138 robustness) dpi:BN4_10344 (0 target-flexibility) (0 robustness) dpi:BN4_10368 (902 target-flexibility) (228 robustness) dpi:BN4_10369 (902 target-flexibility) (228 robustness) dpi:BN4_10393 (222 target-flexibility) (83 robustness) dpi:BN4_10396 (528 target-flexibility) (157 robustness) dpi:BN4_10404 (902 target-flexibility) (228 robustness) dpi:BN4_10420 (706 target-flexibility) (173 robustness) dpi:BN4_10458 (854 target-flexibility) (204 robustness) dpi:BN4_10478 (0 target-flexibility) (0 robustness) dpi:BN4_10485 (841 target-flexibility) (126 robustness) dpi:BN4_10583 (301 target-flexibility) (154 robustness) dpi:BN4_10584 (301 target-flexibility) (154 robustness) dpi:BN4_10697 (706 target-flexibility) (173 robustness) dpi:BN4_10725 (711 target-flexibility) (104 robustness) dpi:BN4_10871 (0 target-flexibility) (0 robustness) dpi:BN4_10876 (0 target-flexibility) (0 robustness) dpi:BN4_10961 (0 target-flexibility) (0 robustness) dpi:BN4_10996 (0 target-flexibility) (0 robustness) dpi:BN4_11008 (358 target-flexibility) (104 robustness) dpi:BN4_11060 (0 target-flexibility) (0 robustness) dpi:BN4_11230 (528 target-flexibility) (157 robustness) dpi:BN4_11318 (0 target-flexibility) (0 robustness) dpi:BN4_11354 (80 target-flexibility) (80 robustness) dpi:BN4_11368 (659 target-flexibility) (240 robustness) dpi:BN4_11381 (138 target-flexibility) (138 robustness) dpi:BN4_11407 (289 target-flexibility) (73 robustness) dpi:BN4_11611 (659 target-flexibility) (240 robustness) dpi:BN4_11683 (0 target-flexibility) (0 robustness) dpi:BN4_11717 (80 target-flexibility) (80 robustness) dpi:BN4_11826 (358 target-flexibility) (104 robustness) dpi:BN4_11854 (0 target-flexibility) (0 robustness) dpi:BN4_11857 (0 target-flexibility) (0 robustness) dpi:BN4_11868 (854 target-flexibility) (204 robustness) dpi:BN4_11936 (212 target-flexibility) (73 robustness) dpi:BN4_11977 (752 target-flexibility) (76 robustness) dpi:BN4_12054 (790 target-flexibility) (134 robustness) dpi:BN4_12061 (0 target-flexibility) (0 robustness) dpi:BN4_12067 (821 target-flexibility) (137 robustness) dpi:BN4_12189 (821 target-flexibility) (137 robustness) dpi:BN4_12214 (0 target-flexibility) (0 robustness) dpi:BN4_12231 (0 target-flexibility) (0 robustness) dpi:BN4_12300 (902 target-flexibility) (228 robustness) dpi:BN4_12384 (790 target-flexibility) (134 robustness) dpi:BN4_12469 (0 target-flexibility) (0 robustness) dpi:BN4_12531 (1385 target-flexibility) (204 robustness) dpi:BN4_12584 (790 target-flexibility) (134 robustness) dpi:BN4_12643 (0 target-flexibility) (0 robustness) dpi:BN4_12690 (821 target-flexibility) (137 robustness) dpi:BN4_12775 (1385 target-flexibility) (204 robustness) dpi:BN4_12812 (0 target-flexibility) (0 robustness) dpi:BN4_20024 (706 target-flexibility) (173 robustness) dpi:BN4_20088 (706 target-flexibility) (173 robustness) dpi:BN4_20265 (0 target-flexibility) (0 robustness) dpi:BN4_20324 (0 target-flexibility) (0 robustness) dpi:BN4_20344 (219 target-flexibility) (63 robustness) dpi:BN4_20389 (279 target-flexibility) (126 robustness) dpi:BN4_20419 (219 target-flexibility) (63 robustness) dpr:Despr_0075 (0 target-flexibility) (0 robustness) dpr:Despr_0082 (0 target-flexibility) (0 robustness) dpr:Despr_0279 (0 target-flexibility) (0 robustness) dpr:Despr_0281 (924 target-flexibility) (101 robustness) dpr:Despr_0314 (691 target-flexibility) (528 robustness) dpr:Despr_0363 (0 target-flexibility) (0 robustness) dpr:Despr_0386 (0 target-flexibility) (0 robustness) dpr:Despr_0441 (902 target-flexibility) (228 robustness) dpr:Despr_0517 (138 target-flexibility) (66 robustness) dpr:Despr_0555 (0 target-flexibility) (0 robustness) dpr:Despr_0559 (0 target-flexibility) (0 robustness) dpr:Despr_0574 (289 target-flexibility) (73 robustness) dpr:Despr_0744 (924 target-flexibility) (101 robustness) dpr:Despr_0827 (700 target-flexibility) (80 robustness) dpr:Despr_0862 (1385 target-flexibility) (204 robustness) dpr:Despr_0909 (434 target-flexibility) (67 robustness) dpr:Despr_0910 (657 target-flexibility) (95 robustness) dpr:Despr_0918 (71 target-flexibility) (71 robustness) dpr:Despr_0929 (405 target-flexibility) (169 robustness) dpr:Despr_1050 (1385 target-flexibility) (204 robustness) dpr:Despr_1373 (0 target-flexibility) (0 robustness) dpr:Despr_1394 (902 target-flexibility) (228 robustness) dpr:Despr_1502 (790 target-flexibility) (134 robustness) dpr:Despr_1504 (924 target-flexibility) (101 robustness) dpr:Despr_1528 (732 target-flexibility) (78 robustness) dpr:Despr_1538 (0 target-flexibility) (0 robustness) dpr:Despr_1637 (0 target-flexibility) (0 robustness) dpr:Despr_1640 (138 target-flexibility) (138 robustness) dpr:Despr_1674 (0 target-flexibility) (0 robustness) dpr:Despr_1776 (841 target-flexibility) (126 robustness) dpr:Despr_1832 (0 target-flexibility) (0 robustness) dpr:Despr_1881 (0 target-flexibility) (0 robustness) dpr:Despr_1896 (0 target-flexibility) (0 robustness) dpr:Despr_1916 (691 target-flexibility) (528 robustness) dpr:Despr_1928 (0 target-flexibility) (0 robustness) dpr:Despr_1962 (0 target-flexibility) (0 robustness) dpr:Despr_2003 (0 target-flexibility) (0 robustness) dpr:Despr_2009 (703 target-flexibility) (319 robustness) dpr:Despr_2011 (659 target-flexibility) (240 robustness) dpr:Despr_2042 (706 target-flexibility) (173 robustness) dpr:Despr_2089 (0 target-flexibility) (0 robustness) dpr:Despr_2092 (0 target-flexibility) (0 robustness) dpr:Despr_2093 (0 target-flexibility) (0 robustness) dpr:Despr_2189 (138 target-flexibility) (138 robustness) dpr:Despr_2283 (358 target-flexibility) (104 robustness) dpr:Despr_2289 (239 target-flexibility) (99 robustness) dpr:Despr_2311 (841 target-flexibility) (126 robustness) dpr:Despr_2324 (239 target-flexibility) (99 robustness) dpr:Despr_2346 (686 target-flexibility) (192 robustness) dpr:Despr_2376 (686 target-flexibility) (192 robustness) dpr:Despr_2394 (222 target-flexibility) (83 robustness) dpr:Despr_2467 (0 target-flexibility) (0 robustness) dpr:Despr_2483 (657 target-flexibility) (95 robustness) dpr:Despr_2500 (659 target-flexibility) (240 robustness) dpr:Despr_2534 (902 target-flexibility) (228 robustness) dpr:Despr_2589 (700 target-flexibility) (80 robustness) dpr:Despr_2665 (659 target-flexibility) (240 robustness) dpr:Despr_2670 (703 target-flexibility) (319 robustness) dpr:Despr_2672 (790 target-flexibility) (134 robustness) dpr:Despr_2721 (732 target-flexibility) (78 robustness) dpr:Despr_2776 (752 target-flexibility) (76 robustness) dpr:Despr_2813 (706 target-flexibility) (173 robustness) dpr:Despr_2865 (706 target-flexibility) (173 robustness) dpr:Despr_2867 (706 target-flexibility) (173 robustness) dpr:Despr_2873 (706 target-flexibility) (173 robustness) dpr:Despr_2908 (0 target-flexibility) (0 robustness) dpr:Despr_2956 (138 target-flexibility) (138 robustness) dpr:Despr_2958 (80 target-flexibility) (80 robustness) dpr:Despr_2977 (600 target-flexibility) (126 robustness) dpr:Despr_2980 (1784 target-flexibility) (162 robustness) dpr:Despr_2989 (528 target-flexibility) (157 robustness) dpr:Despr_3037 (212 target-flexibility) (73 robustness) dpr:Despr_3102 (0 target-flexibility) (0 robustness) dpr:Despr_3152 (600 target-flexibility) (126 robustness) dpr:Despr_3156 (897 target-flexibility) (71 robustness) dpr:Despr_3168 (0 target-flexibility) (0 robustness) dpr:Despr_3183 (358 target-flexibility) (104 robustness) dpr:Despr_3256 (1784 target-flexibility) (162 robustness) dpr:Despr_3296 (405 target-flexibility) (169 robustness) dpr:Despr_3306 (0 target-flexibility) (0 robustness) dpr:Despr_3332 (0 target-flexibility) (0 robustness) dps:DP0014 (0 target-flexibility) (0 robustness) dps:DP0022 (0 target-flexibility) (0 robustness) dps:DP0026 (0 target-flexibility) (0 robustness) dps:DP0044 (0 target-flexibility) (0 robustness) dps:DP0045 (0 target-flexibility) (0 robustness) dps:DP0059 (0 target-flexibility) (0 robustness) dps:DP0067 (0 target-flexibility) (0 robustness) dps:DP0103 (600 target-flexibility) (126 robustness) dps:DP0106 (897 target-flexibility) (71 robustness) dps:DP0394 (924 target-flexibility) (101 robustness) dps:DP0437 (138 target-flexibility) (66 robustness) dps:DP0475 (0 target-flexibility) (0 robustness) dps:DP0540 (879 target-flexibility) (71 robustness) dps:DP0544 (879 target-flexibility) (71 robustness) dps:DP0555 (0 target-flexibility) (0 robustness) dps:DP0660 (841 target-flexibility) (126 robustness) dps:DP0784 (691 target-flexibility) (528 robustness) dps:DP0812 (80 target-flexibility) (80 robustness) dps:DP0822 (600 target-flexibility) (126 robustness) dps:DP0825 (790 target-flexibility) (134 robustness) dps:DP0950 (0 target-flexibility) (0 robustness) dps:DP0951 (0 target-flexibility) (0 robustness) dps:DP0952 (0 target-flexibility) (0 robustness) dps:DP0955 (0 target-flexibility) (0 robustness) dps:DP1007 (0 target-flexibility) (0 robustness) dps:DP1022 (0 target-flexibility) (0 robustness) dps:DP1088 (924 target-flexibility) (101 robustness) dps:DP1165 (700 target-flexibility) (80 robustness) dps:DP1266 (0 target-flexibility) (0 robustness) dps:DP1272 (0 target-flexibility) (0 robustness) dps:DP1331 (206 target-flexibility) (68 robustness) dps:DP1333 (0 target-flexibility) (0 robustness) dps:DP1431 (691 target-flexibility) (528 robustness) dps:DP1472 (0 target-flexibility) (0 robustness) dps:DP1629 (71 target-flexibility) (71 robustness) dps:DP1631 (686 target-flexibility) (192 robustness) dps:DP1796 (212 target-flexibility) (73 robustness) dps:DP1847 (659 target-flexibility) (240 robustness) dps:DP1859 (703 target-flexibility) (319 robustness) dps:DP1905 (700 target-flexibility) (80 robustness) dps:DP2097 (790 target-flexibility) (134 robustness) dps:DP2110 (0 target-flexibility) (0 robustness) dps:DP2172 (700 target-flexibility) (89 robustness) dps:DP2220 (0 target-flexibility) (0 robustness) dps:DP2221 (0 target-flexibility) (0 robustness) dps:DP2376 (0 target-flexibility) (0 robustness) dps:DP2403 (703 target-flexibility) (319 robustness) dps:DP2407 (659 target-flexibility) (240 robustness) dps:DP2474 (0 target-flexibility) (0 robustness) dps:DP2475 (0 target-flexibility) (0 robustness) dps:DP2548 (0 target-flexibility) (0 robustness) dps:DP2552 (222 target-flexibility) (83 robustness) dps:DP2600 (0 target-flexibility) (0 robustness) dps:DP2716 (0 target-flexibility) (0 robustness) dps:DP2768 (841 target-flexibility) (126 robustness) dps:DP2788 (703 target-flexibility) (319 robustness) dps:DP2790 (659 target-flexibility) (240 robustness) dps:DP2949 (686 target-flexibility) (192 robustness) dps:DP2990 (0 target-flexibility) (0 robustness) dps:DP2991 (700 target-flexibility) (89 robustness) dps:DPPB37 (790 target-flexibility) (134 robustness) dps:DPPB64 (0 target-flexibility) (0 robustness) dps:DPPB68 (0 target-flexibility) (0 robustness) dps:DPPB70 (0 target-flexibility) (0 robustness) drt:Dret_0011 (0 target-flexibility) (0 robustness) drt:Dret_0014 (752 target-flexibility) (76 robustness) drt:Dret_0042 (0 target-flexibility) (0 robustness) drt:Dret_0079 (1385 target-flexibility) (204 robustness) drt:Dret_0124 (686 target-flexibility) (192 robustness) drt:Dret_0143 (796 target-flexibility) (85 robustness) drt:Dret_0199 (0 target-flexibility) (0 robustness) drt:Dret_0202 (0 target-flexibility) (0 robustness) drt:Dret_0251 (212 target-flexibility) (73 robustness) drt:Dret_0307 (0 target-flexibility) (0 robustness) drt:Dret_0321 (732 target-flexibility) (78 robustness) drt:Dret_0340 (600 target-flexibility) (126 robustness) drt:Dret_0439 (289 target-flexibility) (73 robustness) drt:Dret_0460 (0 target-flexibility) (0 robustness) drt:Dret_0505 (855 target-flexibility) (138 robustness) drt:Dret_0537 (358 target-flexibility) (104 robustness) drt:Dret_0542 (138 target-flexibility) (138 robustness) drt:Dret_0704 (706 target-flexibility) (173 robustness) drt:Dret_0730 (0 target-flexibility) (0 robustness) drt:Dret_0772 (138 target-flexibility) (138 robustness) drt:Dret_0798 (686 target-flexibility) (192 robustness) drt:Dret_0818 (790 target-flexibility) (134 robustness) drt:Dret_0830 (358 target-flexibility) (104 robustness) drt:Dret_1010 (706 target-flexibility) (173 robustness) drt:Dret_1046 (0 target-flexibility) (0 robustness) drt:Dret_1100 (434 target-flexibility) (67 robustness) drt:Dret_1107 (855 target-flexibility) (138 robustness) drt:Dret_1118 (222 target-flexibility) (83 robustness) drt:Dret_1139 (0 target-flexibility) (0 robustness) drt:Dret_1384 (405 target-flexibility) (70 robustness) drt:Dret_1385 (528 target-flexibility) (157 robustness) drt:Dret_1397 (600 target-flexibility) (126 robustness) drt:Dret_1409 (357 target-flexibility) (102 robustness) drt:Dret_1425 (0 target-flexibility) (0 robustness) drt:Dret_1459 (841 target-flexibility) (126 robustness) drt:Dret_1706 (841 target-flexibility) (126 robustness) drt:Dret_1756 (0 target-flexibility) (0 robustness) drt:Dret_1907 (138 target-flexibility) (138 robustness) drt:Dret_1968 (0 target-flexibility) (0 robustness) drt:Dret_2027 (1385 target-flexibility) (204 robustness) drt:Dret_2034 (0 target-flexibility) (0 robustness) drt:Dret_2102 (497 target-flexibility) (186 robustness) drt:Dret_2103 (0 target-flexibility) (0 robustness) drt:Dret_2110 (0 target-flexibility) (0 robustness) drt:Dret_2132 (790 target-flexibility) (134 robustness) drt:Dret_2234 (71 target-flexibility) (71 robustness) drt:Dret_2408 (0 target-flexibility) (0 robustness) drt:Dret_2421 (80 target-flexibility) (80 robustness) drt:Dret_2429 (497 target-flexibility) (186 robustness) drt:Dret_2432 (0 target-flexibility) (0 robustness) drt:Dret_2481 (790 target-flexibility) (134 robustness) drt:Dret_2499 (0 target-flexibility) (0 robustness) dsa:Desal_0017 (897 target-flexibility) (71 robustness) dsa:Desal_0041 (0 target-flexibility) (0 robustness) dsa:Desal_0092 (790 target-flexibility) (134 robustness) dsa:Desal_0136 (528 target-flexibility) (157 robustness) dsa:Desal_0143 (752 target-flexibility) (76 robustness) dsa:Desal_0152 (790 target-flexibility) (134 robustness) dsa:Desal_0178 (0 target-flexibility) (0 robustness) dsa:Desal_0250 (212 target-flexibility) (73 robustness) dsa:Desal_0284 (0 target-flexibility) (0 robustness) dsa:Desal_0289 (0 target-flexibility) (0 robustness) dsa:Desal_0368 (0 target-flexibility) (0 robustness) dsa:Desal_0408 (138 target-flexibility) (138 robustness) dsa:Desal_0523 (703 target-flexibility) (319 robustness) dsa:Desal_0538 (703 target-flexibility) (319 robustness) dsa:Desal_0541 (659 target-flexibility) (240 robustness) dsa:Desal_0558 (1041 target-flexibility) (243 robustness) dsa:Desal_0559 (1041 target-flexibility) (243 robustness) dsa:Desal_0574 (1041 target-flexibility) (243 robustness) dsa:Desal_0575 (1041 target-flexibility) (243 robustness) dsa:Desal_0576 (659 target-flexibility) (240 robustness) dsa:Desal_0616 (387 target-flexibility) (72 robustness) dsa:Desal_0650 (0 target-flexibility) (0 robustness) dsa:Desal_0657 (1066 target-flexibility) (75 robustness) dsa:Desal_0661 (1108 target-flexibility) (319 robustness) dsa:Desal_0743 (0 target-flexibility) (0 robustness) dsa:Desal_0753 (80 target-flexibility) (80 robustness) dsa:Desal_0836 (0 target-flexibility) (0 robustness) dsa:Desal_0990 (0 target-flexibility) (0 robustness) dsa:Desal_1082 (821 target-flexibility) (137 robustness) dsa:Desal_1093 (289 target-flexibility) (73 robustness) dsa:Desal_1102 (103 target-flexibility) (103 robustness) dsa:Desal_1363 (138 target-flexibility) (138 robustness) dsa:Desal_1479 (902 target-flexibility) (228 robustness) dsa:Desal_1582 (841 target-flexibility) (126 robustness) dsa:Desal_1628 (0 target-flexibility) (0 robustness) dsa:Desal_1645 (0 target-flexibility) (0 robustness) dsa:Desal_1745 (138 target-flexibility) (138 robustness) dsa:Desal_1769 (902 target-flexibility) (228 robustness) dsa:Desal_1818 (138 target-flexibility) (138 robustness) dsa:Desal_1910 (600 target-flexibility) (126 robustness) dsa:Desal_2027 (0 target-flexibility) (0 robustness) dsa:Desal_2033 (0 target-flexibility) (0 robustness) dsa:Desal_2037 (706 target-flexibility) (173 robustness) dsa:Desal_2170 (732 target-flexibility) (78 robustness) dsa:Desal_2198 (706 target-flexibility) (173 robustness) dsa:Desal_2302 (855 target-flexibility) (138 robustness) dsa:Desal_2682 (0 target-flexibility) (0 robustness) dsa:Desal_2806 (219 target-flexibility) (63 robustness) dsa:Desal_2862 (358 target-flexibility) (104 robustness) dsa:Desal_2872 (0 target-flexibility) (0 robustness) dsa:Desal_2997 (323 target-flexibility) (101 robustness) dsa:Desal_3010 (686 target-flexibility) (192 robustness) dsa:Desal_3303 (879 target-flexibility) (71 robustness) dsa:Desal_3407 (1385 target-flexibility) (204 robustness) dsf:UWK_00066 (405 target-flexibility) (169 robustness) dsf:UWK_00067 (405 target-flexibility) (169 robustness) dsf:UWK_00087 (0 target-flexibility) (0 robustness) dsf:UWK_00094 (0 target-flexibility) (0 robustness) dsf:UWK_00105 (528 target-flexibility) (157 robustness) dsf:UWK_00122 (703 target-flexibility) (319 robustness) dsf:UWK_00132 (659 target-flexibility) (240 robustness) dsf:UWK_00143 (703 target-flexibility) (319 robustness) dsf:UWK_00144 (703 target-flexibility) (319 robustness) dsf:UWK_00180 (212 target-flexibility) (73 robustness) dsf:UWK_00304 (1784 target-flexibility) (162 robustness) dsf:UWK_00316 (0 target-flexibility) (0 robustness) dsf:UWK_00318 (1784 target-flexibility) (162 robustness) dsf:UWK_00454 (607 target-flexibility) (75 robustness) dsf:UWK_00579 (924 target-flexibility) (101 robustness) dsf:UWK_00627 (706 target-flexibility) (173 robustness) dsf:UWK_00683 (138 target-flexibility) (66 robustness) dsf:UWK_00704 (1784 target-flexibility) (162 robustness) dsf:UWK_00709 (1784 target-flexibility) (162 robustness) dsf:UWK_00789 (600 target-flexibility) (126 robustness) dsf:UWK_00793 (897 target-flexibility) (71 robustness) dsf:UWK_00827 (91 target-flexibility) (91 robustness) dsf:UWK_00846 (0 target-flexibility) (0 robustness) dsf:UWK_00965 (0 target-flexibility) (0 robustness) dsf:UWK_00991 (0 target-flexibility) (0 robustness) dsf:UWK_01050 (0 target-flexibility) (0 robustness) dsf:UWK_01152 (752 target-flexibility) (76 robustness) dsf:UWK_01260 (732 target-flexibility) (78 robustness) dsf:UWK_01351 (821 target-flexibility) (137 robustness) dsf:UWK_01372 (0 target-flexibility) (0 robustness) dsf:UWK_01373 (0 target-flexibility) (0 robustness) dsf:UWK_01435 (0 target-flexibility) (0 robustness) dsf:UWK_01482 (150 target-flexibility) (76 robustness) dsf:UWK_01506 (262 target-flexibility) (86 robustness) dsf:UWK_01617 (691 target-flexibility) (528 robustness) dsf:UWK_01660 (138 target-flexibility) (138 robustness) dsf:UWK_01662 (80 target-flexibility) (80 robustness) dsf:UWK_01685 (150 target-flexibility) (76 robustness) dsf:UWK_01687 (600 target-flexibility) (126 robustness) dsf:UWK_01758 (0 target-flexibility) (0 robustness) dsf:UWK_01777 (821 target-flexibility) (137 robustness) dsf:UWK_01801 (821 target-flexibility) (137 robustness) dsf:UWK_01819 (358 target-flexibility) (104 robustness) dsf:UWK_01838 (691 target-flexibility) (528 robustness) dsf:UWK_01840 (0 target-flexibility) (0 robustness) dsf:UWK_01915 (700 target-flexibility) (80 robustness) dsf:UWK_01920 (902 target-flexibility) (228 robustness) dsf:UWK_01937 (924 target-flexibility) (101 robustness) dsf:UWK_02087 (700 target-flexibility) (80 robustness) dsf:UWK_02122 (0 target-flexibility) (0 robustness) dsf:UWK_02241 (358 target-flexibility) (104 robustness) dsf:UWK_02316 (700 target-flexibility) (77 robustness) dsf:UWK_02323 (659 target-flexibility) (240 robustness) dsf:UWK_02355 (706 target-flexibility) (173 robustness) dsf:UWK_02372 (70 target-flexibility) (70 robustness) dsf:UWK_02430 (902 target-flexibility) (228 robustness) dsf:UWK_02435 (70 target-flexibility) (70 robustness) dsf:UWK_02496 (657 target-flexibility) (95 robustness) dsf:UWK_02513 (0 target-flexibility) (0 robustness) dsf:UWK_02514 (1169 target-flexibility) (76 robustness) dsf:UWK_02522 (691 target-flexibility) (528 robustness) dsf:UWK_02569 (659 target-flexibility) (240 robustness) dsf:UWK_02571 (703 target-flexibility) (319 robustness) dsf:UWK_02594 (902 target-flexibility) (228 robustness) dsf:UWK_02595 (841 target-flexibility) (126 robustness) dsf:UWK_02650 (706 target-flexibility) (173 robustness) dsf:UWK_02667 (0 target-flexibility) (0 robustness) dsf:UWK_02742 (607 target-flexibility) (75 robustness) dsf:UWK_02745 (262 target-flexibility) (86 robustness) dsf:UWK_02784 (91 target-flexibility) (91 robustness) dsf:UWK_02797 (1041 target-flexibility) (243 robustness) dsf:UWK_02799 (0 target-flexibility) (0 robustness) dsf:UWK_02885 (841 target-flexibility) (126 robustness) dsf:UWK_02927 (700 target-flexibility) (77 robustness) dsf:UWK_02972 (138 target-flexibility) (138 robustness) dsf:UWK_02973 (703 target-flexibility) (319 robustness) dsf:UWK_02977 (659 target-flexibility) (240 robustness) dsf:UWK_03000 (72 target-flexibility) (72 robustness) dsf:UWK_03051 (405 target-flexibility) (169 robustness) dsf:UWK_03052 (405 target-flexibility) (169 robustness) dsf:UWK_03057 (0 target-flexibility) (0 robustness) dsf:UWK_03174 (70 target-flexibility) (70 robustness) dsf:UWK_03294 (0 target-flexibility) (0 robustness) dsf:UWK_03329 (686 target-flexibility) (192 robustness) dsf:UWK_03336 (691 target-flexibility) (528 robustness) dsf:UWK_03366 (686 target-flexibility) (192 robustness) dsf:UWK_03406 (0 target-flexibility) (0 robustness) dsf:UWK_03410 (222 target-flexibility) (83 robustness) dsf:UWK_03421 (0 target-flexibility) (0 robustness) dsf:UWK_03510 (796 target-flexibility) (85 robustness) dsf:UWK_03535 (71 target-flexibility) (71 robustness) dsf:UWK_03539 (657 target-flexibility) (95 robustness) dti:Desti_0036 (0 target-flexibility) (0 robustness) dti:Desti_0051 (902 target-flexibility) (228 robustness) dti:Desti_0057 (600 target-flexibility) (126 robustness) dti:Desti_0059 (528 target-flexibility) (157 robustness) dti:Desti_0062 (405 target-flexibility) (169 robustness) dti:Desti_0148 (1041 target-flexibility) (243 robustness) dti:Desti_0149 (1041 target-flexibility) (243 robustness) dti:Desti_0205 (175 target-flexibility) (96 robustness) dti:Desti_0219 (790 target-flexibility) (134 robustness) dti:Desti_0225 (0 target-flexibility) (0 robustness) dti:Desti_0234 (841 target-flexibility) (126 robustness) dti:Desti_0240 (323 target-flexibility) (101 robustness) dti:Desti_0353 (0 target-flexibility) (0 robustness) dti:Desti_0395 (706 target-flexibility) (173 robustness) dti:Desti_0426 (600 target-flexibility) (126 robustness) dti:Desti_0441 (350 target-flexibility) (84 robustness) dti:Desti_0473 (0 target-flexibility) (0 robustness) dti:Desti_0504 (0 target-flexibility) (0 robustness) dti:Desti_0569 (0 target-flexibility) (0 robustness) dti:Desti_0754 (219 target-flexibility) (63 robustness) dti:Desti_0755 (323 target-flexibility) (101 robustness) dti:Desti_0757 (91 target-flexibility) (91 robustness) dti:Desti_0759 (659 target-flexibility) (240 robustness) dti:Desti_0774 (0 target-flexibility) (0 robustness) dti:Desti_0802 (73 target-flexibility) (73 robustness) dti:Desti_0830 (706 target-flexibility) (173 robustness) dti:Desti_0874 (138 target-flexibility) (138 robustness) dti:Desti_0881 (0 target-flexibility) (0 robustness) dti:Desti_0896 (0 target-flexibility) (0 robustness) dti:Desti_0901 (0 target-flexibility) (0 robustness) dti:Desti_0925 (0 target-flexibility) (0 robustness) dti:Desti_0927 (821 target-flexibility) (137 robustness) dti:Desti_0942 (0 target-flexibility) (0 robustness) dti:Desti_0981 (350 target-flexibility) (84 robustness) dti:Desti_0988 (634 target-flexibility) (72 robustness) dti:Desti_1014 (175 target-flexibility) (96 robustness) dti:Desti_1036 (659 target-flexibility) (240 robustness) dti:Desti_1039 (486 target-flexibility) (89 robustness) dti:Desti_1152 (206 target-flexibility) (68 robustness) dti:Desti_1171 (706 target-flexibility) (173 robustness) dti:Desti_1190 (0 target-flexibility) (0 robustness) dti:Desti_1200 (0 target-flexibility) (0 robustness) dti:Desti_1201 (0 target-flexibility) (0 robustness) dti:Desti_1206 (841 target-flexibility) (126 robustness) dti:Desti_1259 (752 target-flexibility) (76 robustness) dti:Desti_1266 (686 target-flexibility) (192 robustness) dti:Desti_1340 (323 target-flexibility) (101 robustness) dti:Desti_1366 (0 target-flexibility) (0 robustness) dti:Desti_1457 (0 target-flexibility) (0 robustness) dti:Desti_1492 (1169 target-flexibility) (76 robustness) dti:Desti_1600 (821 target-flexibility) (137 robustness) dti:Desti_1662 (138 target-flexibility) (138 robustness) dti:Desti_1674 (0 target-flexibility) (0 robustness) dti:Desti_1695 (279 target-flexibility) (126 robustness) dti:Desti_1700 (387 target-flexibility) (72 robustness) dti:Desti_1808 (0 target-flexibility) (0 robustness) dti:Desti_1836 (0 target-flexibility) (0 robustness) dti:Desti_1892 (301 target-flexibility) (154 robustness) dti:Desti_2003 (0 target-flexibility) (0 robustness) dti:Desti_2096 (350 target-flexibility) (84 robustness) dti:Desti_2110 (486 target-flexibility) (89 robustness) dti:Desti_2111 (1041 target-flexibility) (243 robustness) dti:Desti_2134 (138 target-flexibility) (138 robustness) dti:Desti_2232 (0 target-flexibility) (0 robustness) dti:Desti_2278 (0 target-flexibility) (0 robustness) dti:Desti_2327 (528 target-flexibility) (157 robustness) dti:Desti_2341 (790 target-flexibility) (134 robustness) dti:Desti_2345 (790 target-flexibility) (134 robustness) dti:Desti_2348 (790 target-flexibility) (134 robustness) dti:Desti_2371 (0 target-flexibility) (0 robustness) dti:Desti_2479 (0 target-flexibility) (0 robustness) dti:Desti_2554 (158 target-flexibility) (72 robustness) dti:Desti_2576 (691 target-flexibility) (528 robustness) dti:Desti_2718 (343 target-flexibility) (180 robustness) dti:Desti_2739 (0 target-flexibility) (0 robustness) dti:Desti_2740 (0 target-flexibility) (0 robustness) dti:Desti_2768 (377 target-flexibility) (117 robustness) dti:Desti_2797 (0 target-flexibility) (0 robustness) dti:Desti_2811 (821 target-flexibility) (137 robustness) dti:Desti_2825 (659 target-flexibility) (240 robustness) dti:Desti_2856 (377 target-flexibility) (117 robustness) dti:Desti_2892 (0 target-flexibility) (0 robustness) dti:Desti_2957 (73 target-flexibility) (73 robustness) dti:Desti_2988 (358 target-flexibility) (124 robustness) dti:Desti_2998 (841 target-flexibility) (126 robustness) dti:Desti_3051 (1385 target-flexibility) (204 robustness) dti:Desti_3101 (659 target-flexibility) (240 robustness) dti:Desti_3108 (279 target-flexibility) (126 robustness) dti:Desti_3121 (71 target-flexibility) (71 robustness) dti:Desti_3139 (1041 target-flexibility) (243 robustness) dti:Desti_3164 (0 target-flexibility) (0 robustness) dti:Desti_3199 (405 target-flexibility) (169 robustness) dti:Desti_3300 (175 target-flexibility) (96 robustness) dti:Desti_3356 (0 target-flexibility) (0 robustness) dti:Desti_3578 (0 target-flexibility) (0 robustness) dti:Desti_3611 (821 target-flexibility) (137 robustness) dti:Desti_3628 (1385 target-flexibility) (204 robustness) dti:Desti_3650 (0 target-flexibility) (0 robustness) dti:Desti_3684 (212 target-flexibility) (73 robustness) dti:Desti_3693 (0 target-flexibility) (0 robustness) dti:Desti_3729 (0 target-flexibility) (0 robustness) dti:Desti_3747 (80 target-flexibility) (80 robustness) dti:Desti_3834 (0 target-flexibility) (0 robustness) dti:Desti_3894 (0 target-flexibility) (0 robustness) dti:Desti_4020 (528 target-flexibility) (157 robustness) dti:Desti_4083 (222 target-flexibility) (83 robustness) dti:Desti_4113 (634 target-flexibility) (72 robustness) dti:Desti_4116 (686 target-flexibility) (192 robustness) dti:Desti_4149 (219 target-flexibility) (63 robustness) dti:Desti_4150 (434 target-flexibility) (67 robustness) dti:Desti_4164 (790 target-flexibility) (134 robustness) dti:Desti_4182 (358 target-flexibility) (124 robustness) dti:Desti_4253 (289 target-flexibility) (73 robustness) dti:Desti_4337 (0 target-flexibility) (0 robustness) dti:Desti_4345 (0 target-flexibility) (0 robustness) dti:Desti_4384 (138 target-flexibility) (138 robustness) dti:Desti_4402 (91 target-flexibility) (91 robustness) dti:Desti_4450 (691 target-flexibility) (528 robustness) dti:Desti_4464 (158 target-flexibility) (72 robustness) dti:Desti_4547 (0 target-flexibility) (0 robustness) dti:Desti_4572 (0 target-flexibility) (0 robustness) dti:Desti_4587 (377 target-flexibility) (117 robustness) dti:Desti_4704 (239 target-flexibility) (67 robustness) dti:Desti_4705 (67 target-flexibility) (67 robustness) dti:Desti_4732 (358 target-flexibility) (124 robustness) dti:Desti_4769 (350 target-flexibility) (84 robustness) dti:Desti_4868 (691 target-flexibility) (528 robustness) dti:Desti_4903 (902 target-flexibility) (228 robustness) dti:Desti_4907 (0 target-flexibility) (0 robustness) dti:Desti_4911 (0 target-flexibility) (0 robustness) dti:Desti_4995 (0 target-flexibility) (0 robustness) dti:Desti_5141 (138 target-flexibility) (138 robustness) dti:Desti_5320 (343 target-flexibility) (180 robustness) dti:Desti_5358 (0 target-flexibility) (0 robustness) dti:Desti_5499 (350 target-flexibility) (84 robustness) dti:Desti_5539 (301 target-flexibility) (154 robustness) dti:Desti_5563 (91 target-flexibility) (91 robustness) dti:Desti_5667 (691 target-flexibility) (528 robustness) dto:TOL2_C00330 (706 target-flexibility) (173 robustness) dto:TOL2_C00560 (91 target-flexibility) (91 robustness) dto:TOL2_C02640 (528 target-flexibility) (157 robustness) dto:TOL2_C03020 (0 target-flexibility) (0 robustness) dto:TOL2_C03030 (0 target-flexibility) (0 robustness) dto:TOL2_C03360 (686 target-flexibility) (192 robustness) dto:TOL2_C03820 (659 target-flexibility) (240 robustness) dto:TOL2_C04170 (706 target-flexibility) (173 robustness) dto:TOL2_C04490 (659 target-flexibility) (240 robustness) dto:TOL2_C05070 (0 target-flexibility) (0 robustness) dto:TOL2_C05080 (0 target-flexibility) (0 robustness) dto:TOL2_C05120 (301 target-flexibility) (154 robustness) dto:TOL2_C05220 (790 target-flexibility) (134 robustness) dto:TOL2_C05370 (634 target-flexibility) (72 robustness) dto:TOL2_C07190 (841 target-flexibility) (126 robustness) dto:TOL2_C08210 (0 target-flexibility) (0 robustness) dto:TOL2_C08510 (0 target-flexibility) (0 robustness) dto:TOL2_C10040 (732 target-flexibility) (78 robustness) dto:TOL2_C10990 (358 target-flexibility) (104 robustness) dto:TOL2_C11340 (0 target-flexibility) (0 robustness) dto:TOL2_C11440 (752 target-flexibility) (76 robustness) dto:TOL2_C12360 (0 target-flexibility) (0 robustness) dto:TOL2_C13270 (691 target-flexibility) (528 robustness) dto:TOL2_C13310 (358 target-flexibility) (104 robustness) dto:TOL2_C13420 (691 target-flexibility) (528 robustness) dto:TOL2_C15720 (357 target-flexibility) (115 robustness) dto:TOL2_C15960 (706 target-flexibility) (173 robustness) dto:TOL2_C16510 (212 target-flexibility) (73 robustness) dto:TOL2_C16630 (841 target-flexibility) (126 robustness) dto:TOL2_C16640 (841 target-flexibility) (126 robustness) dto:TOL2_C17330 (924 target-flexibility) (101 robustness) dto:TOL2_C17500 (0 target-flexibility) (0 robustness) dto:TOL2_C18190 (80 target-flexibility) (80 robustness) dto:TOL2_C18400 (0 target-flexibility) (0 robustness) dto:TOL2_C18860 (80 target-flexibility) (80 robustness) dto:TOL2_C21050 (222 target-flexibility) (83 robustness) dto:TOL2_C21920 (897 target-flexibility) (71 robustness) dto:TOL2_C22060 (600 target-flexibility) (126 robustness) dto:TOL2_C22520 (634 target-flexibility) (72 robustness) dto:TOL2_C22640 (0 target-flexibility) (0 robustness) dto:TOL2_C22880 (0 target-flexibility) (0 robustness) dto:TOL2_C23200 (239 target-flexibility) (99 robustness) dto:TOL2_C23400 (0 target-flexibility) (0 robustness) dto:TOL2_C24560 (138 target-flexibility) (66 robustness) dto:TOL2_C24750 (0 target-flexibility) (0 robustness) dto:TOL2_C24800 (0 target-flexibility) (0 robustness) dto:TOL2_C26900 (0 target-flexibility) (0 robustness) dto:TOL2_C27090 (0 target-flexibility) (0 robustness) dto:TOL2_C27260 (0 target-flexibility) (0 robustness) dto:TOL2_C27460 (0 target-flexibility) (0 robustness) dto:TOL2_C27650 (0 target-flexibility) (0 robustness) dto:TOL2_C28080 (0 target-flexibility) (0 robustness) dto:TOL2_C28120 (0 target-flexibility) (0 robustness) dto:TOL2_C28470 (0 target-flexibility) (0 robustness) dto:TOL2_C28480 (0 target-flexibility) (0 robustness) dto:TOL2_C29790 (301 target-flexibility) (154 robustness) dto:TOL2_C31520 (790 target-flexibility) (134 robustness) dto:TOL2_C33600 (0 target-flexibility) (0 robustness) dto:TOL2_C35200 (0 target-flexibility) (0 robustness) dto:TOL2_C35290 (0 target-flexibility) (0 robustness) dto:TOL2_C35960 (239 target-flexibility) (99 robustness) dto:TOL2_C36220 (405 target-flexibility) (169 robustness) dto:TOL2_C37120 (0 target-flexibility) (0 robustness) dto:TOL2_C38340 (703 target-flexibility) (319 robustness) dto:TOL2_C38520 (0 target-flexibility) (0 robustness) dto:TOL2_C38530 (659 target-flexibility) (240 robustness) dto:TOL2_C38550 (703 target-flexibility) (319 robustness) dto:TOL2_C38950 (924 target-flexibility) (101 robustness) dto:TOL2_C39750 (91 target-flexibility) (91 robustness) dto:TOL2_C39790 (752 target-flexibility) (76 robustness) dto:TOL2_C39980 (600 target-flexibility) (126 robustness) dto:TOL2_C41270 (686 target-flexibility) (192 robustness) dto:TOL2_C41730 (0 target-flexibility) (0 robustness) dto:TOL2_C42790 (357 target-flexibility) (115 robustness) dto:TOL2_C42990 (732 target-flexibility) (78 robustness) dto:TOL2_C43000 (405 target-flexibility) (169 robustness) dto:TOL2_C43490 (0 target-flexibility) (0 robustness) dto:TOL2_C43570 (0 target-flexibility) (0 robustness) dvu:DVU0085 (686 target-flexibility) (192 robustness) dvu:DVU0152 (706 target-flexibility) (173 robustness) dvu:DVU0246 (706 target-flexibility) (173 robustness) dvu:DVU0283 (138 target-flexibility) (138 robustness) dvu:DVU0341 (70 target-flexibility) (70 robustness) dvu:DVU0360 (902 target-flexibility) (228 robustness) dvu:DVU0377 (138 target-flexibility) (138 robustness) dvu:DVU0470 (686 target-flexibility) (192 robustness) dvu:DVU0477 (289 target-flexibility) (73 robustness) dvu:DVU0489 (0 target-flexibility) (0 robustness) dvu:DVU0565 (600 target-flexibility) (126 robustness) dvu:DVU0626 (902 target-flexibility) (228 robustness) dvu:DVU0732 (212 target-flexibility) (73 robustness) dvu:DVU0748 (790 target-flexibility) (134 robustness) dvu:DVU0827 (0 target-flexibility) (0 robustness) dvu:DVU0841 (1385 target-flexibility) (204 robustness) dvu:DVU0951 (0 target-flexibility) (0 robustness) dvu:DVU1196 (0 target-flexibility) (0 robustness) dvu:DVU1204 (703 target-flexibility) (319 robustness) dvu:DVU1206 (659 target-flexibility) (240 robustness) dvu:DVU1350 (1169 target-flexibility) (76 robustness) dvu:DVU1360 (0 target-flexibility) (0 robustness) dvu:DVU1364 (0 target-flexibility) (0 robustness) dvu:DVU1376 (902 target-flexibility) (228 robustness) dvu:DVU1377 (902 target-flexibility) (228 robustness) dvu:DVU1453 (0 target-flexibility) (0 robustness) dvu:DVU1457 (138 target-flexibility) (138 robustness) dvu:DVU1615 (0 target-flexibility) (0 robustness) dvu:DVU1647 (239 target-flexibility) (99 robustness) dvu:DVU1693 (357 target-flexibility) (102 robustness) dvu:DVU1833 (706 target-flexibility) (173 robustness) dvu:DVU1838 (138 target-flexibility) (138 robustness) dvu:DVU1914 (841 target-flexibility) (126 robustness) dvu:DVU1927 (222 target-flexibility) (83 robustness) dvu:DVU1940 (497 target-flexibility) (186 robustness) dvu:DVU2091 (0 target-flexibility) (0 robustness) dvu:DVU2144 (600 target-flexibility) (126 robustness) dvu:DVU2250 (790 target-flexibility) (134 robustness) dvu:DVU2362 (0 target-flexibility) (0 robustness) dvu:DVU2396 (0 target-flexibility) (0 robustness) dvu:DVU2405 (0 target-flexibility) (0 robustness) dvu:DVU2530 (1041 target-flexibility) (243 robustness) dvu:DVU2552 (357 target-flexibility) (102 robustness) dvu:DVU2559 (0 target-flexibility) (0 robustness) dvu:DVU2563 (703 target-flexibility) (319 robustness) dvu:DVU2566 (239 target-flexibility) (99 robustness) dvu:DVU2673 (497 target-flexibility) (186 robustness) dvu:DVU2735 (0 target-flexibility) (0 robustness) dvu:DVU2739 (706 target-flexibility) (173 robustness) dvu:DVU2885 (0 target-flexibility) (0 robustness) dvu:DVU2905 (0 target-flexibility) (0 robustness) dvu:DVU2969 (790 target-flexibility) (134 robustness) dvu:DVU2981 (841 target-flexibility) (126 robustness) dvu:DVU2985 (434 target-flexibility) (67 robustness) dvu:DVU2990 (0 target-flexibility) (0 robustness) dvu:DVU2996 (0 target-flexibility) (0 robustness) dvu:DVU3014 (821 target-flexibility) (137 robustness) dvu:DVU3027 (0 target-flexibility) (0 robustness) dvu:DVU3114 (70 target-flexibility) (70 robustness) dvu:DVU3119 (0 target-flexibility) (0 robustness) dvu:DVU3132 (497 target-flexibility) (186 robustness) dvu:DVU3137 (659 target-flexibility) (240 robustness) dvu:DVU3168 (80 target-flexibility) (80 robustness) dvu:DVU3214 (706 target-flexibility) (173 robustness) dvu:DVU3223 (1385 target-flexibility) (204 robustness) dvu:DVU3237 (706 target-flexibility) (173 robustness) dvu:DVU3253 (0 target-flexibility) (0 robustness) dvu:DVU3293 (902 target-flexibility) (228 robustness) dvu:DVU3356 (0 target-flexibility) (0 robustness) dvu:DVUA0073 (821 target-flexibility) (137 robustness) gao:A2G06_01250 (1108 target-flexibility) (319 robustness) gao:A2G06_02140 (659 target-flexibility) (240 robustness) gao:A2G06_03585 (1169 target-flexibility) (76 robustness) gao:A2G06_05615 (686 target-flexibility) (192 robustness) gao:A2G06_05630 (686 target-flexibility) (192 robustness) gao:A2G06_05670 (0 target-flexibility) (0 robustness) gao:A2G06_05980 (71 target-flexibility) (71 robustness) gao:A2G06_06115 (0 target-flexibility) (0 robustness) gao:A2G06_06120 (0 target-flexibility) (0 robustness) gao:A2G06_06270 (0 target-flexibility) (0 robustness) gao:A2G06_06620 (0 target-flexibility) (0 robustness) gao:A2G06_06650 (212 target-flexibility) (73 robustness) gao:A2G06_07085 (0 target-flexibility) (0 robustness) gao:A2G06_07325 (841 target-flexibility) (126 robustness) gao:A2G06_07620 (0 target-flexibility) (0 robustness) gao:A2G06_07920 (841 target-flexibility) (126 robustness) gao:A2G06_08130 (1169 target-flexibility) (76 robustness) gao:A2G06_08260 (0 target-flexibility) (0 robustness) gao:A2G06_08985 (659 target-flexibility) (240 robustness) gao:A2G06_08995 (1108 target-flexibility) (319 robustness) gao:A2G06_09115 (0 target-flexibility) (0 robustness) gao:A2G06_09675 (752 target-flexibility) (76 robustness) gao:A2G06_10540 (897 target-flexibility) (71 robustness) gao:A2G06_10625 (1385 target-flexibility) (204 robustness) gao:A2G06_11490 (1385 target-flexibility) (204 robustness) gao:A2G06_12745 (0 target-flexibility) (0 robustness) gao:A2G06_13050 (0 target-flexibility) (0 robustness) gao:A2G06_13760 (1041 target-flexibility) (243 robustness) gao:A2G06_13765 (1041 target-flexibility) (243 robustness) gao:A2G06_14560 (0 target-flexibility) (0 robustness) gao:A2G06_14565 (0 target-flexibility) (0 robustness) gao:A2G06_14765 (222 target-flexibility) (83 robustness) gao:A2G06_15675 (138 target-flexibility) (66 robustness) gao:A2G06_16175 (1041 target-flexibility) (243 robustness) gbm:Gbem_0212 (691 target-flexibility) (528 robustness) gbm:Gbem_0259 (0 target-flexibility) (0 robustness) gbm:Gbem_0260 (0 target-flexibility) (0 robustness) gbm:Gbem_0279 (1041 target-flexibility) (243 robustness) gbm:Gbem_0280 (1041 target-flexibility) (243 robustness) gbm:Gbem_0486 (239 target-flexibility) (67 robustness) gbm:Gbem_0487 (67 target-flexibility) (67 robustness) gbm:Gbem_0493 (76 target-flexibility) (76 robustness) gbm:Gbem_0564 (0 target-flexibility) (0 robustness) gbm:Gbem_0567 (0 target-flexibility) (0 robustness) gbm:Gbem_0635 (350 target-flexibility) (189 robustness) gbm:Gbem_0751 (0 target-flexibility) (0 robustness) gbm:Gbem_0823 (150 target-flexibility) (76 robustness) gbm:Gbem_0836 (71 target-flexibility) (71 robustness) gbm:Gbem_0861 (0 target-flexibility) (0 robustness) gbm:Gbem_0909 (166 target-flexibility) (99 robustness) gbm:Gbem_0910 (166 target-flexibility) (99 robustness) gbm:Gbem_1081 (821 target-flexibility) (137 robustness) gbm:Gbem_1258 (1169 target-flexibility) (76 robustness) gbm:Gbem_1265 (841 target-flexibility) (126 robustness) gbm:Gbem_1341 (175 target-flexibility) (96 robustness) gbm:Gbem_1348 (70 target-flexibility) (70 robustness) gbm:Gbem_1349 (0 target-flexibility) (0 robustness) gbm:Gbem_1354 (700 target-flexibility) (89 robustness) gbm:Gbem_1379 (1041 target-flexibility) (243 robustness) gbm:Gbem_1436 (700 target-flexibility) (89 robustness) gbm:Gbem_1464 (0 target-flexibility) (0 robustness) gbm:Gbem_1465 (0 target-flexibility) (0 robustness) gbm:Gbem_1531 (212 target-flexibility) (73 robustness) gbm:Gbem_1554 (150 target-flexibility) (76 robustness) gbm:Gbem_1571 (0 target-flexibility) (0 robustness) gbm:Gbem_1615 (821 target-flexibility) (137 robustness) gbm:Gbem_1629 (0 target-flexibility) (0 robustness) gbm:Gbem_1630 (0 target-flexibility) (0 robustness) gbm:Gbem_1652 (924 target-flexibility) (101 robustness) gbm:Gbem_1725 (175 target-flexibility) (96 robustness) gbm:Gbem_1778 (821 target-flexibility) (137 robustness) gbm:Gbem_1896 (897 target-flexibility) (71 robustness) gbm:Gbem_1958 (686 target-flexibility) (192 robustness) gbm:Gbem_1983 (528 target-flexibility) (157 robustness) gbm:Gbem_2051 (0 target-flexibility) (0 robustness) gbm:Gbem_2125 (0 target-flexibility) (0 robustness) gbm:Gbem_2149 (0 target-flexibility) (0 robustness) gbm:Gbem_2173 (262 target-flexibility) (86 robustness) gbm:Gbem_2184 (0 target-flexibility) (0 robustness) gbm:Gbem_2192 (0 target-flexibility) (0 robustness) gbm:Gbem_2216 (0 target-flexibility) (0 robustness) gbm:Gbem_2235 (0 target-flexibility) (0 robustness) gbm:Gbem_2258 (262 target-flexibility) (86 robustness) gbm:Gbem_2272 (700 target-flexibility) (89 robustness) gbm:Gbem_2273 (0 target-flexibility) (0 robustness) gbm:Gbem_2274 (70 target-flexibility) (70 robustness) gbm:Gbem_2336 (600 target-flexibility) (126 robustness) gbm:Gbem_2352 (0 target-flexibility) (0 robustness) gbm:Gbem_2353 (0 target-flexibility) (0 robustness) gbm:Gbem_2446 (0 target-flexibility) (0 robustness) gbm:Gbem_2561 (139 target-flexibility) (139 robustness) gbm:Gbem_2692 (0 target-flexibility) (0 robustness) gbm:Gbem_2742 (841 target-flexibility) (126 robustness) gbm:Gbem_2797 (0 target-flexibility) (0 robustness) gbm:Gbem_2828 (0 target-flexibility) (0 robustness) gbm:Gbem_2859 (239 target-flexibility) (99 robustness) gbm:Gbem_2903 (752 target-flexibility) (76 robustness) gbm:Gbem_2906 (0 target-flexibility) (0 robustness) gbm:Gbem_2980 (350 target-flexibility) (189 robustness) gbm:Gbem_3108 (1108 target-flexibility) (319 robustness) gbm:Gbem_3162 (0 target-flexibility) (0 robustness) gbm:Gbem_3163 (528 target-flexibility) (157 robustness) gbm:Gbem_3180 (76 target-flexibility) (76 robustness) gbm:Gbem_3205 (691 target-flexibility) (528 robustness) gbm:Gbem_3222 (0 target-flexibility) (0 robustness) gbm:Gbem_3223 (0 target-flexibility) (0 robustness) gbm:Gbem_3321 (686 target-flexibility) (192 robustness) gbm:Gbem_3345 (0 target-flexibility) (0 robustness) gbm:Gbem_3346 (0 target-flexibility) (0 robustness) gbm:Gbem_3362 (1169 target-flexibility) (76 robustness) gbm:Gbem_3400 (0 target-flexibility) (0 robustness) gbm:Gbem_3463 (91 target-flexibility) (91 robustness) gbm:Gbem_3530 (0 target-flexibility) (0 robustness) gbm:Gbem_3637 (138 target-flexibility) (66 robustness) gbm:Gbem_3650 (222 target-flexibility) (83 robustness) gbm:Gbem_3700 (0 target-flexibility) (0 robustness) gbm:Gbem_3701 (0 target-flexibility) (0 robustness) gbm:Gbem_3783 (139 target-flexibility) (139 robustness) gbm:Gbem_3789 (600 target-flexibility) (126 robustness) gbm:Gbem_3809 (91 target-flexibility) (91 robustness) gbm:Gbem_3820 (0 target-flexibility) (0 robustness) gbm:Gbem_3905 (924 target-flexibility) (101 robustness) gbm:Gbem_3927 (80 target-flexibility) (80 robustness) gbm:Gbem_3995 (1108 target-flexibility) (319 robustness) gbm:Gbem_4020 (0 target-flexibility) (0 robustness) gbm:Gbem_4055 (239 target-flexibility) (99 robustness) geb:GM18_0169 (691 target-flexibility) (528 robustness) geb:GM18_0287 (0 target-flexibility) (0 robustness) geb:GM18_0288 (0 target-flexibility) (0 robustness) geb:GM18_0316 (1041 target-flexibility) (243 robustness) geb:GM18_0317 (1041 target-flexibility) (243 robustness) geb:GM18_0559 (0 target-flexibility) (0 robustness) geb:GM18_0634 (91 target-flexibility) (91 robustness) geb:GM18_0699 (0 target-flexibility) (0 robustness) geb:GM18_0719 (150 target-flexibility) (76 robustness) geb:GM18_0730 (71 target-flexibility) (71 robustness) geb:GM18_0750 (0 target-flexibility) (0 robustness) geb:GM18_0779 (301 target-flexibility) (154 robustness) geb:GM18_0809 (166 target-flexibility) (99 robustness) geb:GM18_0810 (166 target-flexibility) (99 robustness) geb:GM18_0958 (790 target-flexibility) (134 robustness) geb:GM18_1054 (734 target-flexibility) (110 robustness) geb:GM18_1091 (0 target-flexibility) (0 robustness) geb:GM18_1116 (1169 target-flexibility) (76 robustness) geb:GM18_1123 (841 target-flexibility) (126 robustness) geb:GM18_1206 (0 target-flexibility) (0 robustness) geb:GM18_1211 (700 target-flexibility) (89 robustness) geb:GM18_1241 (1041 target-flexibility) (243 robustness) geb:GM18_1366 (212 target-flexibility) (73 robustness) geb:GM18_1389 (150 target-flexibility) (76 robustness) geb:GM18_1403 (358 target-flexibility) (124 robustness) geb:GM18_1436 (0 target-flexibility) (0 robustness) geb:GM18_1438 (821 target-flexibility) (137 robustness) geb:GM18_1442 (0 target-flexibility) (0 robustness) geb:GM18_1443 (0 target-flexibility) (0 robustness) geb:GM18_1454 (821 target-flexibility) (137 robustness) geb:GM18_1602 (0 target-flexibility) (0 robustness) geb:GM18_1672 (821 target-flexibility) (137 robustness) geb:GM18_1720 (897 target-flexibility) (71 robustness) geb:GM18_1836 (358 target-flexibility) (124 robustness) geb:GM18_1893 (600 target-flexibility) (126 robustness) geb:GM18_1956 (0 target-flexibility) (0 robustness) geb:GM18_1958 (700 target-flexibility) (89 robustness) geb:GM18_1971 (262 target-flexibility) (86 robustness) geb:GM18_1990 (0 target-flexibility) (0 robustness) geb:GM18_2013 (0 target-flexibility) (0 robustness) geb:GM18_2054 (0 target-flexibility) (0 robustness) geb:GM18_2062 (0 target-flexibility) (0 robustness) geb:GM18_2068 (262 target-flexibility) (86 robustness) geb:GM18_2111 (0 target-flexibility) (0 robustness) geb:GM18_2157 (0 target-flexibility) (0 robustness) geb:GM18_2226 (528 target-flexibility) (157 robustness) geb:GM18_2264 (686 target-flexibility) (192 robustness) geb:GM18_2304 (0 target-flexibility) (0 robustness) geb:GM18_2560 (0 target-flexibility) (0 robustness) geb:GM18_2608 (841 target-flexibility) (126 robustness) geb:GM18_2665 (0 target-flexibility) (0 robustness) geb:GM18_2719 (239 target-flexibility) (99 robustness) geb:GM18_2739 (0 target-flexibility) (0 robustness) geb:GM18_2759 (0 target-flexibility) (0 robustness) geb:GM18_2790 (752 target-flexibility) (76 robustness) geb:GM18_2793 (0 target-flexibility) (0 robustness) geb:GM18_3075 (703 target-flexibility) (319 robustness) geb:GM18_3077 (659 target-flexibility) (240 robustness) geb:GM18_3079 (1108 target-flexibility) (319 robustness) geb:GM18_3132 (528 target-flexibility) (157 robustness) geb:GM18_3185 (76 target-flexibility) (76 robustness) geb:GM18_3247 (691 target-flexibility) (528 robustness) geb:GM18_3257 (0 target-flexibility) (0 robustness) geb:GM18_3274 (0 target-flexibility) (0 robustness) geb:GM18_3275 (0 target-flexibility) (0 robustness) geb:GM18_3400 (686 target-flexibility) (192 robustness) geb:GM18_3424 (0 target-flexibility) (0 robustness) geb:GM18_3441 (1169 target-flexibility) (76 robustness) geb:GM18_3547 (734 target-flexibility) (110 robustness) geb:GM18_3598 (0 target-flexibility) (0 robustness) geb:GM18_3789 (0 target-flexibility) (0 robustness) geb:GM18_3792 (0 target-flexibility) (0 robustness) geb:GM18_3827 (301 target-flexibility) (154 robustness) geb:GM18_3885 (76 target-flexibility) (76 robustness) geb:GM18_3889 (140 target-flexibility) (71 robustness) geb:GM18_3891 (67 target-flexibility) (67 robustness) geb:GM18_3892 (239 target-flexibility) (67 robustness) geb:GM18_3980 (0 target-flexibility) (0 robustness) geb:GM18_4050 (703 target-flexibility) (319 robustness) geb:GM18_4055 (703 target-flexibility) (319 robustness) geb:GM18_4063 (0 target-flexibility) (0 robustness) geb:GM18_4066 (703 target-flexibility) (319 robustness) geb:GM18_4069 (659 target-flexibility) (240 robustness) geb:GM18_4095 (138 target-flexibility) (66 robustness) geb:GM18_4108 (222 target-flexibility) (83 robustness) geb:GM18_4149 (0 target-flexibility) (0 robustness) geb:GM18_4150 (0 target-flexibility) (0 robustness) geb:GM18_4151 (0 target-flexibility) (0 robustness) geb:GM18_4171 (0 target-flexibility) (0 robustness) geb:GM18_4219 (600 target-flexibility) (126 robustness) geb:GM18_4239 (91 target-flexibility) (91 robustness) geb:GM18_4250 (0 target-flexibility) (0 robustness) geb:GM18_4391 (80 target-flexibility) (80 robustness) geb:GM18_4453 (1108 target-flexibility) (319 robustness) geb:GM18_4463 (0 target-flexibility) (0 robustness) geb:GM18_4466 (0 target-flexibility) (0 robustness) geb:GM18_4516 (239 target-flexibility) (99 robustness) gem:GM21_0195 (691 target-flexibility) (528 robustness) gem:GM21_0244 (0 target-flexibility) (0 robustness) gem:GM21_0245 (0 target-flexibility) (0 robustness) gem:GM21_0264 (1041 target-flexibility) (243 robustness) gem:GM21_0265 (1041 target-flexibility) (243 robustness) gem:GM21_0503 (239 target-flexibility) (67 robustness) gem:GM21_0506 (140 target-flexibility) (71 robustness) gem:GM21_0510 (76 target-flexibility) (76 robustness) gem:GM21_0577 (0 target-flexibility) (0 robustness) gem:GM21_0580 (0 target-flexibility) (0 robustness) gem:GM21_0718 (323 target-flexibility) (101 robustness) gem:GM21_0766 (0 target-flexibility) (0 robustness) gem:GM21_0883 (1169 target-flexibility) (76 robustness) gem:GM21_0899 (0 target-flexibility) (0 robustness) gem:GM21_0900 (0 target-flexibility) (0 robustness) gem:GM21_0925 (686 target-flexibility) (192 robustness) gem:GM21_1040 (0 target-flexibility) (0 robustness) gem:GM21_1041 (0 target-flexibility) (0 robustness) gem:GM21_1080 (76 target-flexibility) (76 robustness) gem:GM21_1096 (528 target-flexibility) (157 robustness) gem:GM21_1097 (0 target-flexibility) (0 robustness) gem:GM21_1154 (1108 target-flexibility) (319 robustness) gem:GM21_1322 (752 target-flexibility) (76 robustness) gem:GM21_1355 (239 target-flexibility) (99 robustness) gem:GM21_1385 (0 target-flexibility) (0 robustness) gem:GM21_1413 (0 target-flexibility) (0 robustness) gem:GM21_1499 (841 target-flexibility) (126 robustness) gem:GM21_1667 (139 target-flexibility) (139 robustness) gem:GM21_1771 (0 target-flexibility) (0 robustness) gem:GM21_1884 (600 target-flexibility) (126 robustness) gem:GM21_1949 (70 target-flexibility) (70 robustness) gem:GM21_1950 (0 target-flexibility) (0 robustness) gem:GM21_1951 (700 target-flexibility) (89 robustness) gem:GM21_1966 (262 target-flexibility) (86 robustness) gem:GM21_1992 (0 target-flexibility) (0 robustness) gem:GM21_2011 (0 target-flexibility) (0 robustness) gem:GM21_2035 (0 target-flexibility) (0 robustness) gem:GM21_2043 (0 target-flexibility) (0 robustness) gem:GM21_2072 (0 target-flexibility) (0 robustness) gem:GM21_2166 (0 target-flexibility) (0 robustness) gem:GM21_2312 (897 target-flexibility) (71 robustness) gem:GM21_2457 (139 target-flexibility) (72 robustness) gem:GM21_2469 (821 target-flexibility) (137 robustness) gem:GM21_2561 (924 target-flexibility) (101 robustness) gem:GM21_2662 (150 target-flexibility) (76 robustness) gem:GM21_2685 (212 target-flexibility) (73 robustness) gem:GM21_2818 (700 target-flexibility) (89 robustness) gem:GM21_2903 (1041 target-flexibility) (243 robustness) gem:GM21_3025 (1169 target-flexibility) (76 robustness) gem:GM21_3529 (91 target-flexibility) (91 robustness) gem:GM21_3795 (0 target-flexibility) (0 robustness) geo:Geob_0099 (659 target-flexibility) (240 robustness) geo:Geob_0150 (0 target-flexibility) (0 robustness) geo:Geob_0247 (0 target-flexibility) (0 robustness) geo:Geob_0248 (0 target-flexibility) (0 robustness) geo:Geob_0284 (0 target-flexibility) (0 robustness) geo:Geob_0378 (691 target-flexibility) (528 robustness) geo:Geob_0392 (222 target-flexibility) (83 robustness) geo:Geob_0461 (80 target-flexibility) (80 robustness) geo:Geob_0514 (924 target-flexibility) (101 robustness) geo:Geob_0532 (0 target-flexibility) (0 robustness) geo:Geob_0543 (91 target-flexibility) (91 robustness) geo:Geob_0666 (1041 target-flexibility) (243 robustness) geo:Geob_0667 (1041 target-flexibility) (243 robustness) geo:Geob_0692 (0 target-flexibility) (0 robustness) geo:Geob_0693 (0 target-flexibility) (0 robustness) geo:Geob_0761 (0 target-flexibility) (0 robustness) geo:Geob_0762 (0 target-flexibility) (0 robustness) geo:Geob_0775 (239 target-flexibility) (67 robustness) geo:Geob_0776 (67 target-flexibility) (67 robustness) geo:Geob_0778 (140 target-flexibility) (71 robustness) geo:Geob_0781 (70 target-flexibility) (70 robustness) geo:Geob_0805 (0 target-flexibility) (0 robustness) geo:Geob_0952 (350 target-flexibility) (189 robustness) geo:Geob_1002 (1041 target-flexibility) (243 robustness) geo:Geob_1062 (0 target-flexibility) (0 robustness) geo:Geob_1088 (0 target-flexibility) (0 robustness) geo:Geob_1123 (138 target-flexibility) (66 robustness) geo:Geob_1129 (239 target-flexibility) (99 robustness) geo:Geob_1143 (239 target-flexibility) (99 robustness) geo:Geob_1167 (600 target-flexibility) (126 robustness) geo:Geob_1333 (0 target-flexibility) (0 robustness) geo:Geob_1367 (1041 target-flexibility) (243 robustness) geo:Geob_1368 (1041 target-flexibility) (243 robustness) geo:Geob_1403 (528 target-flexibility) (157 robustness) geo:Geob_1417 (91 target-flexibility) (91 robustness) geo:Geob_1420 (64 target-flexibility) (64 robustness) geo:Geob_1439 (0 target-flexibility) (0 robustness) geo:Geob_1458 (0 target-flexibility) (0 robustness) geo:Geob_1504 (841 target-flexibility) (126 robustness) geo:Geob_1550 (350 target-flexibility) (189 robustness) geo:Geob_1637 (0 target-flexibility) (0 robustness) geo:Geob_1647 (0 target-flexibility) (0 robustness) geo:Geob_1656 (175 target-flexibility) (96 robustness) geo:Geob_1753 (0 target-flexibility) (0 robustness) geo:Geob_1870 (0 target-flexibility) (0 robustness) geo:Geob_1910 (659 target-flexibility) (240 robustness) geo:Geob_1911 (703 target-flexibility) (319 robustness) geo:Geob_1980 (358 target-flexibility) (124 robustness) geo:Geob_2094 (71 target-flexibility) (71 robustness) geo:Geob_2134 (0 target-flexibility) (0 robustness) geo:Geob_2151 (691 target-flexibility) (528 robustness) geo:Geob_2171 (0 target-flexibility) (0 robustness) geo:Geob_2241 (175 target-flexibility) (96 robustness) geo:Geob_2295 (64 target-flexibility) (64 robustness) geo:Geob_2315 (64 target-flexibility) (64 robustness) geo:Geob_2459 (528 target-flexibility) (157 robustness) geo:Geob_2507 (358 target-flexibility) (124 robustness) geo:Geob_2508 (64 target-flexibility) (64 robustness) geo:Geob_2526 (358 target-flexibility) (124 robustness) geo:Geob_2530 (528 target-flexibility) (157 robustness) geo:Geob_2612 (1108 target-flexibility) (319 robustness) geo:Geob_2614 (659 target-flexibility) (240 robustness) geo:Geob_2616 (703 target-flexibility) (319 robustness) geo:Geob_2629 (1169 target-flexibility) (76 robustness) geo:Geob_2661 (752 target-flexibility) (76 robustness) geo:Geob_2796 (0 target-flexibility) (0 robustness) geo:Geob_2804 (0 target-flexibility) (0 robustness) geo:Geob_2897 (600 target-flexibility) (126 robustness) geo:Geob_2923 (0 target-flexibility) (0 robustness) geo:Geob_2938 (841 target-flexibility) (126 robustness) geo:Geob_3010 (0 target-flexibility) (0 robustness) geo:Geob_3049 (358 target-flexibility) (124 robustness) geo:Geob_3082 (212 target-flexibility) (73 robustness) geo:Geob_3264 (897 target-flexibility) (71 robustness) geo:Geob_3462 (0 target-flexibility) (0 robustness) geo:Geob_3549 (924 target-flexibility) (101 robustness) geo:Geob_3651 (166 target-flexibility) (99 robustness) geo:Geob_3652 (166 target-flexibility) (99 robustness) geo:Geob_3664 (1169 target-flexibility) (76 robustness) geo:Geob_3708 (1108 target-flexibility) (319 robustness) glo:Glov_0210 (0 target-flexibility) (0 robustness) glo:Glov_0365 (691 target-flexibility) (528 robustness) glo:Glov_0418 (1108 target-flexibility) (319 robustness) glo:Glov_0474 (0 target-flexibility) (0 robustness) glo:Glov_0479 (0 target-flexibility) (0 robustness) glo:Glov_0555 (0 target-flexibility) (0 robustness) glo:Glov_0584 (357 target-flexibility) (102 robustness) glo:Glov_0674 (67 target-flexibility) (67 robustness) glo:Glov_0675 (239 target-flexibility) (67 robustness) glo:Glov_0692 (0 target-flexibility) (0 robustness) glo:Glov_0757 (71 target-flexibility) (71 robustness) glo:Glov_0763 (339 target-flexibility) (98 robustness) glo:Glov_0786 (902 target-flexibility) (228 robustness) glo:Glov_0795 (1041 target-flexibility) (243 robustness) glo:Glov_0796 (1041 target-flexibility) (243 robustness) glo:Glov_0808 (796 target-flexibility) (85 robustness) glo:Glov_0823 (0 target-flexibility) (0 robustness) glo:Glov_0835 (358 target-flexibility) (124 robustness) glo:Glov_0892 (700 target-flexibility) (89 robustness) glo:Glov_0893 (0 target-flexibility) (0 robustness) glo:Glov_0909 (0 target-flexibility) (0 robustness) glo:Glov_0981 (222 target-flexibility) (83 robustness) glo:Glov_1018 (0 target-flexibility) (0 robustness) glo:Glov_1019 (0 target-flexibility) (0 robustness) glo:Glov_1024 (528 target-flexibility) (157 robustness) glo:Glov_1067 (0 target-flexibility) (0 robustness) glo:Glov_1099 (76 target-flexibility) (76 robustness) glo:Glov_1157 (0 target-flexibility) (0 robustness) glo:Glov_1159 (700 target-flexibility) (89 robustness) glo:Glov_1211 (686 target-flexibility) (192 robustness) glo:Glov_1213 (686 target-flexibility) (192 robustness) glo:Glov_1512 (796 target-flexibility) (85 robustness) glo:Glov_1531 (0 target-flexibility) (0 robustness) glo:Glov_1607 (358 target-flexibility) (124 robustness) glo:Glov_1616 (600 target-flexibility) (126 robustness) glo:Glov_1622 (752 target-flexibility) (76 robustness) glo:Glov_1658 (0 target-flexibility) (0 robustness) glo:Glov_1768 (1385 target-flexibility) (204 robustness) glo:Glov_1858 (0 target-flexibility) (0 robustness) glo:Glov_1910 (0 target-flexibility) (0 robustness) glo:Glov_1934 (703 target-flexibility) (319 robustness) glo:Glov_1936 (659 target-flexibility) (240 robustness) glo:Glov_1937 (339 target-flexibility) (98 robustness) glo:Glov_1939 (1108 target-flexibility) (319 robustness) glo:Glov_1947 (691 target-flexibility) (528 robustness) glo:Glov_2038 (841 target-flexibility) (126 robustness) glo:Glov_2085 (897 target-flexibility) (71 robustness) glo:Glov_2116 (0 target-flexibility) (0 robustness) glo:Glov_2128 (405 target-flexibility) (70 robustness) glo:Glov_2182 (1169 target-flexibility) (76 robustness) glo:Glov_2193 (703 target-flexibility) (319 robustness) glo:Glov_2194 (659 target-flexibility) (240 robustness) glo:Glov_2235 (1169 target-flexibility) (76 robustness) glo:Glov_2247 (0 target-flexibility) (0 robustness) glo:Glov_2405 (0 target-flexibility) (0 robustness) glo:Glov_2418 (1108 target-flexibility) (319 robustness) glo:Glov_2503 (902 target-flexibility) (228 robustness) glo:Glov_2508 (0 target-flexibility) (0 robustness) glo:Glov_2538 (212 target-flexibility) (73 robustness) glo:Glov_2562 (600 target-flexibility) (126 robustness) glo:Glov_2600 (1385 target-flexibility) (204 robustness) glo:Glov_2713 (76 target-flexibility) (76 robustness) glo:Glov_2764 (91 target-flexibility) (91 robustness) glo:Glov_2804 (1041 target-flexibility) (243 robustness) glo:Glov_2962 (0 target-flexibility) (0 robustness) glo:Glov_3068 (528 target-flexibility) (157 robustness) glo:Glov_3139 (80 target-flexibility) (80 robustness) glo:Glov_3149 (138 target-flexibility) (66 robustness) glo:Glov_3217 (350 target-flexibility) (189 robustness) glo:Glov_3322 (0 target-flexibility) (0 robustness) glo:Glov_3325 (841 target-flexibility) (126 robustness) glo:Glov_3365 (0 target-flexibility) (0 robustness) glo:Glov_3399 (0 target-flexibility) (0 robustness) glo:Glov_3457 (0 target-flexibility) (0 robustness) glo:Glov_3585 (0 target-flexibility) (0 robustness) glo:Glov_3634 (350 target-flexibility) (189 robustness) glo:Glov_3677 (91 target-flexibility) (91 robustness) glo:Glov_3718 (0 target-flexibility) (0 robustness) gme:Gmet_0065 (0 target-flexibility) (0 robustness) gme:Gmet_0104 (796 target-flexibility) (85 robustness) gme:Gmet_0178 (1041 target-flexibility) (243 robustness) gme:Gmet_0205 (138 target-flexibility) (66 robustness) gme:Gmet_0219 (239 target-flexibility) (99 robustness) gme:Gmet_0264 (528 target-flexibility) (157 robustness) gme:Gmet_0301 (700 target-flexibility) (89 robustness) gme:Gmet_0336 (0 target-flexibility) (0 robustness) gme:Gmet_0337 (700 target-flexibility) (89 robustness) gme:Gmet_0351 (222 target-flexibility) (83 robustness) gme:Gmet_0388 (0 target-flexibility) (0 robustness) gme:Gmet_0389 (0 target-flexibility) (0 robustness) gme:Gmet_0407 (239 target-flexibility) (67 robustness) gme:Gmet_0408 (67 target-flexibility) (67 robustness) gme:Gmet_0410 (140 target-flexibility) (71 robustness) gme:Gmet_0413 (70 target-flexibility) (70 robustness) gme:Gmet_0471 (91 target-flexibility) (91 robustness) gme:Gmet_0551 (1041 target-flexibility) (243 robustness) gme:Gmet_0552 (1041 target-flexibility) (243 robustness) gme:Gmet_0661 (405 target-flexibility) (169 robustness) gme:Gmet_0707 (0 target-flexibility) (0 robustness) gme:Gmet_0729 (0 target-flexibility) (0 robustness) gme:Gmet_0730 (0 target-flexibility) (0 robustness) gme:Gmet_0770 (706 target-flexibility) (173 robustness) gme:Gmet_0872 (358 target-flexibility) (124 robustness) gme:Gmet_0884 (350 target-flexibility) (189 robustness) gme:Gmet_0940 (0 target-flexibility) (0 robustness) gme:Gmet_0950 (0 target-flexibility) (0 robustness) gme:Gmet_0956 (212 target-flexibility) (73 robustness) gme:Gmet_0992 (358 target-flexibility) (124 robustness) gme:Gmet_1016 (262 target-flexibility) (86 robustness) gme:Gmet_1038 (0 target-flexibility) (0 robustness) gme:Gmet_1124 (924 target-flexibility) (101 robustness) gme:Gmet_1211 (600 target-flexibility) (126 robustness) gme:Gmet_1265 (841 target-flexibility) (126 robustness) gme:Gmet_1297 (734 target-flexibility) (110 robustness) gme:Gmet_1357 (752 target-flexibility) (76 robustness) gme:Gmet_1469 (0 target-flexibility) (0 robustness) gme:Gmet_1486 (0 target-flexibility) (0 robustness) gme:Gmet_1487 (796 target-flexibility) (85 robustness) gme:Gmet_1558 (528 target-flexibility) (157 robustness) gme:Gmet_1580 (0 target-flexibility) (0 robustness) gme:Gmet_1599 (1108 target-flexibility) (319 robustness) gme:Gmet_1601 (659 target-flexibility) (240 robustness) gme:Gmet_1603 (703 target-flexibility) (319 robustness) gme:Gmet_1604 (486 target-flexibility) (89 robustness) gme:Gmet_1613 (0 target-flexibility) (0 robustness) gme:Gmet_1694 (659 target-flexibility) (240 robustness) gme:Gmet_1695 (703 target-flexibility) (319 robustness) gme:Gmet_1769 (897 target-flexibility) (71 robustness) gme:Gmet_1774 (405 target-flexibility) (169 robustness) gme:Gmet_1804 (0 target-flexibility) (0 robustness) gme:Gmet_1818 (0 target-flexibility) (0 robustness) gme:Gmet_1825 (0 target-flexibility) (0 robustness) gme:Gmet_1879 (841 target-flexibility) (126 robustness) gme:Gmet_1896 (323 target-flexibility) (101 robustness) gme:Gmet_1910 (734 target-flexibility) (110 robustness) gme:Gmet_1934 (1169 target-flexibility) (76 robustness) gme:Gmet_1946 (600 target-flexibility) (126 robustness) gme:Gmet_1954 (854 target-flexibility) (204 robustness) gme:Gmet_2007 (0 target-flexibility) (0 robustness) gme:Gmet_2019 (239 target-flexibility) (99 robustness) gme:Gmet_2024 (821 target-flexibility) (137 robustness) gme:Gmet_2059 (659 target-flexibility) (240 robustness) gme:Gmet_2068 (0 target-flexibility) (0 robustness) gme:Gmet_2069 (0 target-flexibility) (0 robustness) gme:Gmet_2095 (700 target-flexibility) (89 robustness) gme:Gmet_2101 (706 target-flexibility) (173 robustness) gme:Gmet_2172 (821 target-flexibility) (137 robustness) gme:Gmet_2229 (0 target-flexibility) (0 robustness) gme:Gmet_2260 (0 target-flexibility) (0 robustness) gme:Gmet_2261 (0 target-flexibility) (0 robustness) gme:Gmet_2300 (0 target-flexibility) (0 robustness) gme:Gmet_2319 (691 target-flexibility) (528 robustness) gme:Gmet_2329 (0 target-flexibility) (0 robustness) gme:Gmet_2330 (0 target-flexibility) (0 robustness) gme:Gmet_2340 (790 target-flexibility) (134 robustness) gme:Gmet_2353 (139 target-flexibility) (66 robustness) gme:Gmet_2360 (71 target-flexibility) (71 robustness) gme:Gmet_2473 (0 target-flexibility) (0 robustness) gme:Gmet_2482 (686 target-flexibility) (192 robustness) gme:Gmet_2493 (686 target-flexibility) (192 robustness) gme:Gmet_2567 (139 target-flexibility) (66 robustness) gme:Gmet_2621 (486 target-flexibility) (89 robustness) gme:Gmet_2689 (924 target-flexibility) (101 robustness) gme:Gmet_2763 (262 target-flexibility) (86 robustness) gme:Gmet_2764 (323 target-flexibility) (101 robustness) gme:Gmet_2767 (0 target-flexibility) (0 robustness) gme:Gmet_2822 (1169 target-flexibility) (76 robustness) gme:Gmet_2910 (91 target-flexibility) (91 robustness) gme:Gmet_2911 (854 target-flexibility) (204 robustness) gme:Gmet_2988 (528 target-flexibility) (157 robustness) gme:Gmet_3078 (0 target-flexibility) (0 robustness) gme:Gmet_3159 (0 target-flexibility) (0 robustness) gme:Gmet_3175 (0 target-flexibility) (0 robustness) gme:Gmet_3272 (1108 target-flexibility) (319 robustness) gme:Gmet_3339 (350 target-flexibility) (189 robustness) gme:Gmet_3356 (80 target-flexibility) (80 robustness) gme:Gmet_3422 (691 target-flexibility) (528 robustness) gpi:GPICK_00285 (405 target-flexibility) (70 robustness) gpi:GPICK_00320 (0 target-flexibility) (0 robustness) gpi:GPICK_01105 (175 target-flexibility) (96 robustness) gpi:GPICK_01155 (358 target-flexibility) (124 robustness) gpi:GPICK_01260 (528 target-flexibility) (157 robustness) gpi:GPICK_01450 (138 target-flexibility) (66 robustness) gpi:GPICK_01855 (0 target-flexibility) (0 robustness) gpi:GPICK_02005 (528 target-flexibility) (157 robustness) gpi:GPICK_02075 (222 target-flexibility) (83 robustness) gpi:GPICK_02235 (0 target-flexibility) (0 robustness) gpi:GPICK_02240 (0 target-flexibility) (0 robustness) gpi:GPICK_02335 (239 target-flexibility) (67 robustness) gpi:GPICK_02340 (67 target-flexibility) (67 robustness) gpi:GPICK_02630 (91 target-flexibility) (91 robustness) gpi:GPICK_02895 (1041 target-flexibility) (243 robustness) gpi:GPICK_02900 (1041 target-flexibility) (243 robustness) gpi:GPICK_03195 (166 target-flexibility) (99 robustness) gpi:GPICK_03200 (166 target-flexibility) (99 robustness) gpi:GPICK_03805 (358 target-flexibility) (124 robustness) gpi:GPICK_03840 (64 target-flexibility) (64 robustness) gpi:GPICK_04075 (1169 target-flexibility) (76 robustness) gpi:GPICK_04525 (0 target-flexibility) (0 robustness) gpi:GPICK_04615 (924 target-flexibility) (101 robustness) gpi:GPICK_04625 (841 target-flexibility) (126 robustness) gpi:GPICK_05040 (734 target-flexibility) (110 robustness) gpi:GPICK_05075 (0 target-flexibility) (0 robustness) gpi:GPICK_05080 (0 target-flexibility) (0 robustness) gpi:GPICK_05085 (1385 target-flexibility) (204 robustness) gpi:GPICK_05200 (64 target-flexibility) (64 robustness) gpi:GPICK_05385 (0 target-flexibility) (0 robustness) gpi:GPICK_05460 (212 target-flexibility) (73 robustness) gpi:GPICK_06080 (841 target-flexibility) (126 robustness) gpi:GPICK_06205 (175 target-flexibility) (96 robustness) gpi:GPICK_06250 (734 target-flexibility) (110 robustness) gpi:GPICK_06360 (821 target-flexibility) (137 robustness) gpi:GPICK_06970 (357 target-flexibility) (102 robustness) gpi:GPICK_07085 (841 target-flexibility) (126 robustness) gpi:GPICK_07275 (1169 target-flexibility) (76 robustness) gpi:GPICK_07425 (600 target-flexibility) (126 robustness) gpi:GPICK_07440 (0 target-flexibility) (0 robustness) gpi:GPICK_07485 (0 target-flexibility) (0 robustness) gpi:GPICK_07640 (796 target-flexibility) (85 robustness) gpi:GPICK_07650 (0 target-flexibility) (0 robustness) gpi:GPICK_07790 (0 target-flexibility) (0 robustness) gpi:GPICK_07830 (0 target-flexibility) (0 robustness) gpi:GPICK_07925 (1108 target-flexibility) (319 robustness) gpi:GPICK_07935 (659 target-flexibility) (240 robustness) gpi:GPICK_07945 (703 target-flexibility) (319 robustness) gpi:GPICK_08135 (1041 target-flexibility) (243 robustness) gpi:GPICK_08200 (0 target-flexibility) (0 robustness) gpi:GPICK_08240 (0 target-flexibility) (0 robustness) gpi:GPICK_08380 (732 target-flexibility) (78 robustness) gpi:GPICK_08415 (600 target-flexibility) (126 robustness) gpi:GPICK_08745 (752 target-flexibility) (76 robustness) gpi:GPICK_09020 (821 target-flexibility) (137 robustness) gpi:GPICK_09250 (528 target-flexibility) (157 robustness) gpi:GPICK_09325 (659 target-flexibility) (240 robustness) gpi:GPICK_09350 (0 target-flexibility) (0 robustness) gpi:GPICK_09355 (0 target-flexibility) (0 robustness) gpi:GPICK_09465 (0 target-flexibility) (0 robustness) gpi:GPICK_09850 (897 target-flexibility) (71 robustness) gpi:GPICK_09910 (1385 target-flexibility) (204 robustness) gpi:GPICK_10090 (323 target-flexibility) (101 robustness) gpi:GPICK_10225 (0 target-flexibility) (0 robustness) gpi:GPICK_10320 (691 target-flexibility) (528 robustness) gpi:GPICK_10370 (0 target-flexibility) (0 robustness) gpi:GPICK_10380 (0 target-flexibility) (0 robustness) gpi:GPICK_10485 (139 target-flexibility) (66 robustness) gpi:GPICK_10520 (71 target-flexibility) (71 robustness) gpi:GPICK_10945 (358 target-flexibility) (124 robustness) gpi:GPICK_11140 (924 target-flexibility) (101 robustness) gpi:GPICK_11530 (323 target-flexibility) (101 robustness) gpi:GPICK_11735 (0 target-flexibility) (0 robustness) gpi:GPICK_11740 (0 target-flexibility) (0 robustness) gpi:GPICK_11785 (686 target-flexibility) (192 robustness) gpi:GPICK_11795 (686 target-flexibility) (192 robustness) gpi:GPICK_12055 (0 target-flexibility) (0 robustness) gpi:GPICK_12360 (139 target-flexibility) (66 robustness) gpi:GPICK_12620 (350 target-flexibility) (189 robustness) gpi:GPICK_13255 (0 target-flexibility) (0 robustness) gpi:GPICK_13390 (91 target-flexibility) (91 robustness) gpi:GPICK_13690 (528 target-flexibility) (157 robustness) gpi:GPICK_14070 (0 target-flexibility) (0 robustness) gpi:GPICK_14470 (0 target-flexibility) (0 robustness) gpi:GPICK_14550 (0 target-flexibility) (0 robustness) gpi:GPICK_14900 (0 target-flexibility) (0 robustness) gpi:GPICK_15035 (1108 target-flexibility) (319 robustness) gpi:GPICK_15235 (350 target-flexibility) (189 robustness) gpi:GPICK_15315 (80 target-flexibility) (80 robustness) gpi:GPICK_15365 (796 target-flexibility) (85 robustness) gpi:GPICK_15425 (659 target-flexibility) (240 robustness) gpi:GPICK_15430 (703 target-flexibility) (319 robustness) gpi:GPICK_15670 (691 target-flexibility) (528 robustness) gsb:GSUB_00160 (138 target-flexibility) (138 robustness) gsb:GSUB_00535 (528 target-flexibility) (157 robustness) gsb:GSUB_00615 (80 target-flexibility) (80 robustness) gsb:GSUB_01295 (691 target-flexibility) (528 robustness) gsb:GSUB_01445 (0 target-flexibility) (0 robustness) gsb:GSUB_01620 (0 target-flexibility) (0 robustness) gsb:GSUB_01730 (222 target-flexibility) (83 robustness) gsb:GSUB_01835 (0 target-flexibility) (0 robustness) gsb:GSUB_01970 (231 target-flexibility) (158 robustness) gsb:GSUB_02190 (796 target-flexibility) (85 robustness) gsb:GSUB_02445 (528 target-flexibility) (157 robustness) gsb:GSUB_02540 (0 target-flexibility) (0 robustness) gsb:GSUB_02545 (0 target-flexibility) (0 robustness) gsb:GSUB_02660 (138 target-flexibility) (138 robustness) gsb:GSUB_02810 (1041 target-flexibility) (243 robustness) gsb:GSUB_02815 (1041 target-flexibility) (243 robustness) gsb:GSUB_03040 (138 target-flexibility) (66 robustness) gsb:GSUB_03270 (0 target-flexibility) (0 robustness) gsb:GSUB_03680 (243 target-flexibility) (97 robustness) gsb:GSUB_03880 (405 target-flexibility) (169 robustness) gsb:GSUB_04800 (752 target-flexibility) (76 robustness) gsb:GSUB_05075 (243 target-flexibility) (97 robustness) gsb:GSUB_05255 (0 target-flexibility) (0 robustness) gsb:GSUB_06155 (1169 target-flexibility) (76 robustness) gsb:GSUB_07140 (700 target-flexibility) (80 robustness) gsb:GSUB_07510 (691 target-flexibility) (528 robustness) gsb:GSUB_07515 (526 target-flexibility) (95 robustness) gsb:GSUB_07600 (0 target-flexibility) (0 robustness) gsb:GSUB_07655 (1108 target-flexibility) (319 robustness) gsb:GSUB_08095 (0 target-flexibility) (0 robustness) gsb:GSUB_08160 (0 target-flexibility) (0 robustness) gsb:GSUB_08195 (0 target-flexibility) (0 robustness) gsb:GSUB_08785 (902 target-flexibility) (228 robustness) gsb:GSUB_08840 (0 target-flexibility) (0 robustness) gsb:GSUB_08845 (0 target-flexibility) (0 robustness) gsb:GSUB_08910 (0 target-flexibility) (0 robustness) gsb:GSUB_09020 (0 target-flexibility) (0 robustness) gsb:GSUB_09095 (0 target-flexibility) (0 robustness) gsb:GSUB_09105 (0 target-flexibility) (0 robustness) gsb:GSUB_09165 (405 target-flexibility) (169 robustness) gsb:GSUB_09180 (897 target-flexibility) (71 robustness) gsb:GSUB_09375 (732 target-flexibility) (78 robustness) gsb:GSUB_09400 (600 target-flexibility) (126 robustness) gsb:GSUB_09555 (0 target-flexibility) (0 robustness) gsb:GSUB_10305 (700 target-flexibility) (80 robustness) gsb:GSUB_10480 (71 target-flexibility) (71 robustness) gsb:GSUB_10525 (1108 target-flexibility) (319 robustness) gsb:GSUB_10905 (841 target-flexibility) (126 robustness) gsb:GSUB_10925 (902 target-flexibility) (228 robustness) gsb:GSUB_11175 (212 target-flexibility) (73 robustness) gsb:GSUB_11235 (600 target-flexibility) (126 robustness) gsb:GSUB_12340 (841 target-flexibility) (126 robustness) gsb:GSUB_12475 (686 target-flexibility) (192 robustness) gsb:GSUB_12485 (686 target-flexibility) (192 robustness) gsb:GSUB_12790 (902 target-flexibility) (228 robustness) gsb:GSUB_12980 (231 target-flexibility) (158 robustness) gsb:GSUB_12985 (70 target-flexibility) (70 robustness) gsb:GSUB_13010 (67 target-flexibility) (67 robustness) gsb:GSUB_13015 (239 target-flexibility) (67 robustness) gsb:GSUB_13265 (600 target-flexibility) (126 robustness) gsb:GSUB_13365 (0 target-flexibility) (0 robustness) gsb:GSUB_13565 (528 target-flexibility) (157 robustness) gsb:GSUB_13655 (0 target-flexibility) (0 robustness) gsb:GSUB_13975 (0 target-flexibility) (0 robustness) gsb:GSUB_14410 (1041 target-flexibility) (243 robustness) gsb:GSUB_15430 (0 target-flexibility) (0 robustness) gsb:GSUB_15700 (0 target-flexibility) (0 robustness) gsb:GSUB_17495 (526 target-flexibility) (95 robustness) gsu:GSU0067 (0 target-flexibility) (0 robustness) gsu:GSU0094 (691 target-flexibility) (528 robustness) gsu:GSU0152 (138 target-flexibility) (66 robustness) gsu:GSU0290 (1108 target-flexibility) (319 robustness) gsu:GSU0337 (80 target-flexibility) (80 robustness) gsu:GSU0371 (0 target-flexibility) (0 robustness) gsu:GSU0460 (703 target-flexibility) (319 robustness) gsu:GSU0461 (659 target-flexibility) (240 robustness) gsu:GSU0482 (0 target-flexibility) (0 robustness) gsu:GSU0535 (528 target-flexibility) (157 robustness) gsu:GSU0604 (91 target-flexibility) (91 robustness) gsu:GSU0686 (1169 target-flexibility) (76 robustness) gsu:GSU0846 (262 target-flexibility) (86 robustness) gsu:GSU0999 (139 target-flexibility) (66 robustness) gsu:GSU1023 (0 target-flexibility) (0 robustness) gsu:GSU1061 (1385 target-flexibility) (204 robustness) gsu:GSU1242 (1385 target-flexibility) (204 robustness) gsu:GSU1271 (897 target-flexibility) (71 robustness) gsu:GSU1463 (752 target-flexibility) (76 robustness) gsu:GSU1582 (0 target-flexibility) (0 robustness) gsu:GSU1601 (1108 target-flexibility) (319 robustness) gsu:GSU1603 (659 target-flexibility) (240 robustness) gsu:GSU1605 (703 target-flexibility) (319 robustness) gsu:GSU1623 (0 target-flexibility) (0 robustness) gsu:GSU1729 (0 target-flexibility) (0 robustness) gsu:GSU1737 (0 target-flexibility) (0 robustness) gsu:GSU1764 (1169 target-flexibility) (76 robustness) gsu:GSU1798 (841 target-flexibility) (126 robustness) gsu:GSU1906 (841 target-flexibility) (126 robustness) gsu:GSU2011 (358 target-flexibility) (124 robustness) gsu:GSU2045 (212 target-flexibility) (73 robustness) gsu:GSU2066 (0 target-flexibility) (0 robustness) gsu:GSU2209 (0 target-flexibility) (0 robustness) gsu:GSU2230 (691 target-flexibility) (528 robustness) gsu:GSU2241 (0 target-flexibility) (0 robustness) gsu:GSU2264 (139 target-flexibility) (66 robustness) gsu:GSU2271 (71 target-flexibility) (71 robustness) gsu:GSU2307 (0 target-flexibility) (0 robustness) gsu:GSU2366 (0 target-flexibility) (0 robustness) gsu:GSU2375 (686 target-flexibility) (192 robustness) gsu:GSU2379 (686 target-flexibility) (192 robustness) gsu:GSU2445 (262 target-flexibility) (86 robustness) gsu:GSU2446 (323 target-flexibility) (101 robustness) gsu:GSU2570 (358 target-flexibility) (124 robustness) gsu:GSU2588 (323 target-flexibility) (101 robustness) gsu:GSU2786 (358 target-flexibility) (124 robustness) gsu:GSU2918 (1041 target-flexibility) (243 robustness) gsu:GSU2919 (1041 target-flexibility) (243 robustness) gsu:GSU3005 (91 target-flexibility) (91 robustness) gsu:GSU3095 (0 target-flexibility) (0 robustness) gsu:GSU3096 (0 target-flexibility) (0 robustness) gsu:GSU3136 (222 target-flexibility) (83 robustness) gsu:GSU3158 (528 target-flexibility) (157 robustness) gsu:GSU3257 (0 target-flexibility) (0 robustness) gsu:GSU3296 (0 target-flexibility) (0 robustness) gsu:GSU3372 (0 target-flexibility) (0 robustness) gsu:GSU3423 (1041 target-flexibility) (243 robustness) gur:Gura_0074 (0 target-flexibility) (0 robustness) gur:Gura_0135 (1108 target-flexibility) (319 robustness) gur:Gura_0155 (0 target-flexibility) (0 robustness) gur:Gura_0156 (0 target-flexibility) (0 robustness) gur:Gura_0185 (734 target-flexibility) (110 robustness) gur:Gura_0191 (0 target-flexibility) (0 robustness) gur:Gura_0227 (138 target-flexibility) (66 robustness) gur:Gura_0462 (0 target-flexibility) (0 robustness) gur:Gura_0491 (1041 target-flexibility) (243 robustness) gur:Gura_0492 (1041 target-flexibility) (243 robustness) gur:Gura_0620 (902 target-flexibility) (228 robustness) gur:Gura_0648 (0 target-flexibility) (0 robustness) gur:Gura_0822 (528 target-flexibility) (157 robustness) gur:Gura_0841 (1041 target-flexibility) (243 robustness) gur:Gura_0937 (0 target-flexibility) (0 robustness) gur:Gura_0970 (1041 target-flexibility) (243 robustness) gur:Gura_1018 (1169 target-flexibility) (76 robustness) gur:Gura_1046 (166 target-flexibility) (99 robustness) gur:Gura_1047 (166 target-flexibility) (99 robustness) gur:Gura_1346 (821 target-flexibility) (137 robustness) gur:Gura_1351 (821 target-flexibility) (137 robustness) gur:Gura_1387 (64 target-flexibility) (64 robustness) gur:Gura_1493 (358 target-flexibility) (124 robustness) gur:Gura_1570 (600 target-flexibility) (126 robustness) gur:Gura_1685 (0 target-flexibility) (0 robustness) gur:Gura_1691 (0 target-flexibility) (0 robustness) gur:Gura_1692 (0 target-flexibility) (0 robustness) gur:Gura_1705 (0 target-flexibility) (0 robustness) gur:Gura_1735 (686 target-flexibility) (192 robustness) gur:Gura_1799 (212 target-flexibility) (73 robustness) gur:Gura_1833 (358 target-flexibility) (124 robustness) gur:Gura_1856 (897 target-flexibility) (71 robustness) gur:Gura_1875 (1108 target-flexibility) (319 robustness) gur:Gura_1877 (659 target-flexibility) (240 robustness) gur:Gura_1879 (703 target-flexibility) (319 robustness) gur:Gura_2025 (0 target-flexibility) (0 robustness) gur:Gura_2061 (600 target-flexibility) (126 robustness) gur:Gura_2124 (0 target-flexibility) (0 robustness) gur:Gura_2133 (0 target-flexibility) (0 robustness) gur:Gura_2175 (1169 target-flexibility) (76 robustness) gur:Gura_2196 (752 target-flexibility) (76 robustness) gur:Gura_2199 (0 target-flexibility) (0 robustness) gur:Gura_2244 (0 target-flexibility) (0 robustness) gur:Gura_2259 (734 target-flexibility) (110 robustness) gur:Gura_2317 (841 target-flexibility) (126 robustness) gur:Gura_2419 (700 target-flexibility) (89 robustness) gur:Gura_2420 (0 target-flexibility) (0 robustness) gur:Gura_2501 (1385 target-flexibility) (204 robustness) gur:Gura_2532 (686 target-flexibility) (192 robustness) gur:Gura_2566 (526 target-flexibility) (95 robustness) gur:Gura_2598 (0 target-flexibility) (0 robustness) gur:Gura_2643 (526 target-flexibility) (95 robustness) gur:Gura_2655 (1784 target-flexibility) (162 robustness) gur:Gura_2659 (600 target-flexibility) (126 robustness) gur:Gura_2661 (0 target-flexibility) (0 robustness) gur:Gura_2953 (64 target-flexibility) (64 robustness) gur:Gura_3134 (0 target-flexibility) (0 robustness) gur:Gura_3154 (691 target-flexibility) (528 robustness) gur:Gura_3171 (0 target-flexibility) (0 robustness) gur:Gura_3240 (71 target-flexibility) (71 robustness) gur:Gura_3273 (0 target-flexibility) (0 robustness) gur:Gura_3288 (686 target-flexibility) (192 robustness) gur:Gura_3354 (1385 target-flexibility) (204 robustness) gur:Gura_3393 (0 target-flexibility) (0 robustness) gur:Gura_3485 (0 target-flexibility) (0 robustness) gur:Gura_3486 (0 target-flexibility) (0 robustness) gur:Gura_3541 (0 target-flexibility) (0 robustness) gur:Gura_3571 (700 target-flexibility) (89 robustness) gur:Gura_3574 (0 target-flexibility) (0 robustness) gur:Gura_3606 (703 target-flexibility) (319 robustness) gur:Gura_3607 (659 target-flexibility) (240 robustness) gur:Gura_3622 (139 target-flexibility) (139 robustness) gur:Gura_3715 (841 target-flexibility) (126 robustness) gur:Gura_3720 (902 target-flexibility) (228 robustness) gur:Gura_3830 (0 target-flexibility) (0 robustness) gur:Gura_3852 (91 target-flexibility) (91 robustness) gur:Gura_3854 (0 target-flexibility) (0 robustness) gur:Gura_3859 (528 target-flexibility) (157 robustness) gur:Gura_3907 (528 target-flexibility) (157 robustness) gur:Gura_3934 (0 target-flexibility) (0 robustness) gur:Gura_3978 (67 target-flexibility) (67 robustness) gur:Gura_3979 (239 target-flexibility) (67 robustness) gur:Gura_3998 (0 target-flexibility) (0 robustness) gur:Gura_3999 (0 target-flexibility) (0 robustness) gur:Gura_4053 (0 target-flexibility) (0 robustness) gur:Gura_4054 (0 target-flexibility) (0 robustness) gur:Gura_4055 (0 target-flexibility) (0 robustness) gur:Gura_4137 (139 target-flexibility) (139 robustness) gur:Gura_4183 (91 target-flexibility) (91 robustness) gur:Gura_4193 (0 target-flexibility) (0 robustness) gur:Gura_4245 (80 target-flexibility) (80 robustness) gur:Gura_4250 (600 target-flexibility) (126 robustness) gur:Gura_4313 (222 target-flexibility) (83 robustness) gur:Gura_4327 (691 target-flexibility) (528 robustness) gur:Gura_4348 (0 target-flexibility) (0 robustness) gur:Gura_4349 (0 target-flexibility) (0 robustness) gur:Gura_4409 (1784 target-flexibility) (162 robustness) hmr:Hipma_0012 (1041 target-flexibility) (243 robustness) hmr:Hipma_0121 (138 target-flexibility) (66 robustness) hmr:Hipma_0146 (0 target-flexibility) (0 robustness) hmr:Hipma_0215 (0 target-flexibility) (0 robustness) hmr:Hipma_0301 (222 target-flexibility) (83 robustness) hmr:Hipma_0341 (71 target-flexibility) (71 robustness) hmr:Hipma_0369 (146 target-flexibility) (70 robustness) hmr:Hipma_0390 (146 target-flexibility) (70 robustness) hmr:Hipma_0412 (0 target-flexibility) (0 robustness) hmr:Hipma_0431 (752 target-flexibility) (76 robustness) hmr:Hipma_0432 (686 target-flexibility) (192 robustness) hmr:Hipma_0501 (897 target-flexibility) (71 robustness) hmr:Hipma_0574 (0 target-flexibility) (0 robustness) hmr:Hipma_0577 (790 target-flexibility) (134 robustness) hmr:Hipma_0790 (0 target-flexibility) (0 robustness) hmr:Hipma_0845 (80 target-flexibility) (80 robustness) hmr:Hipma_0954 (0 target-flexibility) (0 robustness) hmr:Hipma_0956 (0 target-flexibility) (0 robustness) hmr:Hipma_0985 (1169 target-flexibility) (76 robustness) hmr:Hipma_1016 (212 target-flexibility) (73 robustness) hmr:Hipma_1025 (1385 target-flexibility) (204 robustness) hmr:Hipma_1045 (0 target-flexibility) (0 robustness) hmr:Hipma_1167 (0 target-flexibility) (0 robustness) hmr:Hipma_1193 (0 target-flexibility) (0 robustness) hmr:Hipma_1212 (659 target-flexibility) (240 robustness) hmr:Hipma_1397 (1385 target-flexibility) (204 robustness) hmr:Hipma_1401 (0 target-flexibility) (0 robustness) hmr:Hipma_1462 (0 target-flexibility) (0 robustness) hmr:Hipma_1516 (0 target-flexibility) (0 robustness) hmr:Hipma_1526 (790 target-flexibility) (134 robustness) hmr:Hipma_1565 (686 target-flexibility) (192 robustness) hmr:Hipma_1646 (659 target-flexibility) (240 robustness) hmr:Hipma_1703 (0 target-flexibility) (0 robustness) hoh:Hoch_0005 (1108 target-flexibility) (319 robustness) hoh:Hoch_0106 (0 target-flexibility) (0 robustness) hoh:Hoch_0124 (841 target-flexibility) (126 robustness) hoh:Hoch_0217 (528 target-flexibility) (157 robustness) hoh:Hoch_0232 (1108 target-flexibility) (319 robustness) hoh:Hoch_0240 (323 target-flexibility) (101 robustness) hoh:Hoch_0330 (657 target-flexibility) (95 robustness) hoh:Hoch_0343 (80 target-flexibility) (80 robustness) hoh:Hoch_0345 (73 target-flexibility) (73 robustness) hoh:Hoch_0360 (231 target-flexibility) (158 robustness) hoh:Hoch_0379 (0 target-flexibility) (0 robustness) hoh:Hoch_0394 (138 target-flexibility) (66 robustness) hoh:Hoch_0481 (659 target-flexibility) (240 robustness) hoh:Hoch_0610 (1022 target-flexibility) (80 robustness) hoh:Hoch_0637 (691 target-flexibility) (528 robustness) hoh:Hoch_0966 (691 target-flexibility) (528 robustness) hoh:Hoch_1085 (855 target-flexibility) (138 robustness) hoh:Hoch_1478 (796 target-flexibility) (85 robustness) hoh:Hoch_1786 (752 target-flexibility) (105 robustness) hoh:Hoch_1849 (0 target-flexibility) (0 robustness) hoh:Hoch_1891 (530 target-flexibility) (162 robustness) hoh:Hoch_2046 (0 target-flexibility) (0 robustness) hoh:Hoch_2104 (902 target-flexibility) (228 robustness) hoh:Hoch_2190 (358 target-flexibility) (124 robustness) hoh:Hoch_2547 (358 target-flexibility) (124 robustness) hoh:Hoch_2693 (0 target-flexibility) (0 robustness) hoh:Hoch_3033 (855 target-flexibility) (138 robustness) hoh:Hoch_3186 (752 target-flexibility) (76 robustness) hoh:Hoch_3189 (212 target-flexibility) (73 robustness) hoh:Hoch_3234 (323 target-flexibility) (101 robustness) hoh:Hoch_3248 (0 target-flexibility) (0 robustness) hoh:Hoch_3514 (0 target-flexibility) (0 robustness) hoh:Hoch_3572 (0 target-flexibility) (0 robustness) hoh:Hoch_3581 (634 target-flexibility) (72 robustness) hoh:Hoch_3705 (323 target-flexibility) (101 robustness) hoh:Hoch_4024 (357 target-flexibility) (115 robustness) hoh:Hoch_4075 (74 target-flexibility) (74 robustness) hoh:Hoch_4175 (528 target-flexibility) (157 robustness) hoh:Hoch_4179 (528 target-flexibility) (157 robustness) hoh:Hoch_4359 (166 target-flexibility) (99 robustness) hoh:Hoch_4360 (752 target-flexibility) (105 robustness) hoh:Hoch_4463 (796 target-flexibility) (85 robustness) hoh:Hoch_4475 (80 target-flexibility) (80 robustness) hoh:Hoch_4947 (752 target-flexibility) (105 robustness) hoh:Hoch_4968 (1385 target-flexibility) (204 robustness) hoh:Hoch_5001 (659 target-flexibility) (240 robustness) hoh:Hoch_5030 (659 target-flexibility) (240 robustness) hoh:Hoch_5197 (659 target-flexibility) (240 robustness) hoh:Hoch_5539 (790 target-flexibility) (134 robustness) hoh:Hoch_5889 (222 target-flexibility) (83 robustness) hoh:Hoch_6483 (691 target-flexibility) (528 robustness) lip:LI0152 (0 target-flexibility) (0 robustness) lip:LI0379 (0 target-flexibility) (0 robustness) lip:LI0466 (0 target-flexibility) (0 robustness) lip:LI0580 (0 target-flexibility) (0 robustness) lip:LI0648 (212 target-flexibility) (73 robustness) lip:LI0764 (600 target-flexibility) (126 robustness) lip:LI1051 (222 target-flexibility) (83 robustness) lip:LI1066 (0 target-flexibility) (0 robustness) lip:LI1119 (600 target-flexibility) (126 robustness) lip:LIC023 (0 target-flexibility) (0 robustness) llu:AKJ09_00297 (691 target-flexibility) (528 robustness) llu:AKJ09_00381 (0 target-flexibility) (0 robustness) llu:AKJ09_00430 (323 target-flexibility) (101 robustness) llu:AKJ09_00583 (0 target-flexibility) (0 robustness) llu:AKJ09_00609 (0 target-flexibility) (0 robustness) llu:AKJ09_00756 (686 target-flexibility) (192 robustness) llu:AKJ09_00929 (0 target-flexibility) (0 robustness) llu:AKJ09_00976 (0 target-flexibility) (0 robustness) llu:AKJ09_00988 (343 target-flexibility) (180 robustness) llu:AKJ09_01024 (0 target-flexibility) (0 robustness) llu:AKJ09_01101 (175 target-flexibility) (78 robustness) llu:AKJ09_01219 (659 target-flexibility) (240 robustness) llu:AKJ09_01359 (659 target-flexibility) (240 robustness) llu:AKJ09_01443 (659 target-flexibility) (240 robustness) llu:AKJ09_01492 (1041 target-flexibility) (243 robustness) llu:AKJ09_01495 (0 target-flexibility) (0 robustness) llu:AKJ09_01814 (0 target-flexibility) (0 robustness) llu:AKJ09_01841 (659 target-flexibility) (240 robustness) llu:AKJ09_01852 (0 target-flexibility) (0 robustness) llu:AKJ09_01880 (734 target-flexibility) (110 robustness) llu:AKJ09_01932 (659 target-flexibility) (240 robustness) llu:AKJ09_02037 (301 target-flexibility) (154 robustness) llu:AKJ09_02362 (659 target-flexibility) (240 robustness) llu:AKJ09_02446 (752 target-flexibility) (105 robustness) llu:AKJ09_02465 (503 target-flexibility) (78 robustness) llu:AKJ09_02467 (1108 target-flexibility) (319 robustness) llu:AKJ09_02491 (175 target-flexibility) (78 robustness) llu:AKJ09_02570 (706 target-flexibility) (173 robustness) llu:AKJ09_02591 (902 target-flexibility) (228 robustness) llu:AKJ09_02664 (0 target-flexibility) (0 robustness) llu:AKJ09_02687 (697 target-flexibility) (78 robustness) llu:AKJ09_02763 (357 target-flexibility) (102 robustness) llu:AKJ09_02792 (138 target-flexibility) (138 robustness) llu:AKJ09_02816 (357 target-flexibility) (102 robustness) llu:AKJ09_02824 (855 target-flexibility) (138 robustness) llu:AKJ09_02949 (189 target-flexibility) (94 robustness) llu:AKJ09_02979 (228 target-flexibility) (83 robustness) llu:AKJ09_02991 (0 target-flexibility) (0 robustness) llu:AKJ09_03084 (924 target-flexibility) (101 robustness) llu:AKJ09_03136 (841 target-flexibility) (126 robustness) llu:AKJ09_03141 (841 target-flexibility) (126 robustness) llu:AKJ09_03445 (691 target-flexibility) (528 robustness) llu:AKJ09_03567 (752 target-flexibility) (76 robustness) llu:AKJ09_03571 (357 target-flexibility) (115 robustness) llu:AKJ09_03976 (0 target-flexibility) (0 robustness) llu:AKJ09_04170 (0 target-flexibility) (0 robustness) llu:AKJ09_04246 (358 target-flexibility) (104 robustness) llu:AKJ09_04269 (796 target-flexibility) (85 robustness) llu:AKJ09_04272 (434 target-flexibility) (67 robustness) llu:AKJ09_04281 (1183 target-flexibility) (114 robustness) llu:AKJ09_04504 (269 target-flexibility) (64 robustness) llu:AKJ09_04506 (902 target-flexibility) (228 robustness) llu:AKJ09_04690 (239 target-flexibility) (67 robustness) llu:AKJ09_04691 (67 target-flexibility) (67 robustness) llu:AKJ09_04767 (71 target-flexibility) (71 robustness) llu:AKJ09_04777 (821 target-flexibility) (137 robustness) llu:AKJ09_04857 (231 target-flexibility) (158 robustness) llu:AKJ09_04918 (358 target-flexibility) (104 robustness) llu:AKJ09_04925 (659 target-flexibility) (240 robustness) llu:AKJ09_05088 (821 target-flexibility) (137 robustness) llu:AKJ09_05091 (821 target-flexibility) (137 robustness) llu:AKJ09_05171 (1108 target-flexibility) (319 robustness) llu:AKJ09_05284 (0 target-flexibility) (0 robustness) llu:AKJ09_05314 (0 target-flexibility) (0 robustness) llu:AKJ09_05385 (138 target-flexibility) (138 robustness) llu:AKJ09_05466 (0 target-flexibility) (0 robustness) llu:AKJ09_05499 (0 target-flexibility) (0 robustness) llu:AKJ09_05604 (855 target-flexibility) (138 robustness) llu:AKJ09_05672 (497 target-flexibility) (186 robustness) llu:AKJ09_05860 (405 target-flexibility) (169 robustness) llu:AKJ09_05861 (0 target-flexibility) (0 robustness) llu:AKJ09_05870 (358 target-flexibility) (124 robustness) llu:AKJ09_06116 (1108 target-flexibility) (319 robustness) llu:AKJ09_06135 (357 target-flexibility) (115 robustness) llu:AKJ09_06149 (790 target-flexibility) (134 robustness) llu:AKJ09_06301 (902 target-flexibility) (228 robustness) llu:AKJ09_06311 (497 target-flexibility) (186 robustness) llu:AKJ09_06892 (706 target-flexibility) (173 robustness) llu:AKJ09_06902 (269 target-flexibility) (64 robustness) llu:AKJ09_06932 (0 target-flexibility) (0 robustness) llu:AKJ09_07273 (1041 target-flexibility) (243 robustness) llu:AKJ09_07279 (138 target-flexibility) (138 robustness) llu:AKJ09_07318 (902 target-flexibility) (228 robustness) llu:AKJ09_07370 (790 target-flexibility) (134 robustness) llu:AKJ09_07537 (301 target-flexibility) (154 robustness) llu:AKJ09_07617 (323 target-flexibility) (101 robustness) llu:AKJ09_07685 (657 target-flexibility) (95 robustness) llu:AKJ09_07813 (0 target-flexibility) (0 robustness) llu:AKJ09_07814 (0 target-flexibility) (0 robustness) llu:AKJ09_07818 (659 target-flexibility) (240 robustness) llu:AKJ09_07825 (821 target-flexibility) (137 robustness) llu:AKJ09_07946 (497 target-flexibility) (186 robustness) llu:AKJ09_07972 (72 target-flexibility) (72 robustness) llu:AKJ09_08079 (0 target-flexibility) (0 robustness) llu:AKJ09_08130 (0 target-flexibility) (0 robustness) llu:AKJ09_08203 (0 target-flexibility) (0 robustness) llu:AKJ09_08204 (0 target-flexibility) (0 robustness) llu:AKJ09_08207 (0 target-flexibility) (0 robustness) llu:AKJ09_08280 (1108 target-flexibility) (319 robustness) llu:AKJ09_08366 (657 target-flexibility) (95 robustness) llu:AKJ09_08401 (528 target-flexibility) (157 robustness) llu:AKJ09_08434 (703 target-flexibility) (319 robustness) llu:AKJ09_08436 (703 target-flexibility) (319 robustness) llu:AKJ09_08534 (0 target-flexibility) (0 robustness) llu:AKJ09_08543 (358 target-flexibility) (124 robustness) llu:AKJ09_08550 (1041 target-flexibility) (243 robustness) llu:AKJ09_08589 (1108 target-flexibility) (319 robustness) llu:AKJ09_08666 (323 target-flexibility) (101 robustness) llu:AKJ09_08711 (343 target-flexibility) (180 robustness) llu:AKJ09_08721 (323 target-flexibility) (101 robustness) llu:AKJ09_08807 (231 target-flexibility) (158 robustness) llu:AKJ09_08845 (0 target-flexibility) (0 robustness) llu:AKJ09_08892 (703 target-flexibility) (319 robustness) llu:AKJ09_08893 (703 target-flexibility) (319 robustness) llu:AKJ09_08899 (222 target-flexibility) (83 robustness) llu:AKJ09_09034 (497 target-flexibility) (186 robustness) llu:AKJ09_09066 (528 target-flexibility) (157 robustness) llu:AKJ09_09070 (528 target-flexibility) (157 robustness) llu:AKJ09_09395 (659 target-flexibility) (240 robustness) llu:AKJ09_09399 (0 target-flexibility) (0 robustness) llu:AKJ09_09446 (530 target-flexibility) (162 robustness) llu:AKJ09_09477 (734 target-flexibility) (110 robustness) llu:AKJ09_09492 (752 target-flexibility) (105 robustness) llu:AKJ09_09548 (686 target-flexibility) (192 robustness) llu:AKJ09_09565 (0 target-flexibility) (0 robustness) llu:AKJ09_09576 (0 target-flexibility) (0 robustness) llu:AKJ09_09652 (0 target-flexibility) (0 robustness) llu:AKJ09_09653 (924 target-flexibility) (101 robustness) llu:AKJ09_09654 (924 target-flexibility) (101 robustness) llu:AKJ09_09735 (0 target-flexibility) (0 robustness) llu:AKJ09_09838 (691 target-flexibility) (528 robustness) llu:AKJ09_09908 (1183 target-flexibility) (114 robustness) llu:AKJ09_09992 (189 target-flexibility) (94 robustness) llu:AKJ09_10077 (855 target-flexibility) (138 robustness) llu:AKJ09_10095 (691 target-flexibility) (528 robustness) llu:AKJ09_10129 (0 target-flexibility) (0 robustness) llu:AKJ09_10188 (0 target-flexibility) (0 robustness) llu:AKJ09_10310 (1108 target-flexibility) (319 robustness) llu:AKJ09_10313 (503 target-flexibility) (78 robustness) llu:AKJ09_10314 (659 target-flexibility) (240 robustness) llu:AKJ09_10316 (703 target-flexibility) (319 robustness) llu:AKJ09_10333 (732 target-flexibility) (78 robustness) llu:AKJ09_10337 (228 target-flexibility) (83 robustness) llu:AKJ09_10397 (289 target-flexibility) (73 robustness) llu:AKJ09_10666 (703 target-flexibility) (319 robustness) llu:AKJ09_10708 (323 target-flexibility) (101 robustness) llu:AKJ09_10720 (343 target-flexibility) (180 robustness) llu:AKJ09_10739 (0 target-flexibility) (0 robustness) llu:AKJ09_10878 (343 target-flexibility) (180 robustness) llu:AKJ09_10905 (212 target-flexibility) (73 robustness) llu:AKJ09_10940 (697 target-flexibility) (78 robustness) llu:AKJ09_11102 (72 target-flexibility) (72 robustness) llu:AKJ09_11129 (358 target-flexibility) (124 robustness) llu:AKJ09_11361 (855 target-flexibility) (138 robustness) llu:AKJ09_11379 (530 target-flexibility) (162 robustness) llu:AKJ09_11455 (405 target-flexibility) (169 robustness) llu:AKJ09_11473 (659 target-flexibility) (240 robustness) mbd:MEBOL_000129 (0 target-flexibility) (0 robustness) mbd:MEBOL_000187 (855 target-flexibility) (138 robustness) mbd:MEBOL_000191 (358 target-flexibility) (124 robustness) mbd:MEBOL_000258 (0 target-flexibility) (0 robustness) mbd:MEBOL_000259 (700 target-flexibility) (77 robustness) mbd:MEBOL_000279 (734 target-flexibility) (110 robustness) mbd:MEBOL_000359 (691 target-flexibility) (528 robustness) mbd:MEBOL_000546 (357 target-flexibility) (102 robustness) mbd:MEBOL_000633 (1022 target-flexibility) (80 robustness) mbd:MEBOL_000658 (1183 target-flexibility) (114 robustness) mbd:MEBOL_000709 (526 target-flexibility) (95 robustness) mbd:MEBOL_000749 (790 target-flexibility) (134 robustness) mbd:MEBOL_000779 (530 target-flexibility) (162 robustness) mbd:MEBOL_000837 (706 target-flexibility) (173 robustness) mbd:MEBOL_000907 (0 target-flexibility) (0 robustness) mbd:MEBOL_000935 (528 target-flexibility) (157 robustness) mbd:MEBOL_000951 (0 target-flexibility) (0 robustness) mbd:MEBOL_001212 (0 target-flexibility) (0 robustness) mbd:MEBOL_001262 (231 target-flexibility) (158 robustness) mbd:MEBOL_001387 (231 target-flexibility) (158 robustness) mbd:MEBOL_001393 (0 target-flexibility) (0 robustness) mbd:MEBOL_001459 (228 target-flexibility) (83 robustness) mbd:MEBOL_001626 (239 target-flexibility) (99 robustness) mbd:MEBOL_001640 (231 target-flexibility) (158 robustness) mbd:MEBOL_001826 (323 target-flexibility) (101 robustness) mbd:MEBOL_001876 (821 target-flexibility) (137 robustness) mbd:MEBOL_001936 (1784 target-flexibility) (162 robustness) mbd:MEBOL_002073 (0 target-flexibility) (0 robustness) mbd:MEBOL_002076 (0 target-flexibility) (0 robustness) mbd:MEBOL_002081 (0 target-flexibility) (0 robustness) mbd:MEBOL_002086 (1183 target-flexibility) (114 robustness) mbd:MEBOL_002196 (222 target-flexibility) (83 robustness) mbd:MEBOL_002331 (1022 target-flexibility) (80 robustness) mbd:MEBOL_002332 (0 target-flexibility) (0 robustness) mbd:MEBOL_002444 (231 target-flexibility) (158 robustness) mbd:MEBOL_002466 (700 target-flexibility) (77 robustness) mbd:MEBOL_002467 (423 target-flexibility) (81 robustness) mbd:MEBOL_002469 (1022 target-flexibility) (80 robustness) mbd:MEBOL_002586 (0 target-flexibility) (0 robustness) mbd:MEBOL_002622 (0 target-flexibility) (0 robustness) mbd:MEBOL_002704 (659 target-flexibility) (240 robustness) mbd:MEBOL_002843 (657 target-flexibility) (95 robustness) mbd:MEBOL_002893 (359 target-flexibility) (65 robustness) mbd:MEBOL_002972 (659 target-flexibility) (240 robustness) mbd:MEBOL_003044 (659 target-flexibility) (240 robustness) mbd:MEBOL_003120 (0 target-flexibility) (0 robustness) mbd:MEBOL_003149 (0 target-flexibility) (0 robustness) mbd:MEBOL_003186 (706 target-flexibility) (173 robustness) mbd:MEBOL_003195 (703 target-flexibility) (319 robustness) mbd:MEBOL_003207 (855 target-flexibility) (138 robustness) mbd:MEBOL_003365 (706 target-flexibility) (173 robustness) mbd:MEBOL_003524 (0 target-flexibility) (0 robustness) mbd:MEBOL_003610 (659 target-flexibility) (240 robustness) mbd:MEBOL_003612 (1108 target-flexibility) (319 robustness) mbd:MEBOL_003654 (528 target-flexibility) (157 robustness) mbd:MEBOL_003759 (0 target-flexibility) (0 robustness) mbd:MEBOL_003801 (222 target-flexibility) (83 robustness) mbd:MEBOL_003817 (73 target-flexibility) (73 robustness) mbd:MEBOL_003822 (80 target-flexibility) (80 robustness) mbd:MEBOL_004017 (1385 target-flexibility) (204 robustness) mbd:MEBOL_004287 (359 target-flexibility) (65 robustness) mbd:MEBOL_004288 (855 target-flexibility) (138 robustness) mbd:MEBOL_004362 (790 target-flexibility) (134 robustness) mbd:MEBOL_004403 (343 target-flexibility) (180 robustness) mbd:MEBOL_004464 (0 target-flexibility) (0 robustness) mbd:MEBOL_004536 (73 target-flexibility) (73 robustness) mbd:MEBOL_004563 (732 target-flexibility) (78 robustness) mbd:MEBOL_004613 (74 target-flexibility) (74 robustness) mbd:MEBOL_004626 (231 target-flexibility) (158 robustness) mbd:MEBOL_004723 (659 target-flexibility) (240 robustness) mbd:MEBOL_004742 (357 target-flexibility) (102 robustness) mbd:MEBOL_004866 (0 target-flexibility) (0 robustness) mbd:MEBOL_004893 (796 target-flexibility) (85 robustness) mbd:MEBOL_004899 (734 target-flexibility) (110 robustness) mbd:MEBOL_004988 (343 target-flexibility) (180 robustness) mbd:MEBOL_005080 (0 target-flexibility) (0 robustness) mbd:MEBOL_005163 (526 target-flexibility) (95 robustness) mbd:MEBOL_005201 (691 target-flexibility) (528 robustness) mbd:MEBOL_005217 (0 target-flexibility) (0 robustness) mbd:MEBOL_005248 (0 target-flexibility) (0 robustness) mbd:MEBOL_005276 (0 target-flexibility) (0 robustness) mbd:MEBOL_005346 (706 target-flexibility) (173 robustness) mbd:MEBOL_005347 (706 target-flexibility) (173 robustness) mbd:MEBOL_005452 (0 target-flexibility) (0 robustness) mbd:MEBOL_005477 (0 target-flexibility) (0 robustness) mbd:MEBOL_005679 (0 target-flexibility) (0 robustness) mbd:MEBOL_005688 (657 target-flexibility) (95 robustness) mbd:MEBOL_005729 (358 target-flexibility) (124 robustness) mbd:MEBOL_005896 (752 target-flexibility) (105 robustness) mbd:MEBOL_005961 (530 target-flexibility) (162 robustness) mbd:MEBOL_005962 (1108 target-flexibility) (319 robustness) mbd:MEBOL_005963 (503 target-flexibility) (78 robustness) mbd:MEBOL_005964 (659 target-flexibility) (240 robustness) mbd:MEBOL_005966 (703 target-flexibility) (319 robustness) mbd:MEBOL_005988 (0 target-flexibility) (0 robustness) mbd:MEBOL_006001 (71 target-flexibility) (71 robustness) mbd:MEBOL_006201 (323 target-flexibility) (101 robustness) mbd:MEBOL_006208 (0 target-flexibility) (0 robustness) mbd:MEBOL_006356 (231 target-flexibility) (158 robustness) mbd:MEBOL_006515 (821 target-flexibility) (137 robustness) mbd:MEBOL_006600 (343 target-flexibility) (180 robustness) mbd:MEBOL_006606 (503 target-flexibility) (78 robustness) mbd:MEBOL_006623 (0 target-flexibility) (0 robustness) mbd:MEBOL_006635 (228 target-flexibility) (83 robustness) mbd:MEBOL_006697 (239 target-flexibility) (99 robustness) mbd:MEBOL_006725 (752 target-flexibility) (105 robustness) mbd:MEBOL_006810 (706 target-flexibility) (173 robustness) mbd:MEBOL_006836 (0 target-flexibility) (0 robustness) mbd:MEBOL_006837 (0 target-flexibility) (0 robustness) mbd:MEBOL_006840 (897 target-flexibility) (71 robustness) mbd:MEBOL_006847 (1784 target-flexibility) (162 robustness) mbd:MEBOL_006903 (0 target-flexibility) (0 robustness) mbd:MEBOL_006920 (74 target-flexibility) (74 robustness) mbd:MEBOL_006939 (0 target-flexibility) (0 robustness) mbd:MEBOL_006971 (706 target-flexibility) (173 robustness) mbd:MEBOL_007199 (423 target-flexibility) (81 robustness) mbd:MEBOL_007247 (423 target-flexibility) (81 robustness) mbd:MEBOL_007560 (343 target-flexibility) (180 robustness) mbd:MEBOL_007627 (0 target-flexibility) (0 robustness) mbd:MEBOL_007650 (821 target-flexibility) (137 robustness) mbd:MEBOL_007696 (0 target-flexibility) (0 robustness) mbd:MEBOL_007699 (301 target-flexibility) (74 robustness) mbd:MEBOL_007700 (138 target-flexibility) (66 robustness) mbd:MEBOL_007718 (1385 target-flexibility) (204 robustness) mbd:MEBOL_007719 (0 target-flexibility) (0 robustness) mbd:MEBOL_007750 (0 target-flexibility) (0 robustness) mbd:MEBOL_007805 (301 target-flexibility) (74 robustness) mbd:MEBOL_007806 (528 target-flexibility) (157 robustness) mbd:MEBOL_007830 (659 target-flexibility) (240 robustness) mbd:MEBOL_007910 (212 target-flexibility) (73 robustness) mbd:MEBOL_007979 (0 target-flexibility) (0 robustness) mbd:MEBOL_008059 (0 target-flexibility) (0 robustness) mbd:MEBOL_008079 (752 target-flexibility) (76 robustness) mfu:LILAB_00500 (0 target-flexibility) (0 robustness) mfu:LILAB_00760 (0 target-flexibility) (0 robustness) mfu:LILAB_00790 (215 target-flexibility) (142 robustness) mfu:LILAB_00885 (528 target-flexibility) (157 robustness) mfu:LILAB_01140 (0 target-flexibility) (0 robustness) mfu:LILAB_01545 (336 target-flexibility) (81 robustness) mfu:LILAB_01860 (796 target-flexibility) (85 robustness) mfu:LILAB_01980 (0 target-flexibility) (0 robustness) mfu:LILAB_02370 (357 target-flexibility) (102 robustness) mfu:LILAB_03115 (732 target-flexibility) (78 robustness) mfu:LILAB_03385 (0 target-flexibility) (0 robustness) mfu:LILAB_03490 (154 target-flexibility) (80 robustness) mfu:LILAB_03630 (361 target-flexibility) (101 robustness) mfu:LILAB_03750 (528 target-flexibility) (157 robustness) mfu:LILAB_04135 (659 target-flexibility) (240 robustness) mfu:LILAB_04155 (357 target-flexibility) (115 robustness) mfu:LILAB_04510 (1108 target-flexibility) (319 robustness) mfu:LILAB_06150 (0 target-flexibility) (0 robustness) mfu:LILAB_06190 (1385 target-flexibility) (204 robustness) mfu:LILAB_06660 (924 target-flexibility) (101 robustness) mfu:LILAB_06720 (80 target-flexibility) (80 robustness) mfu:LILAB_06880 (222 target-flexibility) (83 robustness) mfu:LILAB_07065 (0 target-flexibility) (0 robustness) mfu:LILAB_07165 (821 target-flexibility) (137 robustness) mfu:LILAB_07270 (323 target-flexibility) (101 robustness) mfu:LILAB_07620 (1108 target-flexibility) (319 robustness) mfu:LILAB_07680 (659 target-flexibility) (240 robustness) mfu:LILAB_07990 (343 target-flexibility) (180 robustness) mfu:LILAB_08110 (361 target-flexibility) (101 robustness) mfu:LILAB_08200 (0 target-flexibility) (0 robustness) mfu:LILAB_09240 (0 target-flexibility) (0 robustness) mfu:LILAB_10620 (657 target-flexibility) (95 robustness) mfu:LILAB_10705 (336 target-flexibility) (81 robustness) mfu:LILAB_11470 (0 target-flexibility) (0 robustness) mfu:LILAB_11935 (659 target-flexibility) (240 robustness) mfu:LILAB_12180 (0 target-flexibility) (0 robustness) mfu:LILAB_14035 (154 target-flexibility) (80 robustness) mfu:LILAB_14400 (0 target-flexibility) (0 robustness) mfu:LILAB_14860 (0 target-flexibility) (0 robustness) mfu:LILAB_14960 (1784 target-flexibility) (162 robustness) mfu:LILAB_15365 (222 target-flexibility) (83 robustness) mfu:LILAB_15700 (0 target-flexibility) (0 robustness) mfu:LILAB_15915 (215 target-flexibility) (142 robustness) mfu:LILAB_16115 (1022 target-flexibility) (80 robustness) mfu:LILAB_16510 (231 target-flexibility) (158 robustness) mfu:LILAB_16625 (239 target-flexibility) (99 robustness) mfu:LILAB_17495 (691 target-flexibility) (528 robustness) mfu:LILAB_17540 (0 target-flexibility) (0 robustness) mfu:LILAB_19465 (0 target-flexibility) (0 robustness) mfu:LILAB_19495 (239 target-flexibility) (99 robustness) mfu:LILAB_20360 (0 target-flexibility) (0 robustness) mfu:LILAB_20395 (530 target-flexibility) (162 robustness) mfu:LILAB_20770 (1022 target-flexibility) (80 robustness) mfu:LILAB_21070 (357 target-flexibility) (102 robustness) mfu:LILAB_21465 (821 target-flexibility) (137 robustness) mfu:LILAB_21705 (691 target-flexibility) (528 robustness) mfu:LILAB_22395 (734 target-flexibility) (110 robustness) mfu:LILAB_22525 (0 target-flexibility) (0 robustness) mfu:LILAB_22655 (358 target-flexibility) (124 robustness) mfu:LILAB_24435 (343 target-flexibility) (180 robustness) mfu:LILAB_24700 (0 target-flexibility) (0 robustness) mfu:LILAB_24705 (1385 target-flexibility) (204 robustness) mfu:LILAB_25075 (752 target-flexibility) (105 robustness) mfu:LILAB_25505 (0 target-flexibility) (0 robustness) mfu:LILAB_25510 (0 target-flexibility) (0 robustness) mfu:LILAB_25545 (1784 target-flexibility) (162 robustness) mfu:LILAB_25560 (0 target-flexibility) (0 robustness) mfu:LILAB_25565 (924 target-flexibility) (101 robustness) mfu:LILAB_25930 (0 target-flexibility) (0 robustness) mfu:LILAB_27945 (343 target-flexibility) (180 robustness) mfu:LILAB_28080 (0 target-flexibility) (0 robustness) mfu:LILAB_28260 (0 target-flexibility) (0 robustness) mfu:LILAB_28305 (0 target-flexibility) (0 robustness) mfu:LILAB_28665 (231 target-flexibility) (158 robustness) mfu:LILAB_29010 (528 target-flexibility) (157 robustness) mfu:LILAB_29200 (0 target-flexibility) (0 robustness) mfu:LILAB_29235 (323 target-flexibility) (101 robustness) mfu:LILAB_29280 (0 target-flexibility) (0 robustness) mfu:LILAB_29975 (659 target-flexibility) (240 robustness) mfu:LILAB_30430 (212 target-flexibility) (73 robustness) mfu:LILAB_31010 (0 target-flexibility) (0 robustness) mfu:LILAB_31365 (752 target-flexibility) (76 robustness) mfu:LILAB_31605 (71 target-flexibility) (71 robustness) mfu:LILAB_31675 (0 target-flexibility) (0 robustness) mfu:LILAB_31800 (659 target-flexibility) (240 robustness) mfu:LILAB_31810 (530 target-flexibility) (162 robustness) mfu:LILAB_32345 (752 target-flexibility) (105 robustness) mfu:LILAB_32910 (358 target-flexibility) (124 robustness) mfu:LILAB_33165 (734 target-flexibility) (110 robustness) mfu:LILAB_33330 (657 target-flexibility) (95 robustness) mfu:LILAB_34620 (0 target-flexibility) (0 robustness) mfu:LILAB_35365 (343 target-flexibility) (180 robustness) mfu:LILAB_35470 (231 target-flexibility) (158 robustness) mfu:LILAB_35480 (70 target-flexibility) (70 robustness) mfu:LILAB_35505 (67 target-flexibility) (67 robustness) mfu:LILAB_35630 (357 target-flexibility) (115 robustness) mfu:LILAB_36195 (231 target-flexibility) (158 robustness) mmas:MYMAC_000124 (0 target-flexibility) (0 robustness) mmas:MYMAC_000161 (343 target-flexibility) (180 robustness) mmas:MYMAC_000220 (659 target-flexibility) (240 robustness) mmas:MYMAC_000232 (1108 target-flexibility) (319 robustness) mmas:MYMAC_000305 (323 target-flexibility) (101 robustness) mmas:MYMAC_000327 (821 target-flexibility) (137 robustness) mmas:MYMAC_000346 (0 target-flexibility) (0 robustness) mmas:MYMAC_000385 (222 target-flexibility) (83 robustness) mmas:MYMAC_000432 (80 target-flexibility) (80 robustness) mmas:MYMAC_000444 (924 target-flexibility) (101 robustness) mmas:MYMAC_000545 (1385 target-flexibility) (204 robustness) mmas:MYMAC_000552 (0 target-flexibility) (0 robustness) mmas:MYMAC_000869 (1108 target-flexibility) (319 robustness) mmas:MYMAC_000935 (357 target-flexibility) (115 robustness) mmas:MYMAC_000937 (659 target-flexibility) (240 robustness) mmas:MYMAC_001009 (528 target-flexibility) (157 robustness) mmas:MYMAC_001062 (154 target-flexibility) (80 robustness) mmas:MYMAC_001081 (0 target-flexibility) (0 robustness) mmas:MYMAC_001135 (732 target-flexibility) (78 robustness) mmas:MYMAC_001273 (357 target-flexibility) (102 robustness) mmas:MYMAC_001355 (0 target-flexibility) (0 robustness) mmas:MYMAC_001379 (796 target-flexibility) (85 robustness) mmas:MYMAC_001440 (336 target-flexibility) (81 robustness) mmas:MYMAC_001577 (691 target-flexibility) (528 robustness) mmas:MYMAC_001644 (0 target-flexibility) (0 robustness) mmas:MYMAC_001692 (528 target-flexibility) (157 robustness) mmas:MYMAC_001711 (215 target-flexibility) (142 robustness) mmas:MYMAC_001717 (0 target-flexibility) (0 robustness) mmas:MYMAC_001767 (0 target-flexibility) (0 robustness) mmas:MYMAC_001939 (691 target-flexibility) (528 robustness) mmas:MYMAC_001988 (691 target-flexibility) (528 robustness) mmas:MYMAC_002002 (0 target-flexibility) (0 robustness) mmas:MYMAC_002320 (0 target-flexibility) (0 robustness) mmas:MYMAC_002326 (239 target-flexibility) (99 robustness) mmas:MYMAC_002498 (0 target-flexibility) (0 robustness) mmas:MYMAC_002505 (530 target-flexibility) (162 robustness) mmas:MYMAC_002638 (357 target-flexibility) (102 robustness) mmas:MYMAC_002715 (821 target-flexibility) (137 robustness) mmas:MYMAC_002764 (691 target-flexibility) (528 robustness) mmas:MYMAC_002881 (734 target-flexibility) (110 robustness) mmas:MYMAC_002908 (0 target-flexibility) (0 robustness) mmas:MYMAC_002933 (358 target-flexibility) (124 robustness) mmas:MYMAC_003287 (343 target-flexibility) (180 robustness) mmas:MYMAC_003337 (0 target-flexibility) (0 robustness) mmas:MYMAC_003338 (1385 target-flexibility) (204 robustness) mmas:MYMAC_003407 (752 target-flexibility) (105 robustness) mmas:MYMAC_003448 (0 target-flexibility) (0 robustness) mmas:MYMAC_003449 (0 target-flexibility) (0 robustness) mmas:MYMAC_003456 (1784 target-flexibility) (162 robustness) mmas:MYMAC_003459 (0 target-flexibility) (0 robustness) mmas:MYMAC_003460 (924 target-flexibility) (101 robustness) mmas:MYMAC_003532 (0 target-flexibility) (0 robustness) mmas:MYMAC_003879 (343 target-flexibility) (180 robustness) mmas:MYMAC_003905 (0 target-flexibility) (0 robustness) mmas:MYMAC_003937 (0 target-flexibility) (0 robustness) mmas:MYMAC_003947 (0 target-flexibility) (0 robustness) mmas:MYMAC_004020 (231 target-flexibility) (158 robustness) mmas:MYMAC_004085 (528 target-flexibility) (157 robustness) mmas:MYMAC_004122 (0 target-flexibility) (0 robustness) mmas:MYMAC_004129 (323 target-flexibility) (101 robustness) mmas:MYMAC_004138 (0 target-flexibility) (0 robustness) mmas:MYMAC_004291 (659 target-flexibility) (240 robustness) mmas:MYMAC_004501 (0 target-flexibility) (0 robustness) mmas:MYMAC_004575 (752 target-flexibility) (76 robustness) mmas:MYMAC_004629 (71 target-flexibility) (71 robustness) mmas:MYMAC_004643 (0 target-flexibility) (0 robustness) mmas:MYMAC_004668 (659 target-flexibility) (240 robustness) mmas:MYMAC_004670 (530 target-flexibility) (162 robustness) mmas:MYMAC_004768 (752 target-flexibility) (105 robustness) mmas:MYMAC_004879 (358 target-flexibility) (124 robustness) mmas:MYMAC_004931 (734 target-flexibility) (110 robustness) mmas:MYMAC_004962 (657 target-flexibility) (95 robustness) mmas:MYMAC_005218 (0 target-flexibility) (0 robustness) mmas:MYMAC_005375 (343 target-flexibility) (180 robustness) mmas:MYMAC_005396 (231 target-flexibility) (158 robustness) mmas:MYMAC_005398 (70 target-flexibility) (70 robustness) mmas:MYMAC_005403 (67 target-flexibility) (67 robustness) mmas:MYMAC_005404 (239 target-flexibility) (67 robustness) mmas:MYMAC_005425 (357 target-flexibility) (115 robustness) mmas:MYMAC_005532 (231 target-flexibility) (158 robustness) mmas:MYMAC_005716 (239 target-flexibility) (99 robustness) mmas:MYMAC_005739 (231 target-flexibility) (158 robustness) mmas:MYMAC_005856 (215 target-flexibility) (142 robustness) mmas:MYMAC_005899 (0 target-flexibility) (0 robustness) mmas:MYMAC_005959 (222 target-flexibility) (83 robustness) mmas:MYMAC_006033 (1784 target-flexibility) (162 robustness) mmas:MYMAC_006053 (0 target-flexibility) (0 robustness) mmas:MYMAC_006137 (0 target-flexibility) (0 robustness) mmas:MYMAC_006204 (154 target-flexibility) (80 robustness) mmas:MYMAC_006554 (0 target-flexibility) (0 robustness) mmas:MYMAC_006600 (659 target-flexibility) (240 robustness) mmas:MYMAC_006691 (0 target-flexibility) (0 robustness) mmas:MYMAC_006837 (336 target-flexibility) (81 robustness) mmas:MYMAC_006854 (657 target-flexibility) (95 robustness) mmas:MYMAC_007137 (0 target-flexibility) (0 robustness) mrm:A7982_00131 (138 target-flexibility) (138 robustness) mrm:A7982_00170 (902 target-flexibility) (228 robustness) mrm:A7982_00288 (241 target-flexibility) (71 robustness) mrm:A7982_00296 (659 target-flexibility) (240 robustness) mrm:A7982_00309 (497 target-flexibility) (186 robustness) mrm:A7982_00315 (0 target-flexibility) (0 robustness) mrm:A7982_00371 (239 target-flexibility) (67 robustness) mrm:A7982_00419 (528 target-flexibility) (157 robustness) mrm:A7982_00443 (0 target-flexibility) (0 robustness) mrm:A7982_00857 (189 target-flexibility) (94 robustness) mrm:A7982_01128 (0 target-flexibility) (0 robustness) mrm:A7982_01149 (1385 target-flexibility) (204 robustness) mrm:A7982_01228 (659 target-flexibility) (240 robustness) mrm:A7982_01282 (902 target-flexibility) (228 robustness) mrm:A7982_01283 (1108 target-flexibility) (319 robustness) mrm:A7982_01358 (301 target-flexibility) (154 robustness) mrm:A7982_01390 (1108 target-flexibility) (319 robustness) mrm:A7982_01558 (189 target-flexibility) (94 robustness) mrm:A7982_01769 (0 target-flexibility) (0 robustness) mrm:A7982_01898 (821 target-flexibility) (137 robustness) mrm:A7982_02037 (0 target-flexibility) (0 robustness) mrm:A7982_02117 (0 target-flexibility) (0 robustness) mrm:A7982_02397 (0 target-flexibility) (0 robustness) mrm:A7982_02481 (0 target-flexibility) (0 robustness) mrm:A7982_02519 (790 target-flexibility) (134 robustness) mrm:A7982_02611 (222 target-flexibility) (83 robustness) mrm:A7982_02751 (423 target-flexibility) (81 robustness) mrm:A7982_02766 (0 target-flexibility) (0 robustness) mrm:A7982_02846 (146 target-flexibility) (75 robustness) mrm:A7982_02892 (228 target-flexibility) (83 robustness) mrm:A7982_02930 (0 target-flexibility) (0 robustness) mrm:A7982_02946 (703 target-flexibility) (319 robustness) mrm:A7982_02947 (703 target-flexibility) (319 robustness) mrm:A7982_02950 (659 target-flexibility) (240 robustness) mrm:A7982_02966 (1108 target-flexibility) (319 robustness) mrm:A7982_03001 (358 target-flexibility) (124 robustness) mrm:A7982_03017 (780 target-flexibility) (243 robustness) mrm:A7982_03046 (0 target-flexibility) (0 robustness) mrm:A7982_03051 (700 target-flexibility) (80 robustness) mrm:A7982_03222 (228 target-flexibility) (83 robustness) mrm:A7982_03225 (0 target-flexibility) (0 robustness) mrm:A7982_03238 (1041 target-flexibility) (243 robustness) mrm:A7982_03263 (1041 target-flexibility) (243 robustness) mrm:A7982_03371 (0 target-flexibility) (0 robustness) mrm:A7982_03403 (902 target-flexibility) (228 robustness) mrm:A7982_03732 (231 target-flexibility) (158 robustness) mrm:A7982_04070 (691 target-flexibility) (528 robustness) mrm:A7982_04111 (358 target-flexibility) (104 robustness) mrm:A7982_04172 (350 target-flexibility) (189 robustness) mrm:A7982_04312 (358 target-flexibility) (124 robustness) mrm:A7982_04316 (782 target-flexibility) (75 robustness) mrm:A7982_04557 (0 target-flexibility) (0 robustness) mrm:A7982_04801 (239 target-flexibility) (67 robustness) mrm:A7982_04886 (703 target-flexibility) (319 robustness) mrm:A7982_04896 (0 target-flexibility) (0 robustness) mrm:A7982_04984 (1108 target-flexibility) (319 robustness) mrm:A7982_04986 (902 target-flexibility) (228 robustness) mrm:A7982_05137 (1108 target-flexibility) (319 robustness) mrm:A7982_05182 (0 target-flexibility) (0 robustness) mrm:A7982_05215 (241 target-flexibility) (71 robustness) mrm:A7982_05274 (0 target-flexibility) (0 robustness) mrm:A7982_05339 (0 target-flexibility) (0 robustness) mrm:A7982_05341 (659 target-flexibility) (240 robustness) mrm:A7982_05342 (231 target-flexibility) (158 robustness) mrm:A7982_05402 (0 target-flexibility) (0 robustness) mrm:A7982_05441 (357 target-flexibility) (102 robustness) mrm:A7982_05825 (0 target-flexibility) (0 robustness) mrm:A7982_05891 (0 target-flexibility) (0 robustness) mrm:A7982_05940 (752 target-flexibility) (105 robustness) mrm:A7982_06222 (140 target-flexibility) (74 robustness) mrm:A7982_06344 (700 target-flexibility) (80 robustness) mrm:A7982_06544 (701 target-flexibility) (106 robustness) mrm:A7982_06545 (528 target-flexibility) (157 robustness) mrm:A7982_06576 (0 target-flexibility) (0 robustness) mrm:A7982_06712 (528 target-flexibility) (157 robustness) mrm:A7982_06716 (528 target-flexibility) (157 robustness) mrm:A7982_06797 (703 target-flexibility) (319 robustness) mrm:A7982_06799 (703 target-flexibility) (319 robustness) mrm:A7982_06887 (140 target-flexibility) (74 robustness) mrm:A7982_06955 (289 target-flexibility) (73 robustness) mrm:A7982_07040 (212 target-flexibility) (73 robustness) mrm:A7982_07107 (239 target-flexibility) (99 robustness) mrm:A7982_07443 (0 target-flexibility) (0 robustness) mrm:A7982_07487 (782 target-flexibility) (75 robustness) mrm:A7982_07497 (821 target-flexibility) (137 robustness) mrm:A7982_07501 (821 target-flexibility) (137 robustness) mrm:A7982_07540 (657 target-flexibility) (95 robustness) mrm:A7982_07690 (0 target-flexibility) (0 robustness) mrm:A7982_07760 (701 target-flexibility) (106 robustness) mrm:A7982_07817 (1108 target-flexibility) (319 robustness) mrm:A7982_07818 (902 target-flexibility) (228 robustness) mrm:A7982_07821 (855 target-flexibility) (138 robustness) mrm:A7982_08046 (239 target-flexibility) (99 robustness) mrm:A7982_08253 (780 target-flexibility) (243 robustness) mrm:A7982_08288 (497 target-flexibility) (186 robustness) mrm:A7982_08337 (790 target-flexibility) (134 robustness) mrm:A7982_08390 (734 target-flexibility) (110 robustness) mrm:A7982_08416 (1041 target-flexibility) (243 robustness) mrm:A7982_08417 (1041 target-flexibility) (243 robustness) mrm:A7982_08418 (80 target-flexibility) (80 robustness) mrm:A7982_08550 (528 target-flexibility) (157 robustness) mrm:A7982_08578 (138 target-flexibility) (138 robustness) mrm:A7982_08670 (323 target-flexibility) (101 robustness) mrm:A7982_08677 (497 target-flexibility) (186 robustness) mrm:A7982_08728 (358 target-flexibility) (104 robustness) mrm:A7982_08798 (1108 target-flexibility) (319 robustness) mrm:A7982_08818 (659 target-flexibility) (240 robustness) mrm:A7982_08822 (0 target-flexibility) (0 robustness) mrm:A7982_08954 (336 target-flexibility) (81 robustness) mrm:A7982_08974 (924 target-flexibility) (101 robustness) mrm:A7982_09042 (0 target-flexibility) (0 robustness) mrm:A7982_09160 (0 target-flexibility) (0 robustness) mrm:A7982_09221 (434 target-flexibility) (67 robustness) mrm:A7982_09248 (336 target-flexibility) (81 robustness) mrm:A7982_09318 (1108 target-flexibility) (319 robustness) mrm:A7982_09430 (0 target-flexibility) (0 robustness) mrm:A7982_09467 (350 target-flexibility) (189 robustness) mrm:A7982_09539 (790 target-flexibility) (134 robustness) mrm:A7982_09573 (659 target-flexibility) (240 robustness) mrm:A7982_09578 (497 target-flexibility) (186 robustness) mrm:A7982_09588 (691 target-flexibility) (528 robustness) mrm:A7982_09589 (691 target-flexibility) (528 robustness) mrm:A7982_09670 (902 target-flexibility) (228 robustness) mrm:A7982_09691 (231 target-flexibility) (158 robustness) mrm:A7982_09715 (80 target-flexibility) (80 robustness) mrm:A7982_09718 (301 target-flexibility) (154 robustness) mrm:A7982_09830 (703 target-flexibility) (319 robustness) mrm:A7982_09898 (423 target-flexibility) (81 robustness) mrm:A7982_09970 (1385 target-flexibility) (204 robustness) mrm:A7982_10056 (0 target-flexibility) (0 robustness) mrm:A7982_10241 (189 target-flexibility) (94 robustness) mrm:A7982_10601 (0 target-flexibility) (0 robustness) mrm:A7982_10667 (659 target-flexibility) (240 robustness) mrm:A7982_10763 (358 target-flexibility) (124 robustness) mrm:A7982_10858 (855 target-flexibility) (138 robustness) mrm:A7982_10892 (752 target-flexibility) (105 robustness) mrm:A7982_10954 (0 target-flexibility) (0 robustness) mrm:A7982_11144 (0 target-flexibility) (0 robustness) mrm:A7982_11237 (841 target-flexibility) (288 robustness) mrm:A7982_11353 (902 target-flexibility) (228 robustness) mrm:A7982_11365 (323 target-flexibility) (101 robustness) mrm:A7982_11385 (657 target-flexibility) (95 robustness) mrm:A7982_11740 (752 target-flexibility) (105 robustness) mrm:A7982_12232 (1108 target-flexibility) (319 robustness) mrm:A7982_12387 (0 target-flexibility) (0 robustness) mrm:A7982_12408 (703 target-flexibility) (319 robustness) mrm:A7982_12661 (841 target-flexibility) (288 robustness) mrm:A7982_12663 (231 target-flexibility) (158 robustness) mrm:A7982_12709 (924 target-flexibility) (101 robustness) mrm:A7982_12710 (924 target-flexibility) (101 robustness) mrm:A7982_12819 (0 target-flexibility) (0 robustness) mrm:A7982_12858 (0 target-flexibility) (0 robustness) mrm:A7982_12872 (0 target-flexibility) (0 robustness) mrm:A7982_12928 (734 target-flexibility) (110 robustness) mrm:A7982_12969 (146 target-flexibility) (75 robustness) mrm:A7982_13093 (357 target-flexibility) (102 robustness) mrm:A7982_13482 (659 target-flexibility) (240 robustness) mrm:A7982_13543 (239 target-flexibility) (99 robustness) mrm:A7982_13556 (0 target-flexibility) (0 robustness) mrm:A7982_13708 (0 target-flexibility) (0 robustness) msd:MYSTI_00087 (358 target-flexibility) (124 robustness) msd:MYSTI_00124 (343 target-flexibility) (180 robustness) msd:MYSTI_00211 (659 target-flexibility) (240 robustness) msd:MYSTI_00219 (1108 target-flexibility) (319 robustness) msd:MYSTI_00274 (323 target-flexibility) (101 robustness) msd:MYSTI_00373 (222 target-flexibility) (83 robustness) msd:MYSTI_00520 (1385 target-flexibility) (204 robustness) msd:MYSTI_00528 (0 target-flexibility) (0 robustness) msd:MYSTI_00925 (357 target-flexibility) (115 robustness) msd:MYSTI_00933 (659 target-flexibility) (240 robustness) msd:MYSTI_00991 (790 target-flexibility) (134 robustness) msd:MYSTI_01019 (528 target-flexibility) (157 robustness) msd:MYSTI_01045 (528 target-flexibility) (157 robustness) msd:MYSTI_01086 (154 target-flexibility) (80 robustness) msd:MYSTI_01146 (732 target-flexibility) (78 robustness) msd:MYSTI_01293 (357 target-flexibility) (102 robustness) msd:MYSTI_01365 (659 target-flexibility) (240 robustness) msd:MYSTI_01369 (1041 target-flexibility) (243 robustness) msd:MYSTI_01370 (1041 target-flexibility) (243 robustness) msd:MYSTI_01382 (0 target-flexibility) (0 robustness) msd:MYSTI_01404 (796 target-flexibility) (85 robustness) msd:MYSTI_01458 (336 target-flexibility) (81 robustness) msd:MYSTI_01589 (1108 target-flexibility) (319 robustness) msd:MYSTI_01655 (0 target-flexibility) (0 robustness) msd:MYSTI_01696 (528 target-flexibility) (157 robustness) msd:MYSTI_01723 (0 target-flexibility) (0 robustness) msd:MYSTI_01751 (0 target-flexibility) (0 robustness) msd:MYSTI_01815 (0 target-flexibility) (0 robustness) msd:MYSTI_01936 (267 target-flexibility) (74 robustness) msd:MYSTI_02222 (691 target-flexibility) (528 robustness) msd:MYSTI_02238 (0 target-flexibility) (0 robustness) msd:MYSTI_02246 (138 target-flexibility) (138 robustness) msd:MYSTI_02512 (703 target-flexibility) (319 robustness) msd:MYSTI_02683 (0 target-flexibility) (0 robustness) msd:MYSTI_02722 (0 target-flexibility) (0 robustness) msd:MYSTI_02727 (239 target-flexibility) (99 robustness) msd:MYSTI_02928 (530 target-flexibility) (162 robustness) msd:MYSTI_02961 (790 target-flexibility) (134 robustness) msd:MYSTI_03078 (357 target-flexibility) (102 robustness) msd:MYSTI_03222 (691 target-flexibility) (528 robustness) msd:MYSTI_03297 (703 target-flexibility) (319 robustness) msd:MYSTI_03298 (659 target-flexibility) (240 robustness) msd:MYSTI_03397 (734 target-flexibility) (110 robustness) msd:MYSTI_03416 (0 target-flexibility) (0 robustness) msd:MYSTI_03419 (0 target-flexibility) (0 robustness) msd:MYSTI_03443 (358 target-flexibility) (124 robustness) msd:MYSTI_03722 (0 target-flexibility) (0 robustness) msd:MYSTI_03731 (323 target-flexibility) (101 robustness) msd:MYSTI_03738 (0 target-flexibility) (0 robustness) msd:MYSTI_03778 (528 target-flexibility) (157 robustness) msd:MYSTI_03827 (231 target-flexibility) (158 robustness) msd:MYSTI_03888 (0 target-flexibility) (0 robustness) msd:MYSTI_03897 (0 target-flexibility) (0 robustness) msd:MYSTI_03928 (0 target-flexibility) (0 robustness) msd:MYSTI_03947 (343 target-flexibility) (180 robustness) msd:MYSTI_04013 (0 target-flexibility) (0 robustness) msd:MYSTI_04068 (267 target-flexibility) (74 robustness) msd:MYSTI_04345 (67 target-flexibility) (67 robustness) msd:MYSTI_04360 (0 target-flexibility) (0 robustness) msd:MYSTI_04456 (0 target-flexibility) (0 robustness) msd:MYSTI_04459 (1784 target-flexibility) (162 robustness) msd:MYSTI_04466 (0 target-flexibility) (0 robustness) msd:MYSTI_04467 (0 target-flexibility) (0 robustness) msd:MYSTI_04482 (0 target-flexibility) (0 robustness) msd:MYSTI_04507 (752 target-flexibility) (105 robustness) msd:MYSTI_04546 (1385 target-flexibility) (204 robustness) msd:MYSTI_04547 (0 target-flexibility) (0 robustness) msd:MYSTI_04606 (343 target-flexibility) (180 robustness) msd:MYSTI_04683 (701 target-flexibility) (106 robustness) msd:MYSTI_04778 (503 target-flexibility) (78 robustness) msd:MYSTI_04815 (0 target-flexibility) (0 robustness) msd:MYSTI_04872 (659 target-flexibility) (240 robustness) msd:MYSTI_04946 (212 target-flexibility) (73 robustness) msd:MYSTI_05067 (0 target-flexibility) (0 robustness) msd:MYSTI_05093 (1169 target-flexibility) (76 robustness) msd:MYSTI_05139 (752 target-flexibility) (76 robustness) msd:MYSTI_05188 (71 target-flexibility) (71 robustness) msd:MYSTI_05203 (0 target-flexibility) (0 robustness) msd:MYSTI_05226 (703 target-flexibility) (319 robustness) msd:MYSTI_05228 (659 target-flexibility) (240 robustness) msd:MYSTI_05229 (503 target-flexibility) (78 robustness) msd:MYSTI_05230 (530 target-flexibility) (162 robustness) msd:MYSTI_05360 (752 target-flexibility) (105 robustness) msd:MYSTI_05450 (703 target-flexibility) (319 robustness) msd:MYSTI_05492 (358 target-flexibility) (124 robustness) msd:MYSTI_05549 (734 target-flexibility) (110 robustness) msd:MYSTI_05561 (657 target-flexibility) (95 robustness) msd:MYSTI_05851 (1183 target-flexibility) (114 robustness) msd:MYSTI_05889 (1183 target-flexibility) (114 robustness) msd:MYSTI_05921 (0 target-flexibility) (0 robustness) msd:MYSTI_06076 (228 target-flexibility) (83 robustness) msd:MYSTI_06140 (1183 target-flexibility) (114 robustness) msd:MYSTI_06170 (343 target-flexibility) (180 robustness) msd:MYSTI_06191 (231 target-flexibility) (158 robustness) msd:MYSTI_06198 (67 target-flexibility) (67 robustness) msd:MYSTI_06221 (357 target-flexibility) (115 robustness) msd:MYSTI_06327 (231 target-flexibility) (158 robustness) msd:MYSTI_06393 (701 target-flexibility) (106 robustness) msd:MYSTI_06394 (228 target-flexibility) (83 robustness) msd:MYSTI_06468 (790 target-flexibility) (134 robustness) msd:MYSTI_06547 (239 target-flexibility) (99 robustness) msd:MYSTI_06570 (231 target-flexibility) (158 robustness) msd:MYSTI_06617 (659 target-flexibility) (240 robustness) msd:MYSTI_06805 (222 target-flexibility) (83 robustness) msd:MYSTI_06833 (1041 target-flexibility) (243 robustness) msd:MYSTI_06919 (1784 target-flexibility) (162 robustness) msd:MYSTI_06940 (0 target-flexibility) (0 robustness) msd:MYSTI_07032 (1183 target-flexibility) (114 robustness) msd:MYSTI_07106 (0 target-flexibility) (0 robustness) msd:MYSTI_07118 (154 target-flexibility) (80 robustness) msd:MYSTI_07249 (796 target-flexibility) (85 robustness) msd:MYSTI_07288 (138 target-flexibility) (138 robustness) msd:MYSTI_07451 (0 target-flexibility) (0 robustness) msd:MYSTI_07506 (659 target-flexibility) (240 robustness) msd:MYSTI_07724 (336 target-flexibility) (81 robustness) msd:MYSTI_07749 (657 target-flexibility) (95 robustness) msd:MYSTI_07831 (659 target-flexibility) (240 robustness) msd:MYSTI_08015 (1041 target-flexibility) (243 robustness) msd:MYSTI_08065 (0 target-flexibility) (0 robustness) msd:MYSTI_08093 (0 target-flexibility) (0 robustness) mxa:MXAN_0110 (0 target-flexibility) (0 robustness) mxa:MXAN_0147 (343 target-flexibility) (180 robustness) mxa:MXAN_0211 (659 target-flexibility) (240 robustness) mxa:MXAN_0215 (1108 target-flexibility) (319 robustness) mxa:MXAN_0278 (323 target-flexibility) (101 robustness) mxa:MXAN_0318 (0 target-flexibility) (0 robustness) mxa:MXAN_0358 (222 target-flexibility) (83 robustness) mxa:MXAN_0395 (80 target-flexibility) (80 robustness) mxa:MXAN_0407 (924 target-flexibility) (101 robustness) mxa:MXAN_0501 (796 target-flexibility) (85 robustness) mxa:MXAN_0531 (1385 target-flexibility) (204 robustness) mxa:MXAN_0537 (0 target-flexibility) (0 robustness) mxa:MXAN_0853 (1108 target-flexibility) (319 robustness) mxa:MXAN_0912 (357 target-flexibility) (115 robustness) mxa:MXAN_0915 (659 target-flexibility) (240 robustness) mxa:MXAN_0949 (790 target-flexibility) (134 robustness) mxa:MXAN_0992 (528 target-flexibility) (157 robustness) mxa:MXAN_1039 (154 target-flexibility) (80 robustness) mxa:MXAN_1103 (732 target-flexibility) (78 robustness) mxa:MXAN_1271 (357 target-flexibility) (102 robustness) mxa:MXAN_1283 (434 target-flexibility) (67 robustness) mxa:MXAN_1362 (0 target-flexibility) (0 robustness) mxa:MXAN_1386 (796 target-flexibility) (85 robustness) mxa:MXAN_1438 (336 target-flexibility) (81 robustness) mxa:MXAN_1528 (0 target-flexibility) (0 robustness) mxa:MXAN_1571 (528 target-flexibility) (157 robustness) mxa:MXAN_1595 (0 target-flexibility) (0 robustness) mxa:MXAN_1933 (691 target-flexibility) (528 robustness) mxa:MXAN_1947 (0 target-flexibility) (0 robustness) mxa:MXAN_2352 (0 target-flexibility) (0 robustness) mxa:MXAN_2358 (239 target-flexibility) (99 robustness) mxa:MXAN_2536 (0 target-flexibility) (0 robustness) mxa:MXAN_2543 (530 target-flexibility) (162 robustness) mxa:MXAN_2570 (790 target-flexibility) (134 robustness) mxa:MXAN_2675 (357 target-flexibility) (102 robustness) mxa:MXAN_2800 (691 target-flexibility) (528 robustness) mxa:MXAN_2925 (734 target-flexibility) (110 robustness) mxa:MXAN_2959 (0 target-flexibility) (0 robustness) mxa:MXAN_2983 (358 target-flexibility) (124 robustness) mxa:MXAN_3330 (343 target-flexibility) (180 robustness) mxa:MXAN_3385 (0 target-flexibility) (0 robustness) mxa:MXAN_3386 (1385 target-flexibility) (204 robustness) mxa:MXAN_3466 (752 target-flexibility) (105 robustness) mxa:MXAN_3506 (0 target-flexibility) (0 robustness) mxa:MXAN_3507 (0 target-flexibility) (0 robustness) mxa:MXAN_3514 (1784 target-flexibility) (162 robustness) mxa:MXAN_3518 (0 target-flexibility) (0 robustness) mxa:MXAN_3519 (924 target-flexibility) (101 robustness) mxa:MXAN_3537 (289 target-flexibility) (73 robustness) mxa:MXAN_3591 (0 target-flexibility) (0 robustness) mxa:MXAN_3969 (343 target-flexibility) (180 robustness) mxa:MXAN_3987 (0 target-flexibility) (0 robustness) mxa:MXAN_4027 (0 target-flexibility) (0 robustness) mxa:MXAN_4038 (0 target-flexibility) (0 robustness) mxa:MXAN_4051 (0 target-flexibility) (0 robustness) mxa:MXAN_4097 (231 target-flexibility) (158 robustness) mxa:MXAN_4171 (528 target-flexibility) (157 robustness) mxa:MXAN_4212 (0 target-flexibility) (0 robustness) mxa:MXAN_4219 (323 target-flexibility) (101 robustness) mxa:MXAN_4228 (0 target-flexibility) (0 robustness) mxa:MXAN_4370 (659 target-flexibility) (240 robustness) mxa:MXAN_4460 (212 target-flexibility) (73 robustness) mxa:MXAN_4613 (0 target-flexibility) (0 robustness) mxa:MXAN_4684 (752 target-flexibility) (76 robustness) mxa:MXAN_4725 (339 target-flexibility) (98 robustness) mxa:MXAN_4731 (71 target-flexibility) (71 robustness) mxa:MXAN_4745 (0 target-flexibility) (0 robustness) mxa:MXAN_4768 (703 target-flexibility) (319 robustness) mxa:MXAN_4770 (659 target-flexibility) (240 robustness) mxa:MXAN_4772 (530 target-flexibility) (162 robustness) mxa:MXAN_4877 (752 target-flexibility) (105 robustness) mxa:MXAN_5001 (358 target-flexibility) (124 robustness) mxa:MXAN_5057 (734 target-flexibility) (110 robustness) mxa:MXAN_5075 (657 target-flexibility) (95 robustness) mxa:MXAN_5358 (0 target-flexibility) (0 robustness) mxa:MXAN_5578 (343 target-flexibility) (180 robustness) mxa:MXAN_5601 (231 target-flexibility) (158 robustness) mxa:MXAN_5608 (67 target-flexibility) (67 robustness) mxa:MXAN_5609 (239 target-flexibility) (67 robustness) mxa:MXAN_5630 (357 target-flexibility) (115 robustness) mxa:MXAN_5741 (231 target-flexibility) (158 robustness) mxa:MXAN_5856 (790 target-flexibility) (134 robustness) mxa:MXAN_5928 (697 target-flexibility) (78 robustness) mxa:MXAN_5929 (239 target-flexibility) (99 robustness) mxa:MXAN_5951 (231 target-flexibility) (158 robustness) mxa:MXAN_6112 (0 target-flexibility) (0 robustness) mxa:MXAN_6220 (222 target-flexibility) (83 robustness) mxa:MXAN_6299 (1784 target-flexibility) (162 robustness) mxa:MXAN_6319 (0 target-flexibility) (0 robustness) mxa:MXAN_6393 (339 target-flexibility) (98 robustness) mxa:MXAN_6395 (703 target-flexibility) (319 robustness) mxa:MXAN_6398 (659 target-flexibility) (240 robustness) mxa:MXAN_6399 (659 target-flexibility) (240 robustness) mxa:MXAN_6400 (703 target-flexibility) (319 robustness) mxa:MXAN_6431 (0 target-flexibility) (0 robustness) mxa:MXAN_6497 (154 target-flexibility) (80 robustness) mxa:MXAN_6731 (697 target-flexibility) (78 robustness) mxa:MXAN_6859 (0 target-flexibility) (0 robustness) mxa:MXAN_6909 (659 target-flexibility) (240 robustness) mxa:MXAN_7138 (336 target-flexibility) (81 robustness) mxa:MXAN_7156 (657 target-flexibility) (95 robustness) mxa:MXAN_7413 (0 target-flexibility) (0 robustness) mym:A176_000033 (706 target-flexibility) (173 robustness) mym:A176_000388 (154 target-flexibility) (80 robustness) mym:A176_000459 (0 target-flexibility) (0 robustness) mym:A176_000489 (703 target-flexibility) (319 robustness) mym:A176_000490 (659 target-flexibility) (240 robustness) mym:A176_000491 (659 target-flexibility) (240 robustness) mym:A176_000494 (703 target-flexibility) (319 robustness) mym:A176_000496 (339 target-flexibility) (98 robustness) mym:A176_000578 (0 target-flexibility) (0 robustness) mym:A176_000601 (1784 target-flexibility) (162 robustness) mym:A176_000635 (0 target-flexibility) (0 robustness) mym:A176_000682 (222 target-flexibility) (83 robustness) mym:A176_000945 (231 target-flexibility) (158 robustness) mym:A176_000967 (239 target-flexibility) (99 robustness) mym:A176_001048 (790 target-flexibility) (134 robustness) mym:A176_001167 (231 target-flexibility) (158 robustness) mym:A176_001288 (357 target-flexibility) (115 robustness) mym:A176_001320 (231 target-flexibility) (158 robustness) mym:A176_001362 (343 target-flexibility) (180 robustness) mym:A176_001499 (0 target-flexibility) (0 robustness) mym:A176_001554 (0 target-flexibility) (0 robustness) mym:A176_001811 (657 target-flexibility) (95 robustness) mym:A176_001826 (734 target-flexibility) (110 robustness) mym:A176_001887 (358 target-flexibility) (124 robustness) mym:A176_001932 (703 target-flexibility) (319 robustness) mym:A176_002007 (752 target-flexibility) (105 robustness) mym:A176_002120 (530 target-flexibility) (162 robustness) mym:A176_002122 (659 target-flexibility) (240 robustness) mym:A176_002124 (703 target-flexibility) (319 robustness) mym:A176_002147 (0 target-flexibility) (0 robustness) mym:A176_002161 (71 target-flexibility) (71 robustness) mym:A176_002167 (339 target-flexibility) (98 robustness) mym:A176_002210 (752 target-flexibility) (76 robustness) mym:A176_002255 (1169 target-flexibility) (76 robustness) mym:A176_002284 (0 target-flexibility) (0 robustness) mym:A176_002437 (212 target-flexibility) (73 robustness) mym:A176_002532 (659 target-flexibility) (240 robustness) mym:A176_002672 (0 target-flexibility) (0 robustness) mym:A176_002681 (323 target-flexibility) (101 robustness) mym:A176_002689 (0 target-flexibility) (0 robustness) mym:A176_002734 (528 target-flexibility) (157 robustness) mym:A176_002773 (706 target-flexibility) (173 robustness) mym:A176_002800 (231 target-flexibility) (158 robustness) mym:A176_002870 (0 target-flexibility) (0 robustness) mym:A176_002879 (0 target-flexibility) (0 robustness) mym:A176_002926 (0 target-flexibility) (0 robustness) mym:A176_002955 (343 target-flexibility) (180 robustness) mym:A176_002984 (0 target-flexibility) (0 robustness) mym:A176_003317 (0 target-flexibility) (0 robustness) mym:A176_003393 (0 target-flexibility) (0 robustness) mym:A176_003399 (1784 target-flexibility) (162 robustness) mym:A176_003407 (0 target-flexibility) (0 robustness) mym:A176_003408 (0 target-flexibility) (0 robustness) mym:A176_003458 (752 target-flexibility) (105 robustness) mym:A176_003560 (1385 target-flexibility) (204 robustness) mym:A176_003561 (0 target-flexibility) (0 robustness) mym:A176_003617 (343 target-flexibility) (180 robustness) mym:A176_003849 (0 target-flexibility) (0 robustness) mym:A176_003863 (1041 target-flexibility) (243 robustness) mym:A176_004027 (358 target-flexibility) (124 robustness) mym:A176_004054 (0 target-flexibility) (0 robustness) mym:A176_004057 (0 target-flexibility) (0 robustness) mym:A176_004084 (734 target-flexibility) (110 robustness) mym:A176_004217 (691 target-flexibility) (528 robustness) mym:A176_004236 (703 target-flexibility) (319 robustness) mym:A176_004355 (357 target-flexibility) (102 robustness) mym:A176_004468 (790 target-flexibility) (134 robustness) mym:A176_004497 (530 target-flexibility) (162 robustness) mym:A176_004505 (0 target-flexibility) (0 robustness) mym:A176_004685 (239 target-flexibility) (99 robustness) mym:A176_004693 (0 target-flexibility) (0 robustness) mym:A176_004884 (358 target-flexibility) (124 robustness) mym:A176_005044 (0 target-flexibility) (0 robustness) mym:A176_005054 (691 target-flexibility) (528 robustness) mym:A176_005227 (0 target-flexibility) (0 robustness) mym:A176_005386 (0 target-flexibility) (0 robustness) mym:A176_005409 (528 target-flexibility) (157 robustness) mym:A176_005454 (0 target-flexibility) (0 robustness) mym:A176_005543 (336 target-flexibility) (81 robustness) mym:A176_005616 (796 target-flexibility) (85 robustness) mym:A176_005642 (0 target-flexibility) (0 robustness) mym:A176_005718 (357 target-flexibility) (102 robustness) mym:A176_005864 (732 target-flexibility) (78 robustness) mym:A176_005929 (154 target-flexibility) (80 robustness) mym:A176_005981 (528 target-flexibility) (157 robustness) mym:A176_006029 (790 target-flexibility) (134 robustness) mym:A176_006064 (659 target-flexibility) (240 robustness) mym:A176_006068 (357 target-flexibility) (115 robustness) mym:A176_006490 (0 target-flexibility) (0 robustness) mym:A176_006496 (1385 target-flexibility) (204 robustness) mym:A176_006642 (222 target-flexibility) (83 robustness) mym:A176_006715 (323 target-flexibility) (101 robustness) mym:A176_006784 (659 target-flexibility) (240 robustness) mym:A176_006864 (343 target-flexibility) (180 robustness) mym:A176_006908 (0 target-flexibility) (0 robustness) mym:A176_007109 (0 target-flexibility) (0 robustness) mym:A176_007168 (1041 target-flexibility) (243 robustness) mym:A176_007377 (657 target-flexibility) (95 robustness) mym:A176_007396 (336 target-flexibility) (81 robustness) mym:A176_007563 (0 target-flexibility) (0 robustness) mym:A176_007648 (659 target-flexibility) (240 robustness) pace:A6070_00050 (73 target-flexibility) (73 robustness) pace:A6070_00320 (358 target-flexibility) (124 robustness) pace:A6070_00575 (1041 target-flexibility) (243 robustness) pace:A6070_00600 (138 target-flexibility) (138 robustness) pace:A6070_01225 (1108 target-flexibility) (319 robustness) pace:A6070_01315 (528 target-flexibility) (157 robustness) pace:A6070_01515 (138 target-flexibility) (138 robustness) pace:A6070_01580 (691 target-flexibility) (528 robustness) pace:A6070_01735 (91 target-flexibility) (91 robustness) pace:A6070_01780 (323 target-flexibility) (101 robustness) pace:A6070_01880 (796 target-flexibility) (85 robustness) pace:A6070_02565 (613 target-flexibility) (72 robustness) pace:A6070_02940 (222 target-flexibility) (83 robustness) pace:A6070_03160 (528 target-flexibility) (157 robustness) pace:A6070_03240 (138 target-flexibility) (66 robustness) pace:A6070_03835 (212 target-flexibility) (73 robustness) pace:A6070_04095 (686 target-flexibility) (192 robustness) pace:A6070_04115 (91 target-flexibility) (91 robustness) pace:A6070_04145 (0 target-flexibility) (0 robustness) pace:A6070_04260 (239 target-flexibility) (67 robustness) pace:A6070_04265 (67 target-flexibility) (67 robustness) pace:A6070_04300 (231 target-flexibility) (158 robustness) pace:A6070_04750 (0 target-flexibility) (0 robustness) pace:A6070_04955 (686 target-flexibility) (192 robustness) pace:A6070_04975 (71 target-flexibility) (71 robustness) pace:A6070_05010 (139 target-flexibility) (66 robustness) pace:A6070_05320 (0 target-flexibility) (0 robustness) pace:A6070_05385 (732 target-flexibility) (78 robustness) pace:A6070_05405 (600 target-flexibility) (126 robustness) pace:A6070_05790 (0 target-flexibility) (0 robustness) pace:A6070_05920 (1108 target-flexibility) (319 robustness) pace:A6070_06035 (0 target-flexibility) (0 robustness) pace:A6070_06075 (0 target-flexibility) (0 robustness) pace:A6070_06120 (0 target-flexibility) (0 robustness) pace:A6070_06385 (323 target-flexibility) (101 robustness) pace:A6070_06445 (231 target-flexibility) (158 robustness) pace:A6070_06450 (231 target-flexibility) (158 robustness) pace:A6070_06665 (691 target-flexibility) (528 robustness) pace:A6070_06815 (1169 target-flexibility) (76 robustness) pace:A6070_06835 (139 target-flexibility) (66 robustness) pace:A6070_07185 (897 target-flexibility) (71 robustness) pace:A6070_07200 (405 target-flexibility) (169 robustness) pace:A6070_07305 (0 target-flexibility) (0 robustness) pace:A6070_07325 (0 target-flexibility) (0 robustness) pace:A6070_07525 (821 target-flexibility) (137 robustness) pace:A6070_07975 (613 target-flexibility) (72 robustness) pace:A6070_08045 (358 target-flexibility) (124 robustness) pace:A6070_08275 (841 target-flexibility) (126 robustness) pace:A6070_08290 (902 target-flexibility) (228 robustness) pace:A6070_09000 (0 target-flexibility) (0 robustness) pace:A6070_10090 (752 target-flexibility) (76 robustness) pace:A6070_10120 (0 target-flexibility) (0 robustness) pace:A6070_10395 (841 target-flexibility) (126 robustness) pace:A6070_10675 (0 target-flexibility) (0 robustness) pace:A6070_10805 (0 target-flexibility) (0 robustness) pace:A6070_11125 (600 target-flexibility) (126 robustness) pace:A6070_12850 (0 target-flexibility) (0 robustness) pace:A6070_13030 (821 target-flexibility) (137 robustness) pace:A6070_13195 (0 target-flexibility) (0 robustness) pace:A6070_13200 (0 target-flexibility) (0 robustness) pace:A6070_13365 (1041 target-flexibility) (243 robustness) pace:A6070_13370 (1041 target-flexibility) (243 robustness) pace:A6070_13415 (600 target-flexibility) (126 robustness) pace:A6070_13790 (405 target-flexibility) (169 robustness) pace:A6070_13980 (0 target-flexibility) (0 robustness) pace:A6070_13985 (0 target-flexibility) (0 robustness) pace:A6070_14230 (902 target-flexibility) (228 robustness) pace:A6070_14605 (0 target-flexibility) (0 robustness) pace:A6070_14615 (0 target-flexibility) (0 robustness) pace:A6070_14665 (80 target-flexibility) (80 robustness) pace:A6070_14775 (73 target-flexibility) (73 robustness) pca:Pcar_0050 (358 target-flexibility) (124 robustness) pca:Pcar_0092 (334 target-flexibility) (71 robustness) pca:Pcar_0114 (138 target-flexibility) (138 robustness) pca:Pcar_0189 (902 target-flexibility) (228 robustness) pca:Pcar_0251 (0 target-flexibility) (0 robustness) pca:Pcar_0255 (0 target-flexibility) (0 robustness) pca:Pcar_0266 (80 target-flexibility) (80 robustness) pca:Pcar_0337 (91 target-flexibility) (91 robustness) pca:Pcar_0342 (0 target-flexibility) (0 robustness) pca:Pcar_0347 (323 target-flexibility) (101 robustness) pca:Pcar_0374 (691 target-flexibility) (528 robustness) pca:Pcar_0482 (0 target-flexibility) (0 robustness) pca:Pcar_0607 (0 target-flexibility) (0 robustness) pca:Pcar_0824 (279 target-flexibility) (126 robustness) pca:Pcar_1007 (841 target-flexibility) (126 robustness) pca:Pcar_1033 (0 target-flexibility) (0 robustness) pca:Pcar_1040 (752 target-flexibility) (76 robustness) pca:Pcar_1121 (902 target-flexibility) (228 robustness) pca:Pcar_1129 (0 target-flexibility) (0 robustness) pca:Pcar_1244 (686 target-flexibility) (192 robustness) pca:Pcar_1248 (71 target-flexibility) (71 robustness) pca:Pcar_1255 (139 target-flexibility) (66 robustness) pca:Pcar_1320 (0 target-flexibility) (0 robustness) pca:Pcar_1326 (732 target-flexibility) (78 robustness) pca:Pcar_1331 (600 target-flexibility) (126 robustness) pca:Pcar_1413 (0 target-flexibility) (0 robustness) pca:Pcar_1436 (1108 target-flexibility) (319 robustness) pca:Pcar_1438 (659 target-flexibility) (240 robustness) pca:Pcar_1440 (703 target-flexibility) (319 robustness) pca:Pcar_1460 (0 target-flexibility) (0 robustness) pca:Pcar_1466 (0 target-flexibility) (0 robustness) pca:Pcar_1467 (0 target-flexibility) (0 robustness) pca:Pcar_1486 (323 target-flexibility) (101 robustness) pca:Pcar_1495 (139 target-flexibility) (66 robustness) pca:Pcar_1514 (279 target-flexibility) (126 robustness) pca:Pcar_1534 (528 target-flexibility) (157 robustness) pca:Pcar_1569 (0 target-flexibility) (0 robustness) pca:Pcar_1594 (0 target-flexibility) (0 robustness) pca:Pcar_1607 (0 target-flexibility) (0 robustness) pca:Pcar_1615 (897 target-flexibility) (71 robustness) pca:Pcar_1632 (0 target-flexibility) (0 robustness) pca:Pcar_1667 (1169 target-flexibility) (76 robustness) pca:Pcar_1692 (691 target-flexibility) (528 robustness) pca:Pcar_1718 (528 target-flexibility) (157 robustness) pca:Pcar_1722 (0 target-flexibility) (0 robustness) pca:Pcar_1727 (334 target-flexibility) (71 robustness) pca:Pcar_1776 (243 target-flexibility) (97 robustness) pca:Pcar_1804 (0 target-flexibility) (0 robustness) pca:Pcar_1805 (796 target-flexibility) (85 robustness) pca:Pcar_1806 (0 target-flexibility) (0 robustness) pca:Pcar_1807 (0 target-flexibility) (0 robustness) pca:Pcar_1841 (358 target-flexibility) (124 robustness) pca:Pcar_1860 (358 target-flexibility) (124 robustness) pca:Pcar_1907 (841 target-flexibility) (126 robustness) pca:Pcar_1910 (902 target-flexibility) (228 robustness) pca:Pcar_1916 (76 target-flexibility) (76 robustness) pca:Pcar_2115 (0 target-flexibility) (0 robustness) pca:Pcar_2150 (241 target-flexibility) (71 robustness) pca:Pcar_2174 (243 target-flexibility) (97 robustness) pca:Pcar_2192 (241 target-flexibility) (71 robustness) pca:Pcar_2206 (67 target-flexibility) (67 robustness) pca:Pcar_2207 (239 target-flexibility) (67 robustness) pca:Pcar_2230 (0 target-flexibility) (0 robustness) pca:Pcar_2236 (91 target-flexibility) (91 robustness) pca:Pcar_2240 (686 target-flexibility) (192 robustness) pca:Pcar_2254 (600 target-flexibility) (126 robustness) pca:Pcar_2315 (212 target-flexibility) (73 robustness) pca:Pcar_2415 (138 target-flexibility) (66 robustness) pca:Pcar_2430 (528 target-flexibility) (157 robustness) pca:Pcar_2435 (706 target-flexibility) (173 robustness) pca:Pcar_2455 (222 target-flexibility) (83 robustness) pca:Pcar_2506 (0 target-flexibility) (0 robustness) pca:Pcar_2593 (0 target-flexibility) (0 robustness) pca:Pcar_2596 (0 target-flexibility) (0 robustness) pca:Pcar_2624 (600 target-flexibility) (126 robustness) pca:Pcar_2664 (703 target-flexibility) (319 robustness) pca:Pcar_2667 (659 target-flexibility) (240 robustness) pca:Pcar_2684 (0 target-flexibility) (0 robustness) pca:Pcar_2685 (0 target-flexibility) (0 robustness) pca:Pcar_2719 (1041 target-flexibility) (243 robustness) pca:Pcar_2720 (1041 target-flexibility) (243 robustness) pca:Pcar_2778 (76 target-flexibility) (76 robustness) pca:Pcar_2847 (0 target-flexibility) (0 robustness) pca:Pcar_2933 (796 target-flexibility) (85 robustness) pca:Pcar_2943 (138 target-flexibility) (138 robustness) pca:Pcar_2987 (1108 target-flexibility) (319 robustness) pca:Pcar_3005 (528 target-flexibility) (157 robustness) pca:Pcar_3011 (706 target-flexibility) (173 robustness) pca:Pcar_3106 (0 target-flexibility) (0 robustness) pca:Pcar_3125 (1041 target-flexibility) (243 robustness) pef:A7E78_00020 (0 target-flexibility) (0 robustness) pef:A7E78_00045 (350 target-flexibility) (84 robustness) pef:A7E78_00095 (290 target-flexibility) (63 robustness) pef:A7E78_00335 (0 target-flexibility) (0 robustness) pef:A7E78_00350 (0 target-flexibility) (0 robustness) pef:A7E78_00355 (0 target-flexibility) (0 robustness) pef:A7E78_00360 (0 target-flexibility) (0 robustness) pef:A7E78_01045 (0 target-flexibility) (0 robustness) pef:A7E78_01225 (290 target-flexibility) (63 robustness) pef:A7E78_01330 (71 target-flexibility) (71 robustness) pef:A7E78_01430 (0 target-flexibility) (0 robustness) pef:A7E78_01440 (0 target-flexibility) (0 robustness) pef:A7E78_01445 (0 target-flexibility) (0 robustness) pef:A7E78_01785 (613 target-flexibility) (72 robustness) pef:A7E78_01825 (1108 target-flexibility) (319 robustness) pef:A7E78_02235 (0 target-flexibility) (0 robustness) pef:A7E78_02275 (691 target-flexibility) (528 robustness) pef:A7E78_02355 (691 target-flexibility) (528 robustness) pef:A7E78_02400 (0 target-flexibility) (0 robustness) pef:A7E78_02580 (600 target-flexibility) (126 robustness) pef:A7E78_02600 (732 target-flexibility) (78 robustness) pef:A7E78_02750 (1169 target-flexibility) (76 robustness) pef:A7E78_02810 (231 target-flexibility) (158 robustness) pef:A7E78_02815 (231 target-flexibility) (158 robustness) pef:A7E78_02985 (897 target-flexibility) (71 robustness) pef:A7E78_03040 (0 target-flexibility) (0 robustness) pef:A7E78_03600 (528 target-flexibility) (157 robustness) pef:A7E78_03620 (0 target-flexibility) (0 robustness) pef:A7E78_03875 (0 target-flexibility) (0 robustness) pef:A7E78_04140 (358 target-flexibility) (124 robustness) pef:A7E78_04420 (528 target-flexibility) (157 robustness) pef:A7E78_04585 (358 target-flexibility) (124 robustness) pef:A7E78_04590 (358 target-flexibility) (124 robustness) pef:A7E78_04875 (434 target-flexibility) (67 robustness) pef:A7E78_04890 (841 target-flexibility) (126 robustness) pef:A7E78_05185 (691 target-flexibility) (528 robustness) pef:A7E78_05540 (350 target-flexibility) (189 robustness) pef:A7E78_05805 (497 target-flexibility) (186 robustness) pef:A7E78_05895 (752 target-flexibility) (76 robustness) pef:A7E78_05905 (289 target-flexibility) (73 robustness) pef:A7E78_06000 (841 target-flexibility) (126 robustness) pef:A7E78_06095 (0 target-flexibility) (0 robustness) pef:A7E78_06150 (0 target-flexibility) (0 robustness) pef:A7E78_06630 (212 target-flexibility) (73 robustness) pef:A7E78_07325 (686 target-flexibility) (192 robustness) pef:A7E78_07335 (686 target-flexibility) (192 robustness) pef:A7E78_07855 (600 target-flexibility) (126 robustness) pef:A7E78_08220 (0 target-flexibility) (0 robustness) pef:A7E78_08225 (0 target-flexibility) (0 robustness) pef:A7E78_08565 (691 target-flexibility) (528 robustness) pef:A7E78_08985 (528 target-flexibility) (157 robustness) pef:A7E78_09055 (1108 target-flexibility) (319 robustness) pef:A7E78_10095 (334 target-flexibility) (71 robustness) pef:A7E78_10390 (1041 target-flexibility) (243 robustness) pef:A7E78_10450 (138 target-flexibility) (138 robustness) pef:A7E78_10690 (358 target-flexibility) (124 robustness) pef:A7E78_10820 (0 target-flexibility) (0 robustness) pef:A7E78_10830 (0 target-flexibility) (0 robustness) pef:A7E78_10835 (0 target-flexibility) (0 robustness) pef:A7E78_10875 (350 target-flexibility) (189 robustness) pef:A7E78_11135 (350 target-flexibility) (84 robustness) pef:A7E78_11145 (1041 target-flexibility) (243 robustness) pef:A7E78_11150 (1041 target-flexibility) (243 robustness) pef:A7E78_11340 (600 target-flexibility) (126 robustness) pef:A7E78_11715 (796 target-flexibility) (85 robustness) pef:A7E78_11740 (0 target-flexibility) (0 robustness) pef:A7E78_11875 (0 target-flexibility) (0 robustness) pef:A7E78_12325 (138 target-flexibility) (138 robustness) pef:A7E78_12430 (497 target-flexibility) (186 robustness) pef:A7E78_12505 (600 target-flexibility) (126 robustness) pef:A7E78_12525 (334 target-flexibility) (71 robustness) pef:A7E78_13175 (613 target-flexibility) (72 robustness) pef:A7E78_13520 (222 target-flexibility) (83 robustness) pef:A7E78_13750 (528 target-flexibility) (157 robustness) pef:A7E78_13795 (138 target-flexibility) (66 robustness) pef:A7E78_14195 (231 target-flexibility) (158 robustness) ppd:Ppro_0016 (1108 target-flexibility) (319 robustness) ppd:Ppro_0050 (821 target-flexibility) (137 robustness) ppd:Ppro_0301 (691 target-flexibility) (528 robustness) ppd:Ppro_0342 (339 target-flexibility) (98 robustness) ppd:Ppro_0343 (600 target-flexibility) (126 robustness) ppd:Ppro_0387 (0 target-flexibility) (0 robustness) ppd:Ppro_0415 (0 target-flexibility) (0 robustness) ppd:Ppro_0454 (0 target-flexibility) (0 robustness) ppd:Ppro_0579 (267 target-flexibility) (74 robustness) ppd:Ppro_0905 (659 target-flexibility) (240 robustness) ppd:Ppro_0907 (703 target-flexibility) (319 robustness) ppd:Ppro_1029 (219 target-flexibility) (63 robustness) ppd:Ppro_1034 (91 target-flexibility) (91 robustness) ppd:Ppro_1046 (1385 target-flexibility) (204 robustness) ppd:Ppro_1177 (0 target-flexibility) (0 robustness) ppd:Ppro_1191 (1169 target-flexibility) (76 robustness) ppd:Ppro_1291 (686 target-flexibility) (192 robustness) ppd:Ppro_1453 (0 target-flexibility) (0 robustness) ppd:Ppro_1518 (659 target-flexibility) (240 robustness) ppd:Ppro_1520 (0 target-flexibility) (0 robustness) ppd:Ppro_1580 (212 target-flexibility) (73 robustness) ppd:Ppro_1669 (0 target-flexibility) (0 robustness) ppd:Ppro_1725 (405 target-flexibility) (70 robustness) ppd:Ppro_1731 (0 target-flexibility) (0 robustness) ppd:Ppro_1832 (528 target-flexibility) (157 robustness) ppd:Ppro_2098 (0 target-flexibility) (0 robustness) ppd:Ppro_2118 (0 target-flexibility) (0 robustness) ppd:Ppro_2240 (0 target-flexibility) (0 robustness) ppd:Ppro_2329 (752 target-flexibility) (76 robustness) ppd:Ppro_2466 (821 target-flexibility) (137 robustness) ppd:Ppro_2529 (897 target-flexibility) (71 robustness) ppd:Ppro_2540 (0 target-flexibility) (0 robustness) ppd:Ppro_2556 (902 target-flexibility) (228 robustness) ppd:Ppro_2596 (91 target-flexibility) (91 robustness) ppd:Ppro_3055 (0 target-flexibility) (0 robustness) ppd:Ppro_3288 (70 target-flexibility) (70 robustness) ppd:Ppro_3293 (67 target-flexibility) (67 robustness) pprf:DPRO_0148 (841 target-flexibility) (126 robustness) pprf:DPRO_0151 (434 target-flexibility) (67 robustness) pprf:DPRO_0163 (0 target-flexibility) (0 robustness) pprf:DPRO_0184 (138 target-flexibility) (138 robustness) pprf:DPRO_0282 (279 target-flexibility) (126 robustness) pprf:DPRO_0296 (711 target-flexibility) (104 robustness) pprf:DPRO_0434 (330 target-flexibility) (76 robustness) pprf:DPRO_0650 (706 target-flexibility) (173 robustness) pprf:DPRO_0665 (902 target-flexibility) (228 robustness) pprf:DPRO_0799 (528 target-flexibility) (157 robustness) pprf:DPRO_0802 (222 target-flexibility) (83 robustness) pprf:DPRO_0842 (841 target-flexibility) (126 robustness) pprf:DPRO_0843 (600 target-flexibility) (126 robustness) pprf:DPRO_0869 (902 target-flexibility) (228 robustness) pprf:DPRO_0870 (902 target-flexibility) (228 robustness) pprf:DPRO_0895 (0 target-flexibility) (0 robustness) pprf:DPRO_0920 (138 target-flexibility) (138 robustness) pprf:DPRO_1057 (711 target-flexibility) (104 robustness) pprf:DPRO_1084 (0 target-flexibility) (0 robustness) pprf:DPRO_1221 (0 target-flexibility) (0 robustness) pprf:DPRO_1333 (0 target-flexibility) (0 robustness) pprf:DPRO_1336 (0 target-flexibility) (0 robustness) pprf:DPRO_1432 (0 target-flexibility) (0 robustness) pprf:DPRO_1450 (0 target-flexibility) (0 robustness) pprf:DPRO_1502 (790 target-flexibility) (134 robustness) pprf:DPRO_1557 (1385 target-flexibility) (204 robustness) pprf:DPRO_1577 (414 target-flexibility) (96 robustness) pprf:DPRO_1580 (600 target-flexibility) (126 robustness) pprf:DPRO_1581 (390 target-flexibility) (74 robustness) pprf:DPRO_1583 (1784 target-flexibility) (162 robustness) pprf:DPRO_1584 (330 target-flexibility) (76 robustness) pprf:DPRO_1586 (1041 target-flexibility) (243 robustness) pprf:DPRO_1657 (80 target-flexibility) (80 robustness) pprf:DPRO_1802 (790 target-flexibility) (134 robustness) pprf:DPRO_1845 (138 target-flexibility) (138 robustness) pprf:DPRO_1856 (0 target-flexibility) (0 robustness) pprf:DPRO_1945 (0 target-flexibility) (0 robustness) pprf:DPRO_1966 (902 target-flexibility) (228 robustness) pprf:DPRO_2030 (0 target-flexibility) (0 robustness) pprf:DPRO_2174 (790 target-flexibility) (134 robustness) pprf:DPRO_2239 (879 target-flexibility) (71 robustness) pprf:DPRO_2275 (0 target-flexibility) (0 robustness) pprf:DPRO_2329 (414 target-flexibility) (96 robustness) pprf:DPRO_2330 (1041 target-flexibility) (243 robustness) pprf:DPRO_2444 (358 target-flexibility) (104 robustness) pprf:DPRO_2470 (212 target-flexibility) (73 robustness) pprf:DPRO_2555 (0 target-flexibility) (0 robustness) pprf:DPRO_2602 (0 target-flexibility) (0 robustness) pprf:DPRO_2629 (1385 target-flexibility) (204 robustness) pprf:DPRO_2638 (0 target-flexibility) (0 robustness) pprf:DPRO_2643 (0 target-flexibility) (0 robustness) pprf:DPRO_2705 (1784 target-flexibility) (162 robustness) pprf:DPRO_2839 (686 target-flexibility) (192 robustness) pprf:DPRO_2879 (289 target-flexibility) (73 robustness) pprf:DPRO_2881 (686 target-flexibility) (192 robustness) pprf:DPRO_2976 (358 target-flexibility) (104 robustness) pprf:DPRO_3025 (0 target-flexibility) (0 robustness) pprf:DPRO_3102 (0 target-flexibility) (0 robustness) pprf:DPRO_3319 (706 target-flexibility) (173 robustness) pprf:DPRO_3321 (879 target-flexibility) (71 robustness) pprf:DPRO_3425 (706 target-flexibility) (173 robustness) pprf:DPRO_3768 (0 target-flexibility) (0 robustness) pprf:DPRO_3829 (0 target-flexibility) (0 robustness) pprf:DPRO_3892 (279 target-flexibility) (126 robustness) pprf:DPRO_4008 (390 target-flexibility) (74 robustness) samy:DB32_000011 (241 target-flexibility) (71 robustness) samy:DB32_000113 (231 target-flexibility) (158 robustness) samy:DB32_000220 (659 target-flexibility) (240 robustness) samy:DB32_000279 (703 target-flexibility) (319 robustness) samy:DB32_000329 (175 target-flexibility) (96 robustness) samy:DB32_000330 (686 target-flexibility) (192 robustness) samy:DB32_000455 (138 target-flexibility) (138 robustness) samy:DB32_000467 (497 target-flexibility) (186 robustness) samy:DB32_000470 (357 target-flexibility) (102 robustness) samy:DB32_000588 (657 target-flexibility) (95 robustness) samy:DB32_000657 (703 target-flexibility) (319 robustness) samy:DB32_000680 (0 target-flexibility) (0 robustness) samy:DB32_000949 (659 target-flexibility) (240 robustness) samy:DB32_000965 (0 target-flexibility) (0 robustness) samy:DB32_000992 (0 target-flexibility) (0 robustness) samy:DB32_001023 (752 target-flexibility) (76 robustness) samy:DB32_001141 (1108 target-flexibility) (319 robustness) samy:DB32_001261 (140 target-flexibility) (65 robustness) samy:DB32_001353 (0 target-flexibility) (0 robustness) samy:DB32_001409 (703 target-flexibility) (319 robustness) samy:DB32_001412 (659 target-flexibility) (240 robustness) samy:DB32_001415 (503 target-flexibility) (78 robustness) samy:DB32_001613 (323 target-flexibility) (101 robustness) samy:DB32_001636 (323 target-flexibility) (101 robustness) samy:DB32_001667 (350 target-flexibility) (189 robustness) samy:DB32_001708 (434 target-flexibility) (67 robustness) samy:DB32_001770 (924 target-flexibility) (101 robustness) samy:DB32_001845 (821 target-flexibility) (137 robustness) samy:DB32_001908 (357 target-flexibility) (102 robustness) samy:DB32_001928 (659 target-flexibility) (240 robustness) samy:DB32_002077 (1385 target-flexibility) (204 robustness) samy:DB32_002225 (902 target-flexibility) (228 robustness) samy:DB32_002239 (659 target-flexibility) (240 robustness) samy:DB32_002265 (0 target-flexibility) (0 robustness) samy:DB32_002497 (691 target-flexibility) (528 robustness) samy:DB32_002655 (1183 target-flexibility) (114 robustness) samy:DB32_002852 (0 target-flexibility) (0 robustness) samy:DB32_002924 (503 target-flexibility) (78 robustness) samy:DB32_002947 (350 target-flexibility) (189 robustness) samy:DB32_002954 (0 target-flexibility) (0 robustness) samy:DB32_003077 (528 target-flexibility) (157 robustness) samy:DB32_003101 (902 target-flexibility) (228 robustness) samy:DB32_003115 (902 target-flexibility) (228 robustness) samy:DB32_003116 (1108 target-flexibility) (319 robustness) samy:DB32_003149 (0 target-flexibility) (0 robustness) samy:DB32_003166 (497 target-flexibility) (186 robustness) samy:DB32_003170 (0 target-flexibility) (0 robustness) samy:DB32_003477 (0 target-flexibility) (0 robustness) samy:DB32_003480 (0 target-flexibility) (0 robustness) samy:DB32_003518 (0 target-flexibility) (0 robustness) samy:DB32_003546 (0 target-flexibility) (0 robustness) samy:DB32_003553 (212 target-flexibility) (73 robustness) samy:DB32_003583 (752 target-flexibility) (105 robustness) samy:DB32_003678 (289 target-flexibility) (73 robustness) samy:DB32_003711 (0 target-flexibility) (0 robustness) samy:DB32_003728 (222 target-flexibility) (83 robustness) samy:DB32_003841 (0 target-flexibility) (0 robustness) samy:DB32_003842 (0 target-flexibility) (0 robustness) samy:DB32_003877 (691 target-flexibility) (528 robustness) samy:DB32_003887 (659 target-flexibility) (240 robustness) samy:DB32_003889 (703 target-flexibility) (319 robustness) samy:DB32_003941 (175 target-flexibility) (78 robustness) samy:DB32_003961 (528 target-flexibility) (157 robustness) samy:DB32_003964 (528 target-flexibility) (157 robustness) samy:DB32_003973 (231 target-flexibility) (158 robustness) samy:DB32_004039 (855 target-flexibility) (138 robustness) samy:DB32_004060 (752 target-flexibility) (105 robustness) samy:DB32_004093 (358 target-flexibility) (124 robustness) samy:DB32_004135 (0 target-flexibility) (0 robustness) samy:DB32_004155 (821 target-flexibility) (137 robustness) samy:DB32_004284 (497 target-flexibility) (186 robustness) samy:DB32_004319 (0 target-flexibility) (0 robustness) samy:DB32_004322 (0 target-flexibility) (0 robustness) samy:DB32_004394 (706 target-flexibility) (173 robustness) samy:DB32_004421 (0 target-flexibility) (0 robustness) samy:DB32_004445 (239 target-flexibility) (67 robustness) samy:DB32_004448 (140 target-flexibility) (71 robustness) samy:DB32_004546 (855 target-flexibility) (138 robustness) samy:DB32_004597 (1183 target-flexibility) (114 robustness) samy:DB32_004608 (0 target-flexibility) (0 robustness) samy:DB32_004662 (703 target-flexibility) (319 robustness) samy:DB32_004711 (358 target-flexibility) (124 robustness) samy:DB32_004856 (657 target-flexibility) (95 robustness) samy:DB32_004998 (323 target-flexibility) (101 robustness) samy:DB32_005052 (1041 target-flexibility) (243 robustness) samy:DB32_005101 (528 target-flexibility) (157 robustness) samy:DB32_005105 (358 target-flexibility) (104 robustness) samy:DB32_005118 (1385 target-flexibility) (204 robustness) samy:DB32_005205 (434 target-flexibility) (67 robustness) samy:DB32_005206 (841 target-flexibility) (126 robustness) samy:DB32_005209 (841 target-flexibility) (126 robustness) samy:DB32_005212 (902 target-flexibility) (228 robustness) samy:DB32_005289 (657 target-flexibility) (95 robustness) samy:DB32_005406 (71 target-flexibility) (71 robustness) samy:DB32_005686 (0 target-flexibility) (0 robustness) samy:DB32_005700 (497 target-flexibility) (186 robustness) samy:DB32_005704 (686 target-flexibility) (192 robustness) samy:DB32_005734 (0 target-flexibility) (0 robustness) samy:DB32_005885 (323 target-flexibility) (101 robustness) samy:DB32_005931 (1041 target-flexibility) (243 robustness) samy:DB32_005996 (691 target-flexibility) (528 robustness) samy:DB32_006298 (528 target-flexibility) (157 robustness) samy:DB32_006304 (231 target-flexibility) (158 robustness) samy:DB32_006309 (924 target-flexibility) (101 robustness) samy:DB32_006310 (924 target-flexibility) (101 robustness) samy:DB32_006326 (175 target-flexibility) (78 robustness) samy:DB32_006421 (0 target-flexibility) (0 robustness) samy:DB32_006503 (138 target-flexibility) (138 robustness) samy:DB32_006581 (0 target-flexibility) (0 robustness) samy:DB32_006761 (841 target-flexibility) (126 robustness) samy:DB32_006869 (706 target-flexibility) (173 robustness) samy:DB32_006894 (0 target-flexibility) (0 robustness) samy:DB32_007120 (0 target-flexibility) (0 robustness) samy:DB32_007124 (358 target-flexibility) (104 robustness) samy:DB32_007188 (1108 target-flexibility) (319 robustness) samy:DB32_007196 (0 target-flexibility) (0 robustness) samy:DB32_007268 (790 target-flexibility) (134 robustness) samy:DB32_007373 (175 target-flexibility) (96 robustness) samy:DB32_007469 (0 target-flexibility) (0 robustness) samy:DB32_007585 (734 target-flexibility) (110 robustness) samy:DB32_007648 (0 target-flexibility) (0 robustness) samy:DB32_007837 (1385 target-flexibility) (204 robustness) samy:DB32_007931 (1108 target-flexibility) (319 robustness) samy:DB32_008364 (0 target-flexibility) (0 robustness) samy:DB32_008367 (1108 target-flexibility) (319 robustness) samy:DB32_008421 (734 target-flexibility) (110 robustness) samy:DB32_008496 (0 target-flexibility) (0 robustness) samy:DB32_008540 (241 target-flexibility) (71 robustness) samy:DB32_008570 (691 target-flexibility) (528 robustness) samy:DB32_008592 (140 target-flexibility) (65 robustness) samy:DB32_008649 (231 target-flexibility) (158 robustness) samy:DB32_008650 (231 target-flexibility) (158 robustness) samy:DB32_008655 (1385 target-flexibility) (204 robustness) samy:DB32_008737 (0 target-flexibility) (0 robustness) samy:DB32_008959 (241 target-flexibility) (71 robustness) sat:SYN_00001 (0 target-flexibility) (0 robustness) sat:SYN_00075 (358 target-flexibility) (104 robustness) sat:SYN_00090 (841 target-flexibility) (126 robustness) sat:SYN_00163 (691 target-flexibility) (528 robustness) sat:SYN_00211 (0 target-flexibility) (0 robustness) sat:SYN_00231 (0 target-flexibility) (0 robustness) sat:SYN_00266 (0 target-flexibility) (0 robustness) sat:SYN_00267 (0 target-flexibility) (0 robustness) sat:SYN_00272 (0 target-flexibility) (0 robustness) sat:SYN_00298 (0 target-flexibility) (0 robustness) sat:SYN_00302 (0 target-flexibility) (0 robustness) sat:SYN_00381 (700 target-flexibility) (89 robustness) sat:SYN_00412 (231 target-flexibility) (158 robustness) sat:SYN_00424 (854 target-flexibility) (204 robustness) sat:SYN_00442 (0 target-flexibility) (0 robustness) sat:SYN_00446 (528 target-flexibility) (157 robustness) sat:SYN_00583 (80 target-flexibility) (80 robustness) sat:SYN_00621 (279 target-flexibility) (126 robustness) sat:SYN_00729 (854 target-flexibility) (204 robustness) sat:SYN_00761 (0 target-flexibility) (0 robustness) sat:SYN_00891 (279 target-flexibility) (126 robustness) sat:SYN_00904 (700 target-flexibility) (80 robustness) sat:SYN_00907 (732 target-flexibility) (78 robustness) sat:SYN_00908 (1385 target-flexibility) (204 robustness) sat:SYN_01112 (0 target-flexibility) (0 robustness) sat:SYN_01125 (0 target-flexibility) (0 robustness) sat:SYN_01130 (0 target-flexibility) (0 robustness) sat:SYN_01149 (1108 target-flexibility) (319 robustness) sat:SYN_01150 (1108 target-flexibility) (319 robustness) sat:SYN_01164 (0 target-flexibility) (0 robustness) sat:SYN_01184 (146 target-flexibility) (70 robustness) sat:SYN_01209 (734 target-flexibility) (110 robustness) sat:SYN_01223 (790 target-flexibility) (134 robustness) sat:SYN_01226 (734 target-flexibility) (110 robustness) sat:SYN_01231 (512 target-flexibility) (74 robustness) sat:SYN_01251 (358 target-flexibility) (124 robustness) sat:SYN_01253 (528 target-flexibility) (157 robustness) sat:SYN_01258 (334 target-flexibility) (71 robustness) sat:SYN_01331 (0 target-flexibility) (0 robustness) sat:SYN_01365 (146 target-flexibility) (70 robustness) sat:SYN_01451 (0 target-flexibility) (0 robustness) sat:SYN_01454 (222 target-flexibility) (83 robustness) sat:SYN_01483 (231 target-flexibility) (158 robustness) sat:SYN_01517 (0 target-flexibility) (0 robustness) sat:SYN_01532 (897 target-flexibility) (71 robustness) sat:SYN_01577 (146 target-flexibility) (70 robustness) sat:SYN_01624 (732 target-flexibility) (78 robustness) sat:SYN_01625 (405 target-flexibility) (169 robustness) sat:SYN_01680 (659 target-flexibility) (240 robustness) sat:SYN_01684 (0 target-flexibility) (0 robustness) sat:SYN_01696 (659 target-flexibility) (240 robustness) sat:SYN_01710 (902 target-flexibility) (228 robustness) sat:SYN_01711 (902 target-flexibility) (228 robustness) sat:SYN_01712 (902 target-flexibility) (228 robustness) sat:SYN_01713 (902 target-flexibility) (228 robustness) sat:SYN_01740 (239 target-flexibility) (67 robustness) sat:SYN_01742 (67 target-flexibility) (67 robustness) sat:SYN_01747 (70 target-flexibility) (70 robustness) sat:SYN_01901 (700 target-flexibility) (80 robustness) sat:SYN_01942 (686 target-flexibility) (192 robustness) sat:SYN_01943 (226 target-flexibility) (85 robustness) sat:SYN_01944 (346 target-flexibility) (67 robustness) sat:SYN_01945 (634 target-flexibility) (72 robustness) sat:SYN_01960 (700 target-flexibility) (89 robustness) sat:SYN_01965 (902 target-flexibility) (228 robustness) sat:SYN_01988 (686 target-flexibility) (192 robustness) sat:SYN_02126 (358 target-flexibility) (124 robustness) sat:SYN_02127 (659 target-flexibility) (240 robustness) sat:SYN_02148 (0 target-flexibility) (0 robustness) sat:SYN_02156 (138 target-flexibility) (66 robustness) sat:SYN_02188 (607 target-flexibility) (75 robustness) sat:SYN_02194 (841 target-flexibility) (126 robustness) sat:SYN_02365 (703 target-flexibility) (319 robustness) sat:SYN_02374 (0 target-flexibility) (0 robustness) sat:SYN_02496 (512 target-flexibility) (74 robustness) sat:SYN_02501 (0 target-flexibility) (0 robustness) sat:SYN_02502 (0 target-flexibility) (0 robustness) sat:SYN_02535 (752 target-flexibility) (76 robustness) sat:SYN_02538 (607 target-flexibility) (75 robustness) sat:SYN_02563 (0 target-flexibility) (0 robustness) sat:SYN_02566 (703 target-flexibility) (319 robustness) sat:SYN_02578 (0 target-flexibility) (0 robustness) sat:SYN_02589 (405 target-flexibility) (169 robustness) sat:SYN_02590 (634 target-flexibility) (72 robustness) sat:SYN_02591 (346 target-flexibility) (67 robustness) sat:SYN_02592 (226 target-flexibility) (85 robustness) sat:SYN_02600 (0 target-flexibility) (0 robustness) sat:SYN_02602 (752 target-flexibility) (76 robustness) sat:SYN_02635 (790 target-flexibility) (134 robustness) sat:SYN_02640 (0 target-flexibility) (0 robustness) sat:SYN_02641 (279 target-flexibility) (126 robustness) sat:SYN_02643 (0 target-flexibility) (0 robustness) sat:SYN_02661 (0 target-flexibility) (0 robustness) sat:SYN_02666 (821 target-flexibility) (137 robustness) sat:SYN_02678 (821 target-flexibility) (137 robustness) sat:SYN_02758 (334 target-flexibility) (71 robustness) sat:SYN_02761 (0 target-flexibility) (0 robustness) sat:SYN_02778 (0 target-flexibility) (0 robustness) sat:SYN_02866 (0 target-flexibility) (0 robustness) sat:SYN_02880 (0 target-flexibility) (0 robustness) sat:SYN_02884 (0 target-flexibility) (0 robustness) sat:SYN_02886 (212 target-flexibility) (73 robustness) sat:SYN_02937 (1385 target-flexibility) (204 robustness) sat:SYN_02985 (691 target-flexibility) (528 robustness) sat:SYN_03026 (358 target-flexibility) (104 robustness) sat:SYN_03128 (0 target-flexibility) (0 robustness) sat:SYN_03227 (0 target-flexibility) (0 robustness) scl:sce0088 (423 target-flexibility) (81 robustness) scl:sce0127 (175 target-flexibility) (78 robustness) scl:sce0176 (855 target-flexibility) (138 robustness) scl:sce0253 (855 target-flexibility) (138 robustness) scl:sce0379 (734 target-flexibility) (110 robustness) scl:sce0564 (231 target-flexibility) (158 robustness) scl:sce0616 (358 target-flexibility) (104 robustness) scl:sce0693 (0 target-flexibility) (0 robustness) scl:sce0752 (0 target-flexibility) (0 robustness) scl:sce0903 (0 target-flexibility) (0 robustness) scl:sce1032 (423 target-flexibility) (81 robustness) scl:sce1044 (279 target-flexibility) (126 robustness) scl:sce1063 (0 target-flexibility) (0 robustness) scl:sce1175 (497 target-flexibility) (186 robustness) scl:sce1213 (1108 target-flexibility) (319 robustness) scl:sce1214 (902 target-flexibility) (228 robustness) scl:sce1639 (241 target-flexibility) (71 robustness) scl:sce1646 (659 target-flexibility) (240 robustness) scl:sce1736 (924 target-flexibility) (101 robustness) scl:sce1738 (924 target-flexibility) (101 robustness) scl:sce2226 (241 target-flexibility) (71 robustness) scl:sce2402 (0 target-flexibility) (0 robustness) scl:sce2526 (703 target-flexibility) (319 robustness) scl:sce2535 (752 target-flexibility) (105 robustness) scl:sce2553 (140 target-flexibility) (74 robustness) scl:sce2600 (1108 target-flexibility) (319 robustness) scl:sce2813 (0 target-flexibility) (0 robustness) scl:sce3018 (343 target-flexibility) (180 robustness) scl:sce3035 (248 target-flexibility) (73 robustness) scl:sce3161 (0 target-flexibility) (0 robustness) scl:sce3187 (821 target-flexibility) (137 robustness) scl:sce3273 (659 target-flexibility) (240 robustness) scl:sce3351 (703 target-flexibility) (319 robustness) scl:sce3354 (659 target-flexibility) (240 robustness) scl:sce3432 (343 target-flexibility) (180 robustness) scl:sce3447 (0 target-flexibility) (0 robustness) scl:sce3526 (701 target-flexibility) (106 robustness) scl:sce3703 (358 target-flexibility) (124 robustness) scl:sce3730 (902 target-flexibility) (228 robustness) scl:sce3733 (841 target-flexibility) (126 robustness) scl:sce3734 (841 target-flexibility) (126 robustness) scl:sce3735 (434 target-flexibility) (67 robustness) scl:sce3760 (0 target-flexibility) (0 robustness) scl:sce3813 (703 target-flexibility) (319 robustness) scl:sce3815 (659 target-flexibility) (240 robustness) scl:sce3817 (1108 target-flexibility) (319 robustness) scl:sce3826 (821 target-flexibility) (137 robustness) scl:sce3875 (734 target-flexibility) (110 robustness) scl:sce3953 (357 target-flexibility) (115 robustness) scl:sce3987 (1041 target-flexibility) (243 robustness) scl:sce4177 (706 target-flexibility) (173 robustness) scl:sce4215 (0 target-flexibility) (0 robustness) scl:sce4236 (222 target-flexibility) (83 robustness) scl:sce4259 (0 target-flexibility) (0 robustness) scl:sce4283 (0 target-flexibility) (0 robustness) scl:sce4320 (732 target-flexibility) (78 robustness) scl:sce4359 (343 target-flexibility) (180 robustness) scl:sce4502 (279 target-flexibility) (126 robustness) scl:sce4540 (1784 target-flexibility) (162 robustness) scl:sce4570 (706 target-flexibility) (173 robustness) scl:sce4640 (701 target-flexibility) (106 robustness) scl:sce4641 (528 target-flexibility) (157 robustness) scl:sce4786 (528 target-flexibility) (157 robustness) scl:sce4883 (841 target-flexibility) (126 robustness) scl:sce4939 (821 target-flexibility) (137 robustness) scl:sce5053 (1108 target-flexibility) (319 robustness) scl:sce5078 (0 target-flexibility) (0 robustness) scl:sce5134 (212 target-flexibility) (73 robustness) scl:sce5197 (1784 target-flexibility) (162 robustness) scl:sce5271 (0 target-flexibility) (0 robustness) scl:sce5302 (659 target-flexibility) (240 robustness) scl:sce5320 (358 target-flexibility) (104 robustness) scl:sce5556 (239 target-flexibility) (99 robustness) scl:sce5753 (528 target-flexibility) (157 robustness) scl:sce5757 (528 target-flexibility) (157 robustness) scl:sce5871 (350 target-flexibility) (84 robustness) scl:sce5886 (0 target-flexibility) (0 robustness) scl:sce5922 (703 target-flexibility) (319 robustness) scl:sce6193 (140 target-flexibility) (74 robustness) scl:sce6246 (752 target-flexibility) (105 robustness) scl:sce6540 (657 target-flexibility) (95 robustness) scl:sce6856 (231 target-flexibility) (158 robustness) scl:sce6876 (248 target-flexibility) (73 robustness) scl:sce6934 (657 target-flexibility) (95 robustness) scl:sce7038 (239 target-flexibility) (99 robustness) scl:sce7210 (357 target-flexibility) (115 robustness) scl:sce7329 (358 target-flexibility) (124 robustness) scl:sce7375 (528 target-flexibility) (157 robustness) scl:sce7407 (796 target-flexibility) (85 robustness) scl:sce7417 (0 target-flexibility) (0 robustness) scl:sce7733 (350 target-flexibility) (84 robustness) scl:sce7844 (0 target-flexibility) (0 robustness) scl:sce7847 (706 target-flexibility) (173 robustness) scl:sce7883 (175 target-flexibility) (78 robustness) scl:sce7927 (790 target-flexibility) (134 robustness) scl:sce8012 (0 target-flexibility) (0 robustness) scl:sce8081 (175 target-flexibility) (78 robustness) scl:sce8127 (902 target-flexibility) (228 robustness) scl:sce8151 (434 target-flexibility) (67 robustness) scl:sce8174 (841 target-flexibility) (126 robustness) scl:sce8230 (175 target-flexibility) (78 robustness) scl:sce8281 (924 target-flexibility) (101 robustness) scl:sce8467 (1041 target-flexibility) (243 robustness) scl:sce8601 (0 target-flexibility) (0 robustness) scl:sce8671 (691 target-flexibility) (528 robustness) scl:sce8676 (691 target-flexibility) (528 robustness) scl:sce8683 (497 target-flexibility) (186 robustness) scl:sce8696 (0 target-flexibility) (0 robustness) scl:sce8755 (902 target-flexibility) (228 robustness) scl:sce8804 (821 target-flexibility) (137 robustness) scl:sce8855 (0 target-flexibility) (0 robustness) scl:sce8915 (0 target-flexibility) (0 robustness) scl:sce8917 (0 target-flexibility) (0 robustness) scl:sce9115 (301 target-flexibility) (154 robustness) scl:sce9130 (301 target-flexibility) (154 robustness) scl:sce9167 (80 target-flexibility) (80 robustness) scl:sce9261 (752 target-flexibility) (105 robustness) scl:sce9309 (0 target-flexibility) (0 robustness) sfu:Sfum_0007 (732 target-flexibility) (78 robustness) sfu:Sfum_0008 (405 target-flexibility) (169 robustness) sfu:Sfum_0062 (138 target-flexibility) (66 robustness) sfu:Sfum_0108 (0 target-flexibility) (0 robustness) sfu:Sfum_0112 (659 target-flexibility) (240 robustness) sfu:Sfum_0113 (1108 target-flexibility) (319 robustness) sfu:Sfum_0122 (222 target-flexibility) (83 robustness) sfu:Sfum_0156 (691 target-flexibility) (528 robustness) sfu:Sfum_0179 (0 target-flexibility) (0 robustness) sfu:Sfum_0192 (212 target-flexibility) (73 robustness) sfu:Sfum_0296 (902 target-flexibility) (228 robustness) sfu:Sfum_0379 (0 target-flexibility) (0 robustness) sfu:Sfum_0382 (0 target-flexibility) (0 robustness) sfu:Sfum_0392 (0 target-flexibility) (0 robustness) sfu:Sfum_0478 (358 target-flexibility) (104 robustness) sfu:Sfum_0483 (0 target-flexibility) (0 robustness) sfu:Sfum_0605 (854 target-flexibility) (204 robustness) sfu:Sfum_0615 (0 target-flexibility) (0 robustness) sfu:Sfum_0630 (706 target-flexibility) (173 robustness) sfu:Sfum_0634 (706 target-flexibility) (173 robustness) sfu:Sfum_0649 (706 target-flexibility) (173 robustness) sfu:Sfum_0698 (138 target-flexibility) (138 robustness) sfu:Sfum_0745 (790 target-flexibility) (134 robustness) sfu:Sfum_0769 (634 target-flexibility) (72 robustness) sfu:Sfum_0841 (0 target-flexibility) (0 robustness) sfu:Sfum_0871 (343 target-flexibility) (180 robustness) sfu:Sfum_0934 (486 target-flexibility) (89 robustness) sfu:Sfum_0937 (343 target-flexibility) (180 robustness) sfu:Sfum_0983 (700 target-flexibility) (80 robustness) sfu:Sfum_1039 (0 target-flexibility) (0 robustness) sfu:Sfum_1171 (1385 target-flexibility) (204 robustness) sfu:Sfum_1208 (657 target-flexibility) (95 robustness) sfu:Sfum_1215 (0 target-flexibility) (0 robustness) sfu:Sfum_1302 (1041 target-flexibility) (243 robustness) sfu:Sfum_1375 (703 target-flexibility) (319 robustness) sfu:Sfum_1468 (600 target-flexibility) (126 robustness) sfu:Sfum_1470 (0 target-flexibility) (0 robustness) sfu:Sfum_1475 (1784 target-flexibility) (162 robustness) sfu:Sfum_1533 (924 target-flexibility) (101 robustness) sfu:Sfum_1538 (0 target-flexibility) (0 robustness) sfu:Sfum_1608 (80 target-flexibility) (80 robustness) sfu:Sfum_1676 (0 target-flexibility) (0 robustness) sfu:Sfum_1700 (0 target-flexibility) (0 robustness) sfu:Sfum_1771 (686 target-flexibility) (192 robustness) sfu:Sfum_1824 (0 target-flexibility) (0 robustness) sfu:Sfum_1913 (154 target-flexibility) (80 robustness) sfu:Sfum_2015 (0 target-flexibility) (0 robustness) sfu:Sfum_2061 (600 target-flexibility) (126 robustness) sfu:Sfum_2123 (377 target-flexibility) (117 robustness) sfu:Sfum_2263 (0 target-flexibility) (0 robustness) sfu:Sfum_2610 (0 target-flexibility) (0 robustness) sfu:Sfum_2645 (323 target-flexibility) (101 robustness) sfu:Sfum_2980 (902 target-flexibility) (228 robustness) sfu:Sfum_2981 (902 target-flexibility) (228 robustness) sfu:Sfum_2982 (902 target-flexibility) (228 robustness) sfu:Sfum_2983 (902 target-flexibility) (228 robustness) sfu:Sfum_2984 (359 target-flexibility) (65 robustness) sfu:Sfum_2985 (103 target-flexibility) (103 robustness) sfu:Sfum_2986 (638 target-flexibility) (94 robustness) sfu:Sfum_2989 (434 target-flexibility) (67 robustness) sfu:Sfum_2990 (166 target-flexibility) (99 robustness) sfu:Sfum_2992 (0 target-flexibility) (0 robustness) sfu:Sfum_3010 (558 target-flexibility) (68 robustness) sfu:Sfum_3022 (902 target-flexibility) (228 robustness) sfu:Sfum_3023 (902 target-flexibility) (228 robustness) sfu:Sfum_3031 (434 target-flexibility) (67 robustness) sfu:Sfum_3302 (752 target-flexibility) (76 robustness) sfu:Sfum_3365 (752 target-flexibility) (76 robustness) sur:STAUR_0056 (1041 target-flexibility) (243 robustness) sur:STAUR_0276 (659 target-flexibility) (240 robustness) sur:STAUR_0279 (1108 target-flexibility) (319 robustness) sur:STAUR_0299 (0 target-flexibility) (0 robustness) sur:STAUR_0404 (154 target-flexibility) (80 robustness) sur:STAUR_0531 (212 target-flexibility) (73 robustness) sur:STAUR_0636 (336 target-flexibility) (81 robustness) sur:STAUR_0672 (526 target-flexibility) (95 robustness) sur:STAUR_0782 (215 target-flexibility) (142 robustness) sur:STAUR_0784 (0 target-flexibility) (0 robustness) sur:STAUR_0785 (855 target-flexibility) (138 robustness) sur:STAUR_1091 (686 target-flexibility) (192 robustness) sur:STAUR_1573 (503 target-flexibility) (78 robustness) sur:STAUR_1653 (73 target-flexibility) (73 robustness) sur:STAUR_1671 (732 target-flexibility) (78 robustness) sur:STAUR_1904 (357 target-flexibility) (102 robustness) sur:STAUR_2087 (659 target-flexibility) (240 robustness) sur:STAUR_2116 (0 target-flexibility) (0 robustness) sur:STAUR_2146 (796 target-flexibility) (85 robustness) sur:STAUR_2240 (336 target-flexibility) (81 robustness) sur:STAUR_2244 (343 target-flexibility) (180 robustness) sur:STAUR_2302 (0 target-flexibility) (0 robustness) sur:STAUR_2346 (528 target-flexibility) (157 robustness) sur:STAUR_2543 (691 target-flexibility) (528 robustness) sur:STAUR_2647 (691 target-flexibility) (528 robustness) sur:STAUR_2699 (691 target-flexibility) (528 robustness) sur:STAUR_2714 (0 target-flexibility) (0 robustness) sur:STAUR_2729 (659 target-flexibility) (240 robustness) sur:STAUR_3111 (697 target-flexibility) (78 robustness) sur:STAUR_3279 (0 target-flexibility) (0 robustness) sur:STAUR_3296 (790 target-flexibility) (134 robustness) sur:STAUR_3316 (526 target-flexibility) (95 robustness) sur:STAUR_3348 (1022 target-flexibility) (80 robustness) sur:STAUR_3412 (357 target-flexibility) (102 robustness) sur:STAUR_3549 (0 target-flexibility) (0 robustness) sur:STAUR_3605 (434 target-flexibility) (67 robustness) sur:STAUR_3608 (841 target-flexibility) (126 robustness) sur:STAUR_3769 (343 target-flexibility) (180 robustness) sur:STAUR_3779 (231 target-flexibility) (158 robustness) sur:STAUR_3846 (357 target-flexibility) (115 robustness) sur:STAUR_3888 (228 target-flexibility) (83 robustness) sur:STAUR_3898 (821 target-flexibility) (137 robustness) sur:STAUR_3946 (0 target-flexibility) (0 robustness) sur:STAUR_3991 (752 target-flexibility) (105 robustness) sur:STAUR_4027 (0 target-flexibility) (0 robustness) sur:STAUR_4028 (0 target-flexibility) (0 robustness) sur:STAUR_4035 (1784 target-flexibility) (162 robustness) sur:STAUR_4038 (0 target-flexibility) (0 robustness) sur:STAUR_4039 (924 target-flexibility) (101 robustness) sur:STAUR_4050 (289 target-flexibility) (73 robustness) sur:STAUR_4128 (0 target-flexibility) (0 robustness) sur:STAUR_4273 (821 target-flexibility) (137 robustness) sur:STAUR_4439 (343 target-flexibility) (180 robustness) sur:STAUR_4493 (0 target-flexibility) (0 robustness) sur:STAUR_4567 (231 target-flexibility) (158 robustness) sur:STAUR_4663 (0 target-flexibility) (0 robustness) sur:STAUR_4684 (0 target-flexibility) (0 robustness) sur:STAUR_4743 (659 target-flexibility) (240 robustness) sur:STAUR_4815 (212 target-flexibility) (73 robustness) sur:STAUR_4852 (528 target-flexibility) (157 robustness) sur:STAUR_4853 (301 target-flexibility) (74 robustness) sur:STAUR_4869 (0 target-flexibility) (0 robustness) sur:STAUR_4873 (841 target-flexibility) (126 robustness) sur:STAUR_4874 (434 target-flexibility) (67 robustness) sur:STAUR_5122 (855 target-flexibility) (138 robustness) sur:STAUR_5127 (358 target-flexibility) (124 robustness) sur:STAUR_5152 (0 target-flexibility) (0 robustness) sur:STAUR_5155 (0 target-flexibility) (0 robustness) sur:STAUR_5175 (734 target-flexibility) (110 robustness) sur:STAUR_5197 (657 target-flexibility) (95 robustness) sur:STAUR_5252 (691 target-flexibility) (528 robustness) sur:STAUR_5285 (528 target-flexibility) (157 robustness) sur:STAUR_5309 (796 target-flexibility) (85 robustness) sur:STAUR_5339 (703 target-flexibility) (319 robustness) sur:STAUR_5347 (902 target-flexibility) (228 robustness) sur:STAUR_5425 (1169 target-flexibility) (76 robustness) sur:STAUR_5482 (821 target-flexibility) (137 robustness) sur:STAUR_5486 (752 target-flexibility) (76 robustness) sur:STAUR_5581 (71 target-flexibility) (71 robustness) sur:STAUR_5595 (0 target-flexibility) (0 robustness) sur:STAUR_5618 (703 target-flexibility) (319 robustness) sur:STAUR_5620 (659 target-flexibility) (240 robustness) sur:STAUR_5621 (503 target-flexibility) (78 robustness) sur:STAUR_5622 (1108 target-flexibility) (319 robustness) sur:STAUR_5666 (752 target-flexibility) (105 robustness) sur:STAUR_5774 (222 target-flexibility) (83 robustness) sur:STAUR_5813 (358 target-flexibility) (124 robustness) sur:STAUR_5839 (734 target-flexibility) (110 robustness) sur:STAUR_5845 (657 target-flexibility) (95 robustness) sur:STAUR_5870 (0 target-flexibility) (0 robustness) sur:STAUR_5872 (301 target-flexibility) (74 robustness) sur:STAUR_5875 (0 target-flexibility) (0 robustness) sur:STAUR_6060 (0 target-flexibility) (0 robustness) sur:STAUR_6096 (0 target-flexibility) (0 robustness) sur:STAUR_6098 (0 target-flexibility) (0 robustness) sur:STAUR_6259 (231 target-flexibility) (158 robustness) sur:STAUR_6266 (67 target-flexibility) (67 robustness) sur:STAUR_6267 (239 target-flexibility) (67 robustness) sur:STAUR_6310 (357 target-flexibility) (115 robustness) sur:STAUR_6406 (231 target-flexibility) (158 robustness) sur:STAUR_6468 (228 target-flexibility) (83 robustness) sur:STAUR_6597 (697 target-flexibility) (78 robustness) sur:STAUR_6616 (231 target-flexibility) (158 robustness) sur:STAUR_6684 (0 target-flexibility) (0 robustness) sur:STAUR_6701 (924 target-flexibility) (101 robustness) sur:STAUR_6761 (686 target-flexibility) (192 robustness) sur:STAUR_6764 (215 target-flexibility) (142 robustness) sur:STAUR_6803 (902 target-flexibility) (228 robustness) sur:STAUR_6805 (855 target-flexibility) (138 robustness) sur:STAUR_6830 (357 target-flexibility) (115 robustness) sur:STAUR_6858 (1784 target-flexibility) (162 robustness) sur:STAUR_6979 (343 target-flexibility) (180 robustness) sur:STAUR_7012 (528 target-flexibility) (157 robustness) sur:STAUR_7055 (790 target-flexibility) (134 robustness) sur:STAUR_7164 (0 target-flexibility) (0 robustness) sur:STAUR_7165 (0 target-flexibility) (0 robustness) sur:STAUR_7168 (0 target-flexibility) (0 robustness) sur:STAUR_7259 (154 target-flexibility) (80 robustness) sur:STAUR_7849 (659 target-flexibility) (240 robustness) sur:STAUR_7912 (0 target-flexibility) (0 robustness) sur:STAUR_7939 (1022 target-flexibility) (80 robustness) sur:STAUR_8101 (80 target-flexibility) (80 robustness) sur:STAUR_8110 (73 target-flexibility) (73 robustness) sur:STAUR_8129 (222 target-flexibility) (83 robustness) sur:STAUR_8226 (0 target-flexibility) (0 robustness) vin:AKJ08_0033 (140 target-flexibility) (140 robustness) vin:AKJ08_0035 (140 target-flexibility) (140 robustness) vin:AKJ08_0051 (732 target-flexibility) (78 robustness) vin:AKJ08_0067 (0 target-flexibility) (0 robustness) vin:AKJ08_0163 (138 target-flexibility) (66 robustness) vin:AKJ08_0182 (343 target-flexibility) (180 robustness) vin:AKJ08_0229 (821 target-flexibility) (137 robustness) vin:AKJ08_0242 (821 target-flexibility) (137 robustness) vin:AKJ08_0304 (0 target-flexibility) (0 robustness) vin:AKJ08_0448 (262 target-flexibility) (86 robustness) vin:AKJ08_0452 (262 target-flexibility) (86 robustness) vin:AKJ08_0498 (530 target-flexibility) (162 robustness) vin:AKJ08_0507 (231 target-flexibility) (158 robustness) vin:AKJ08_0517 (262 target-flexibility) (86 robustness) vin:AKJ08_0647 (323 target-flexibility) (101 robustness) vin:AKJ08_0731 (1041 target-flexibility) (243 robustness) vin:AKJ08_0779 (0 target-flexibility) (0 robustness) vin:AKJ08_0879 (405 target-flexibility) (169 robustness) vin:AKJ08_0977 (0 target-flexibility) (0 robustness) vin:AKJ08_1030 (358 target-flexibility) (124 robustness) vin:AKJ08_1046 (796 target-flexibility) (85 robustness) vin:AKJ08_1190 (222 target-flexibility) (83 robustness) vin:AKJ08_1262 (1169 target-flexibility) (76 robustness) vin:AKJ08_1405 (289 target-flexibility) (73 robustness) vin:AKJ08_1409 (405 target-flexibility) (169 robustness) vin:AKJ08_1410 (149 target-flexibility) (77 robustness) vin:AKJ08_1411 (897 target-flexibility) (71 robustness) vin:AKJ08_1417 (0 target-flexibility) (0 robustness) vin:AKJ08_1488 (231 target-flexibility) (158 robustness) vin:AKJ08_1509 (357 target-flexibility) (102 robustness) vin:AKJ08_1631 (659 target-flexibility) (240 robustness) vin:AKJ08_1633 (530 target-flexibility) (162 robustness) vin:AKJ08_1829 (262 target-flexibility) (86 robustness) vin:AKJ08_1847 (405 target-flexibility) (169 robustness) vin:AKJ08_1848 (405 target-flexibility) (169 robustness) vin:AKJ08_1882 (434 target-flexibility) (67 robustness) vin:AKJ08_1884 (262 target-flexibility) (86 robustness) vin:AKJ08_1908 (0 target-flexibility) (0 robustness) vin:AKJ08_2065 (212 target-flexibility) (73 robustness) vin:AKJ08_2124 (323 target-flexibility) (101 robustness) vin:AKJ08_2231 (343 target-flexibility) (180 robustness) vin:AKJ08_2247 (231 target-flexibility) (158 robustness) vin:AKJ08_2249 (70 target-flexibility) (70 robustness) vin:AKJ08_2252 (140 target-flexibility) (71 robustness) vin:AKJ08_2254 (67 target-flexibility) (67 robustness) vin:AKJ08_2255 (239 target-flexibility) (67 robustness) vin:AKJ08_2274 (357 target-flexibility) (115 robustness) vin:AKJ08_2290 (358 target-flexibility) (124 robustness) vin:AKJ08_2325 (0 target-flexibility) (0 robustness) vin:AKJ08_2336 (659 target-flexibility) (240 robustness) vin:AKJ08_2528 (796 target-flexibility) (85 robustness) vin:AKJ08_2585 (659 target-flexibility) (240 robustness) vin:AKJ08_2627 (0 target-flexibility) (0 robustness) vin:AKJ08_2747 (74 target-flexibility) (74 robustness) vin:AKJ08_2748 (175 target-flexibility) (96 robustness) vin:AKJ08_2749 (175 target-flexibility) (96 robustness) vin:AKJ08_2890 (74 target-flexibility) (74 robustness) vin:AKJ08_3025 (175 target-flexibility) (96 robustness) vin:AKJ08_3161 (357 target-flexibility) (102 robustness) vin:AKJ08_3214 (222 target-flexibility) (83 robustness) vin:AKJ08_3459 (357 target-flexibility) (115 robustness) vin:AKJ08_3614 (0 target-flexibility) (0 robustness) vin:AKJ08_3662 (149 target-flexibility) (77 robustness)

Target-flexibility contribution: 96.20466159790601% Robustness contribution: 86.81914495824505%

Conclusion

27% of all enzymes are gene-duplicated, which seems like a sane value.

A bit more surprisingly, there are only 5868 gene-duplicated enzymes for a total of 5561 pairs of homologous enzymes, while it could have been double the number of pairs, i.e. 11122. But this would mean that each pair of enzymes contains unique enzymes. Obivously, however, there are many enzymes which occur in more than one pair. This means the enzymes actually form groups of homologous enzymes.

On the other hand, around 90% of all redundant enzymes have a gene-duplicated enzyme on one of their redundant paths. This seems like a lot, but such a high value is actually to be expected. This is because, assuming the probability of hitting a gene-duplicated enzyme were to be equally distributed (which it is not, due to the scale-free architecture of the network), the probability of hitting at least one gene-duplicated enzyme on a redundant path of length 1 is 27%. However, the probability of hitting at least one gene-duplicated enzyme on a redundant path of length 2 is already 54%. Additionally, one node often has more than one alternative paths to another node. Also, one enzyme can have multiple edges, futher increasing the odds of hitting at least one gene-duplicated enzyme on any of its alternative paths. Finally, in this case, we use an enzyme graph derived from enzymes which have EC numbers which occur in the core metabolism of the organism group. Because of this, there almost certainly have to be multiple enzymes connecting each pair of nodes, because otherwise, they would not have been part of the enzymes involved in the core metabolism.

This does not answer the question whether an enzyme would not be robust/flexible if the gene-duplicated enzymes did not exist!

Due to the definition of flexibility and robustness, flexibility must always be higher than robustness, which it is here. Also, due to the definition of target-flexibility, it must always be even higher than flexibility. Still, target-flexibility is close to 100%, which is probably due to the above mentioned likelihood of one enzyme (edge key), having multiple edges, having multiple alternative paths, of which only one must contain a gene-duplicated enzyme.

FEV_KEGG.Experiments.46.getCladeA()[source]
FEV_KEGG.Experiments.47 module
Question

Which neofunctionalised enzymes exist in Deltaproteobacteria? Does their existence increase redundancy? If yes, how much?

Method
  • get Deltaproteobacteria
  • get neofunctionalised enzymes
  • calculate redundancy
  • REPEAT for each neofunctionalised enzyme
  • print number of enzymes the neofunctionalised enzyme provides redundancy for (robustness and flexibility)
Result
::

core metabolism majority: 80%

Deltaproteobacteria:

core metabolism enzymes: 21519

neofunctionalised enzymes: 1400 ( 7%) ade:Adeh_0012 (222 target-flexibility) (83 robustness) ade:Adeh_0069 (0 target-flexibility) (0 robustness) ade:Adeh_0221 (0 target-flexibility) (0 robustness) ade:Adeh_1078 (71 target-flexibility) (71 robustness) ade:Adeh_1165 (0 target-flexibility) (0 robustness) ade:Adeh_1618 (897 target-flexibility) (71 robustness) ade:Adeh_1954 (0 target-flexibility) (0 robustness) ade:Adeh_1955 (0 target-flexibility) (0 robustness) ade:Adeh_2390 (212 target-flexibility) (73 robustness) ade:Adeh_2533 (752 target-flexibility) (76 robustness) ade:Adeh_2619 (790 target-flexibility) (134 robustness) ade:Adeh_2691 (138 target-flexibility) (66 robustness) ade:Adeh_2727 (0 target-flexibility) (0 robustness) ade:Adeh_2728 (206 target-flexibility) (68 robustness) ade:Adeh_3766 (239 target-flexibility) (67 robustness) ade:Adeh_3767 (67 target-flexibility) (67 robustness) ade:Adeh_3769 (140 target-flexibility) (71 robustness) ade:Adeh_3772 (70 target-flexibility) (70 robustness) ade:Adeh_3959 (796 target-flexibility) (85 robustness) ade:Adeh_4206 (732 target-flexibility) (78 robustness) ade:Adeh_4288 (0 target-flexibility) (0 robustness) ade:Adeh_4344 (80 target-flexibility) (80 robustness) afw:Anae109_0013 (222 target-flexibility) (83 robustness) afw:Anae109_0070 (0 target-flexibility) (0 robustness) afw:Anae109_0462 (796 target-flexibility) (85 robustness) afw:Anae109_1117 (71 target-flexibility) (71 robustness) afw:Anae109_1136 (1169 target-flexibility) (76 robustness) afw:Anae109_1212 (0 target-flexibility) (0 robustness) afw:Anae109_1329 (752 target-flexibility) (76 robustness) afw:Anae109_1477 (212 target-flexibility) (73 robustness) afw:Anae109_1900 (0 target-flexibility) (0 robustness) afw:Anae109_1901 (0 target-flexibility) (0 robustness) afw:Anae109_2193 (897 target-flexibility) (71 robustness) afw:Anae109_2586 (790 target-flexibility) (134 robustness) afw:Anae109_2685 (138 target-flexibility) (66 robustness) afw:Anae109_2719 (0 target-flexibility) (0 robustness) afw:Anae109_3170 (790 target-flexibility) (134 robustness) afw:Anae109_3317 (1041 target-flexibility) (243 robustness) afw:Anae109_3879 (239 target-flexibility) (67 robustness) afw:Anae109_3880 (67 target-flexibility) (67 robustness) afw:Anae109_3882 (140 target-flexibility) (71 robustness) afw:Anae109_3885 (70 target-flexibility) (70 robustness) afw:Anae109_4196 (0 target-flexibility) (0 robustness) afw:Anae109_4354 (732 target-flexibility) (78 robustness) afw:Anae109_4443 (0 target-flexibility) (0 robustness) afw:Anae109_4491 (80 target-flexibility) (80 robustness) age:AA314_01105 (0 target-flexibility) (0 robustness) age:AA314_01165 (222 target-flexibility) (83 robustness) age:AA314_01193 (80 target-flexibility) (80 robustness) age:AA314_01912 (790 target-flexibility) (134 robustness) age:AA314_02310 (732 target-flexibility) (78 robustness) age:AA314_02714 (796 target-flexibility) (85 robustness) age:AA314_02872 (0 target-flexibility) (0 robustness) age:AA314_03054 (0 target-flexibility) (0 robustness) age:AA314_04189 (0 target-flexibility) (0 robustness) age:AA314_04205 (71 target-flexibility) (71 robustness) age:AA314_04258 (752 target-flexibility) (76 robustness) age:AA314_04350 (0 target-flexibility) (0 robustness) age:AA314_04447 (212 target-flexibility) (73 robustness) age:AA314_04970 (0 target-flexibility) (0 robustness) age:AA314_05002 (0 target-flexibility) (0 robustness) age:AA314_05003 (0 target-flexibility) (0 robustness) age:AA314_05007 (897 target-flexibility) (71 robustness) age:AA314_05182 (212 target-flexibility) (73 robustness) age:AA314_05840 (0 target-flexibility) (0 robustness) age:AA314_05880 (138 target-flexibility) (66 robustness) age:AA314_08007 (70 target-flexibility) (70 robustness) age:AA314_08012 (67 target-flexibility) (67 robustness) ank:AnaeK_0012 (222 target-flexibility) (83 robustness) ank:AnaeK_0075 (0 target-flexibility) (0 robustness) ank:AnaeK_0232 (0 target-flexibility) (0 robustness) ank:AnaeK_1137 (71 target-flexibility) (71 robustness) ank:AnaeK_1224 (0 target-flexibility) (0 robustness) ank:AnaeK_1316 (752 target-flexibility) (76 robustness) ank:AnaeK_1474 (212 target-flexibility) (73 robustness) ank:AnaeK_1924 (0 target-flexibility) (0 robustness) ank:AnaeK_1925 (0 target-flexibility) (0 robustness) ank:AnaeK_2242 (897 target-flexibility) (71 robustness) ank:AnaeK_2705 (790 target-flexibility) (134 robustness) ank:AnaeK_2784 (138 target-flexibility) (66 robustness) ank:AnaeK_2819 (0 target-flexibility) (0 robustness) ank:AnaeK_3822 (239 target-flexibility) (67 robustness) ank:AnaeK_3823 (67 target-flexibility) (67 robustness) ank:AnaeK_3825 (140 target-flexibility) (71 robustness) ank:AnaeK_3828 (70 target-flexibility) (70 robustness) ank:AnaeK_4069 (796 target-flexibility) (85 robustness) ank:AnaeK_4338 (732 target-flexibility) (78 robustness) ank:AnaeK_4425 (0 target-flexibility) (0 robustness) ank:AnaeK_4480 (80 target-flexibility) (80 robustness) ccro:CMC5_000130 (212 target-flexibility) (73 robustness) ccro:CMC5_011930 (80 target-flexibility) (80 robustness) ccro:CMC5_012020 (0 target-flexibility) (0 robustness) ccro:CMC5_012520 (0 target-flexibility) (0 robustness) ccro:CMC5_019230 (0 target-flexibility) (0 robustness) ccro:CMC5_044530 (222 target-flexibility) (83 robustness) ccro:CMC5_049960 (0 target-flexibility) (0 robustness) ccro:CMC5_065360 (70 target-flexibility) (70 robustness) ccro:CMC5_065390 (140 target-flexibility) (71 robustness) ccro:CMC5_084110 (0 target-flexibility) (0 robustness) ccx:COCOR_00905 (790 target-flexibility) (134 robustness) ccx:COCOR_01049 (732 target-flexibility) (78 robustness) ccx:COCOR_01272 (796 target-flexibility) (85 robustness) ccx:COCOR_01538 (0 target-flexibility) (0 robustness) ccx:COCOR_02172 (0 target-flexibility) (0 robustness) ccx:COCOR_02650 (0 target-flexibility) (0 robustness) ccx:COCOR_02664 (71 target-flexibility) (71 robustness) ccx:COCOR_02713 (752 target-flexibility) (76 robustness) ccx:COCOR_03319 (212 target-flexibility) (73 robustness) ccx:COCOR_03939 (0 target-flexibility) (0 robustness) ccx:COCOR_04535 (0 target-flexibility) (0 robustness) ccx:COCOR_04536 (0 target-flexibility) (0 robustness) ccx:COCOR_04815 (0 target-flexibility) (0 robustness) ccx:COCOR_04847 (1169 target-flexibility) (76 robustness) ccx:COCOR_05520 (790 target-flexibility) (134 robustness) ccx:COCOR_06667 (222 target-flexibility) (83 robustness) ccx:COCOR_06741 (1041 target-flexibility) (243 robustness) ccx:COCOR_07636 (222 target-flexibility) (83 robustness) cfus:CYFUS_000638 (222 target-flexibility) (83 robustness) cfus:CYFUS_001210 (790 target-flexibility) (134 robustness) cfus:CYFUS_001311 (0 target-flexibility) (0 robustness) cfus:CYFUS_001459 (732 target-flexibility) (78 robustness) cfus:CYFUS_002029 (796 target-flexibility) (85 robustness) cfus:CYFUS_002221 (0 target-flexibility) (0 robustness) cfus:CYFUS_002381 (0 target-flexibility) (0 robustness) cfus:CYFUS_002855 (790 target-flexibility) (134 robustness) cfus:CYFUS_003276 (222 target-flexibility) (83 robustness) cfus:CYFUS_003510 (0 target-flexibility) (0 robustness) cfus:CYFUS_003523 (71 target-flexibility) (71 robustness) cfus:CYFUS_004387 (212 target-flexibility) (73 robustness) cfus:CYFUS_004499 (0 target-flexibility) (0 robustness) cfus:CYFUS_004500 (0 target-flexibility) (0 robustness) cfus:CYFUS_004504 (897 target-flexibility) (71 robustness) cfus:CYFUS_004967 (0 target-flexibility) (0 robustness) cfus:CYFUS_005495 (0 target-flexibility) (0 robustness) cfus:CYFUS_005533 (138 target-flexibility) (66 robustness) cfus:CYFUS_006014 (0 target-flexibility) (0 robustness) cfus:CYFUS_006116 (752 target-flexibility) (76 robustness) cfus:CYFUS_007834 (67 target-flexibility) (67 robustness) cfus:CYFUS_007835 (239 target-flexibility) (67 robustness) cfus:CYFUS_007908 (0 target-flexibility) (0 robustness) daf:Desaf_0090 (1041 target-flexibility) (243 robustness) daf:Desaf_0111 (732 target-flexibility) (78 robustness) daf:Desaf_0304 (1041 target-flexibility) (243 robustness) daf:Desaf_0322 (790 target-flexibility) (134 robustness) daf:Desaf_0930 (0 target-flexibility) (0 robustness) daf:Desaf_1013 (0 target-flexibility) (0 robustness) daf:Desaf_1251 (790 target-flexibility) (134 robustness) daf:Desaf_1274 (528 target-flexibility) (157 robustness) daf:Desaf_1333 (0 target-flexibility) (0 robustness) daf:Desaf_1391 (790 target-flexibility) (134 robustness) daf:Desaf_1457 (212 target-flexibility) (73 robustness) daf:Desaf_1564 (796 target-flexibility) (85 robustness) daf:Desaf_1776 (80 target-flexibility) (80 robustness) daf:Desaf_2132 (0 target-flexibility) (0 robustness) daf:Desaf_2261 (358 target-flexibility) (104 robustness) daf:Desaf_2305 (0 target-flexibility) (0 robustness) daf:Desaf_2339 (0 target-flexibility) (0 robustness) daf:Desaf_2415 (0 target-flexibility) (0 robustness) daf:Desaf_2509 (289 target-flexibility) (73 robustness) daf:Desaf_2909 (0 target-flexibility) (0 robustness) daf:Desaf_2926 (222 target-flexibility) (83 robustness) daf:Desaf_2970 (1169 target-flexibility) (76 robustness) daf:Desaf_3260 (434 target-flexibility) (67 robustness) dak:DaAHT2_0472 (0 target-flexibility) (0 robustness) dak:DaAHT2_1051 (212 target-flexibility) (73 robustness) dak:DaAHT2_1178 (222 target-flexibility) (83 robustness) dak:DaAHT2_1480 (70 target-flexibility) (70 robustness) dak:DaAHT2_1482 (140 target-flexibility) (71 robustness) dak:DaAHT2_1636 (732 target-flexibility) (78 robustness) dak:DaAHT2_1791 (0 target-flexibility) (0 robustness) dak:DaAHT2_1792 (0 target-flexibility) (0 robustness) dak:DaAHT2_1794 (0 target-flexibility) (0 robustness) dak:DaAHT2_1831 (0 target-flexibility) (0 robustness) dak:DaAHT2_2211 (138 target-flexibility) (66 robustness) dak:DaAHT2_2315 (897 target-flexibility) (71 robustness) dak:DaAHT2_2371 (796 target-flexibility) (85 robustness) dak:DaAHT2_2537 (80 target-flexibility) (80 robustness) dak:DaAHT2_2561 (0 target-flexibility) (0 robustness) dal:Dalk_0475 (0 target-flexibility) (0 robustness) dal:Dalk_0497 (212 target-flexibility) (73 robustness) dal:Dalk_0836 (1169 target-flexibility) (76 robustness) dal:Dalk_0853 (0 target-flexibility) (0 robustness) dal:Dalk_0935 (0 target-flexibility) (0 robustness) dal:Dalk_1064 (1041 target-flexibility) (243 robustness) dal:Dalk_1193 (0 target-flexibility) (0 robustness) dal:Dalk_1240 (434 target-flexibility) (67 robustness) dal:Dalk_1587 (0 target-flexibility) (0 robustness) dal:Dalk_1693 (0 target-flexibility) (0 robustness) dal:Dalk_1699 (0 target-flexibility) (0 robustness) dal:Dalk_1770 (222 target-flexibility) (83 robustness) dal:Dalk_1784 (71 target-flexibility) (71 robustness) dal:Dalk_1934 (289 target-flexibility) (73 robustness) dal:Dalk_2329 (790 target-flexibility) (134 robustness) dal:Dalk_2651 (528 target-flexibility) (157 robustness) dal:Dalk_2756 (752 target-flexibility) (76 robustness) dal:Dalk_3130 (70 target-flexibility) (70 robustness) dal:Dalk_3133 (140 target-flexibility) (71 robustness) dal:Dalk_3135 (67 target-flexibility) (67 robustness) dal:Dalk_3136 (239 target-flexibility) (67 robustness) dal:Dalk_3333 (0 target-flexibility) (0 robustness) dal:Dalk_3370 (1385 target-flexibility) (204 robustness) dal:Dalk_3820 (358 target-flexibility) (104 robustness) dal:Dalk_4104 (0 target-flexibility) (0 robustness) dal:Dalk_4640 (0 target-flexibility) (0 robustness) dao:Desac_0009 (897 target-flexibility) (71 robustness) dao:Desac_0239 (0 target-flexibility) (0 robustness) dao:Desac_0519 (732 target-flexibility) (78 robustness) dao:Desac_0596 (70 target-flexibility) (70 robustness) dao:Desac_0599 (140 target-flexibility) (71 robustness) dao:Desac_0601 (67 target-flexibility) (67 robustness) dao:Desac_0602 (239 target-flexibility) (67 robustness) dao:Desac_0972 (206 target-flexibility) (68 robustness) dao:Desac_1300 (289 target-flexibility) (73 robustness) dao:Desac_1415 (212 target-flexibility) (73 robustness) dao:Desac_1501 (0 target-flexibility) (0 robustness) dao:Desac_1741 (0 target-flexibility) (0 robustness) dao:Desac_2262 (0 target-flexibility) (0 robustness) dao:Desac_2462 (796 target-flexibility) (85 robustness) dao:Desac_2478 (138 target-flexibility) (66 robustness) dao:Desac_2517 (0 target-flexibility) (0 robustness) dao:Desac_2541 (0 target-flexibility) (0 robustness) dao:Desac_2544 (0 target-flexibility) (0 robustness) dao:Desac_2593 (80 target-flexibility) (80 robustness) dao:Desac_2722 (71 target-flexibility) (71 robustness) dao:Desac_2908 (222 target-flexibility) (83 robustness) dao:Desac_2922 (434 target-flexibility) (67 robustness) das:Daes_0077 (1041 target-flexibility) (243 robustness) das:Daes_0202 (790 target-flexibility) (134 robustness) das:Daes_0235 (752 target-flexibility) (76 robustness) das:Daes_0542 (790 target-flexibility) (134 robustness) das:Daes_0665 (790 target-flexibility) (134 robustness) das:Daes_0687 (1385 target-flexibility) (204 robustness) das:Daes_0744 (212 target-flexibility) (73 robustness) das:Daes_0753 (80 target-flexibility) (80 robustness) das:Daes_0911 (1169 target-flexibility) (76 robustness) das:Daes_0961 (0 target-flexibility) (0 robustness) das:Daes_1318 (0 target-flexibility) (0 robustness) das:Daes_1396 (71 target-flexibility) (71 robustness) das:Daes_1706 (528 target-flexibility) (157 robustness) das:Daes_1709 (222 target-flexibility) (83 robustness) das:Daes_1850 (206 target-flexibility) (68 robustness) das:Daes_1909 (434 target-flexibility) (67 robustness) das:Daes_1972 (1041 target-flexibility) (243 robustness) das:Daes_2350 (358 target-flexibility) (104 robustness) das:Daes_2678 (289 target-flexibility) (73 robustness) das:Daes_2821 (0 target-flexibility) (0 robustness) das:Daes_2857 (0 target-flexibility) (0 robustness) das:Daes_2972 (0 target-flexibility) (0 robustness) das:Daes_3345 (0 target-flexibility) (0 robustness) dat:HRM2_04430 (434 target-flexibility) (67 robustness) dat:HRM2_06910 (528 target-flexibility) (157 robustness) dat:HRM2_08850 (790 target-flexibility) (134 robustness) dat:HRM2_11950 (790 target-flexibility) (134 robustness) dat:HRM2_12660 (239 target-flexibility) (67 robustness) dat:HRM2_12670 (67 target-flexibility) (67 robustness) dat:HRM2_13680 (0 target-flexibility) (0 robustness) dat:HRM2_20130 (358 target-flexibility) (104 robustness) dat:HRM2_20900 (212 target-flexibility) (73 robustness) dat:HRM2_23040 (0 target-flexibility) (0 robustness) dat:HRM2_24890 (222 target-flexibility) (83 robustness) dat:HRM2_26740 (358 target-flexibility) (104 robustness) dat:HRM2_27190 (0 target-flexibility) (0 robustness) dat:HRM2_27560 (138 target-flexibility) (66 robustness) dat:HRM2_27780 (897 target-flexibility) (71 robustness) dat:HRM2_28720 (790 target-flexibility) (134 robustness) dat:HRM2_29750 (0 target-flexibility) (0 robustness) dat:HRM2_41030 (289 target-flexibility) (73 robustness) dat:HRM2_47210 (790 target-flexibility) (134 robustness) dat:HRM2_47820 (0 target-flexibility) (0 robustness) dat:HRM2_47830 (0 target-flexibility) (0 robustness) dav:DESACE_00060 (1041 target-flexibility) (243 robustness) dav:DESACE_01185 (212 target-flexibility) (73 robustness) dav:DESACE_02320 (222 target-flexibility) (83 robustness) dav:DESACE_03005 (67 target-flexibility) (67 robustness) dav:DESACE_03010 (239 target-flexibility) (67 robustness) dav:DESACE_03180 (1169 target-flexibility) (76 robustness) dav:DESACE_03245 (70 target-flexibility) (70 robustness) dav:DESACE_03540 (0 target-flexibility) (0 robustness) dav:DESACE_05935 (80 target-flexibility) (80 robustness) dav:DESACE_08825 (0 target-flexibility) (0 robustness) dba:Dbac_0057 (0 target-flexibility) (0 robustness) dba:Dbac_0109 (790 target-flexibility) (134 robustness) dba:Dbac_0488 (222 target-flexibility) (83 robustness) dba:Dbac_1036 (358 target-flexibility) (104 robustness) dba:Dbac_1478 (790 target-flexibility) (134 robustness) dba:Dbac_1611 (0 target-flexibility) (0 robustness) dba:Dbac_1638 (528 target-flexibility) (157 robustness) dba:Dbac_1740 (434 target-flexibility) (67 robustness) dba:Dbac_1985 (289 target-flexibility) (73 robustness) dba:Dbac_2450 (212 target-flexibility) (73 robustness) dba:Dbac_2718 (0 target-flexibility) (0 robustness) dba:Dbac_2833 (796 target-flexibility) (85 robustness) dba:Dbac_2884 (0 target-flexibility) (0 robustness) dba:Dbac_3003 (80 target-flexibility) (80 robustness) dba:Dbac_3039 (0 target-flexibility) (0 robustness) dba:Dbac_3166 (790 target-flexibility) (134 robustness) dba:Dbac_3212 (732 target-flexibility) (78 robustness) dbr:Deba_0146 (0 target-flexibility) (0 robustness) dbr:Deba_0292 (796 target-flexibility) (85 robustness) dbr:Deba_0342 (434 target-flexibility) (67 robustness) dbr:Deba_0413 (222 target-flexibility) (83 robustness) dbr:Deba_0419 (0 target-flexibility) (0 robustness) dbr:Deba_0577 (80 target-flexibility) (80 robustness) dbr:Deba_0581 (0 target-flexibility) (0 robustness) dbr:Deba_0585 (790 target-flexibility) (134 robustness) dbr:Deba_0606 (0 target-flexibility) (0 robustness) dbr:Deba_0994 (0 target-flexibility) (0 robustness) dbr:Deba_1178 (528 target-flexibility) (157 robustness) dbr:Deba_1275 (289 target-flexibility) (73 robustness) dbr:Deba_1412 (0 target-flexibility) (0 robustness) dbr:Deba_1780 (0 target-flexibility) (0 robustness) dbr:Deba_1882 (138 target-flexibility) (66 robustness) dbr:Deba_2001 (212 target-flexibility) (73 robustness) dbr:Deba_2122 (790 target-flexibility) (134 robustness) dbr:Deba_2140 (0 target-flexibility) (0 robustness) dbr:Deba_2288 (0 target-flexibility) (0 robustness) dbr:Deba_2503 (790 target-flexibility) (134 robustness) dbr:Deba_2654 (897 target-flexibility) (71 robustness) dbr:Deba_2748 (0 target-flexibility) (0 robustness) dbr:Deba_2773 (0 target-flexibility) (0 robustness) dbr:Deba_2788 (239 target-flexibility) (67 robustness) dbr:Deba_2789 (67 target-flexibility) (67 robustness) dbr:Deba_2791 (140 target-flexibility) (71 robustness) dbr:Deba_2794 (70 target-flexibility) (70 robustness) dbr:Deba_3125 (732 target-flexibility) (78 robustness) dbr:Deba_3187 (790 target-flexibility) (134 robustness) dbr:Deba_3263 (358 target-flexibility) (104 robustness) dde:Dde_0033 (0 target-flexibility) (0 robustness) dde:Dde_0626 (405 target-flexibility) (70 robustness) dde:Dde_1725 (0 target-flexibility) (0 robustness) dde:Dde_2142 (222 target-flexibility) (83 robustness) dde:Dde_2182 (0 target-flexibility) (0 robustness) dde:Dde_2187 (0 target-flexibility) (0 robustness) dde:Dde_2317 (790 target-flexibility) (134 robustness) dde:Dde_2439 (0 target-flexibility) (0 robustness) dde:Dde_2648 (357 target-flexibility) (102 robustness) dde:Dde_2656 (0 target-flexibility) (0 robustness) dde:Dde_2823 (790 target-flexibility) (134 robustness) dde:Dde_2839 (212 target-flexibility) (73 robustness) dde:Dde_3180 (80 target-flexibility) (80 robustness) dde:Dde_3207 (790 target-flexibility) (134 robustness) dde:Dde_3222 (434 target-flexibility) (67 robustness) dde:Dde_3476 (289 target-flexibility) (73 robustness) dde:Dde_3691 (0 target-flexibility) (0 robustness) dds:Ddes_0025 (0 target-flexibility) (0 robustness) dds:Ddes_0101 (289 target-flexibility) (73 robustness) dds:Ddes_0385 (222 target-flexibility) (83 robustness) dds:Ddes_0509 (434 target-flexibility) (67 robustness) dds:Ddes_1253 (0 target-flexibility) (0 robustness) dds:Ddes_1300 (0 target-flexibility) (0 robustness) dds:Ddes_1623 (0 target-flexibility) (0 robustness) dds:Ddes_1748 (790 target-flexibility) (134 robustness) dds:Ddes_1950 (0 target-flexibility) (0 robustness) dds:Ddes_2017 (80 target-flexibility) (80 robustness) dds:Ddes_2073 (212 target-flexibility) (73 robustness) def:CNY67_00560 (289 target-flexibility) (73 robustness) def:CNY67_01730 (212 target-flexibility) (73 robustness) def:CNY67_03710 (790 target-flexibility) (134 robustness) def:CNY67_04820 (0 target-flexibility) (0 robustness) def:CNY67_08360 (0 target-flexibility) (0 robustness) def:CNY67_08465 (405 target-flexibility) (70 robustness) def:CNY67_11835 (434 target-flexibility) (67 robustness) def:CNY67_12850 (222 target-flexibility) (83 robustness) def:CNY67_14075 (357 target-flexibility) (102 robustness) dej:AWY79_00595 (790 target-flexibility) (134 robustness) dej:AWY79_00980 (790 target-flexibility) (134 robustness) dej:AWY79_01195 (790 target-flexibility) (134 robustness) dej:AWY79_02820 (0 target-flexibility) (0 robustness) dej:AWY79_03870 (752 target-flexibility) (76 robustness) dej:AWY79_04800 (212 target-flexibility) (73 robustness) dej:AWY79_05625 (0 target-flexibility) (0 robustness) dej:AWY79_10785 (434 target-flexibility) (67 robustness) dej:AWY79_10850 (0 target-flexibility) (0 robustness) dej:AWY79_12435 (528 target-flexibility) (157 robustness) dej:AWY79_12450 (222 target-flexibility) (83 robustness) dej:AWY79_13255 (206 target-flexibility) (68 robustness) dej:AWY79_15280 (358 target-flexibility) (104 robustness) dej:AWY79_15450 (289 target-flexibility) (73 robustness) dej:AWY79_17820 (0 target-flexibility) (0 robustness) des:DSOUD_0047 (796 target-flexibility) (85 robustness) des:DSOUD_0247 (80 target-flexibility) (80 robustness) des:DSOUD_0484 (222 target-flexibility) (83 robustness) des:DSOUD_0657 (1041 target-flexibility) (243 robustness) des:DSOUD_0923 (138 target-flexibility) (66 robustness) des:DSOUD_1127 (212 target-flexibility) (73 robustness) des:DSOUD_1475 (752 target-flexibility) (76 robustness) des:DSOUD_1660 (71 target-flexibility) (71 robustness) des:DSOUD_1686 (0 target-flexibility) (0 robustness) des:DSOUD_1782 (732 target-flexibility) (78 robustness) des:DSOUD_1879 (897 target-flexibility) (71 robustness) des:DSOUD_1909 (0 target-flexibility) (0 robustness) des:DSOUD_1920 (0 target-flexibility) (0 robustness) des:DSOUD_2288 (0 target-flexibility) (0 robustness) des:DSOUD_2394 (1169 target-flexibility) (76 robustness) des:DSOUD_2923 (70 target-flexibility) (70 robustness) des:DSOUD_2928 (67 target-flexibility) (67 robustness) des:DSOUD_2929 (239 target-flexibility) (67 robustness) des:DSOUD_3191 (0 target-flexibility) (0 robustness) des:DSOUD_3192 (0 target-flexibility) (0 robustness) deu:DBW_0440 (80 target-flexibility) (80 robustness) deu:DBW_0616 (796 target-flexibility) (85 robustness) deu:DBW_0759 (222 target-flexibility) (83 robustness) deu:DBW_0911 (138 target-flexibility) (66 robustness) deu:DBW_1650 (0 target-flexibility) (0 robustness) deu:DBW_1746 (732 target-flexibility) (78 robustness) deu:DBW_1916 (0 target-flexibility) (0 robustness) deu:DBW_1942 (897 target-flexibility) (71 robustness) deu:DBW_2132 (0 target-flexibility) (0 robustness) deu:DBW_2313 (0 target-flexibility) (0 robustness) deu:DBW_2425 (1169 target-flexibility) (76 robustness) deu:DBW_2639 (212 target-flexibility) (73 robustness) deu:DBW_2799 (70 target-flexibility) (70 robustness) deu:DBW_2804 (67 target-flexibility) (67 robustness) deu:DBW_2805 (239 target-flexibility) (67 robustness) deu:DBW_3054 (1041 target-flexibility) (243 robustness) deu:DBW_3264 (0 target-flexibility) (0 robustness) deu:DBW_3265 (0 target-flexibility) (0 robustness) dfi:AXF13_00145 (212 target-flexibility) (73 robustness) dfi:AXF13_00460 (434 target-flexibility) (67 robustness) dfi:AXF13_00525 (80 target-flexibility) (80 robustness) dfi:AXF13_00990 (222 target-flexibility) (83 robustness) dfi:AXF13_03820 (0 target-flexibility) (0 robustness) dfi:AXF13_05800 (1169 target-flexibility) (76 robustness) dfi:AXF13_05975 (0 target-flexibility) (0 robustness) dfi:AXF13_07230 (0 target-flexibility) (0 robustness) dfi:AXF13_10380 (790 target-flexibility) (134 robustness) dfi:AXF13_13155 (289 target-flexibility) (73 robustness) dfi:AXF13_13965 (1041 target-flexibility) (243 robustness) dgg:DGI_0026 (0 target-flexibility) (0 robustness) dgg:DGI_0069 (0 target-flexibility) (0 robustness) dgg:DGI_0581 (790 target-flexibility) (134 robustness) dgg:DGI_0738 (528 target-flexibility) (157 robustness) dgg:DGI_0864 (0 target-flexibility) (0 robustness) dgg:DGI_1348 (1041 target-flexibility) (243 robustness) dgg:DGI_1438 (790 target-flexibility) (134 robustness) dgg:DGI_1648 (212 target-flexibility) (73 robustness) dgg:DGI_1737 (790 target-flexibility) (134 robustness) dgg:DGI_1851 (289 target-flexibility) (73 robustness) dgg:DGI_1902 (0 target-flexibility) (0 robustness) dgg:DGI_2476 (0 target-flexibility) (0 robustness) dgg:DGI_2681 (358 target-flexibility) (104 robustness) dgg:DGI_2774 (222 target-flexibility) (83 robustness) dgg:DGI_2795 (1169 target-flexibility) (76 robustness) dgg:DGI_3014 (0 target-flexibility) (0 robustness) dgg:DGI_3260 (434 target-flexibility) (67 robustness) dgg:DGI_4014 (0 target-flexibility) (0 robustness) dhy:DESAM_10054 (71 target-flexibility) (71 robustness) dhy:DESAM_10157 (358 target-flexibility) (104 robustness) dhy:DESAM_20147 (80 target-flexibility) (80 robustness) dhy:DESAM_20155 (0 target-flexibility) (0 robustness) dhy:DESAM_20160 (1169 target-flexibility) (76 robustness) dhy:DESAM_20254 (0 target-flexibility) (0 robustness) dhy:DESAM_20338 (796 target-flexibility) (85 robustness) dhy:DESAM_20480 (212 target-flexibility) (73 robustness) dhy:DESAM_20564 (790 target-flexibility) (134 robustness) dhy:DESAM_20574 (752 target-flexibility) (76 robustness) dhy:DESAM_20586 (528 target-flexibility) (157 robustness) dhy:DESAM_20633 (790 target-flexibility) (134 robustness) dhy:DESAM_20710 (897 target-flexibility) (71 robustness) dhy:DESAM_20726 (0 target-flexibility) (0 robustness) dhy:DESAM_20863 (790 target-flexibility) (134 robustness) dhy:DESAM_20916 (0 target-flexibility) (0 robustness) dhy:DESAM_20933 (0 target-flexibility) (0 robustness) dhy:DESAM_21173 (1041 target-flexibility) (243 robustness) dhy:DESAM_21598 (0 target-flexibility) (0 robustness) dhy:DESAM_21612 (790 target-flexibility) (134 robustness) dhy:DESAM_21680 (289 target-flexibility) (73 robustness) dhy:DESAM_21809 (206 target-flexibility) (68 robustness) dhy:DESAM_21837 (0 target-flexibility) (0 robustness) dhy:DESAM_21926 (434 target-flexibility) (67 robustness) dhy:DESAM_22057 (0 target-flexibility) (0 robustness) dhy:DESAM_22216 (0 target-flexibility) (0 robustness) dhy:DESAM_22252 (222 target-flexibility) (83 robustness) dhy:DESAM_22412 (138 target-flexibility) (66 robustness) dhy:DESAM_22470 (732 target-flexibility) (78 robustness) dma:DMR_00110 (0 target-flexibility) (0 robustness) dma:DMR_02050 (212 target-flexibility) (73 robustness) dma:DMR_04560 (0 target-flexibility) (0 robustness) dma:DMR_16010 (434 target-flexibility) (67 robustness) dma:DMR_17120 (528 target-flexibility) (157 robustness) dma:DMR_22170 (222 target-flexibility) (83 robustness) dma:DMR_28220 (289 target-flexibility) (73 robustness) dma:DMR_28600 (0 target-flexibility) (0 robustness) dma:DMR_30710 (358 target-flexibility) (104 robustness) dma:DMR_37140 (528 target-flexibility) (157 robustness) dma:DMR_39860 (357 target-flexibility) (102 robustness) dma:DMR_44510 (405 target-flexibility) (70 robustness) dml:Dmul_07490 (0 target-flexibility) (0 robustness) dml:Dmul_08540 (0 target-flexibility) (0 robustness) dml:Dmul_08960 (289 target-flexibility) (73 robustness) dml:Dmul_09580 (0 target-flexibility) (0 robustness) dml:Dmul_14330 (358 target-flexibility) (104 robustness) dml:Dmul_18930 (71 target-flexibility) (71 robustness) dml:Dmul_19320 (790 target-flexibility) (134 robustness) dml:Dmul_20590 (222 target-flexibility) (83 robustness) dml:Dmul_21250 (0 target-flexibility) (0 robustness) dml:Dmul_21830 (790 target-flexibility) (134 robustness) dml:Dmul_22810 (0 target-flexibility) (0 robustness) dml:Dmul_22850 (752 target-flexibility) (76 robustness) dml:Dmul_23280 (0 target-flexibility) (0 robustness) dml:Dmul_23620 (790 target-flexibility) (134 robustness) dml:Dmul_24040 (0 target-flexibility) (0 robustness) dml:Dmul_24260 (0 target-flexibility) (0 robustness) dml:Dmul_24630 (0 target-flexibility) (0 robustness) dml:Dmul_25380 (528 target-flexibility) (157 robustness) dml:Dmul_27750 (70 target-flexibility) (70 robustness) dml:Dmul_27780 (140 target-flexibility) (71 robustness) dml:Dmul_27800 (67 target-flexibility) (67 robustness) dml:Dmul_27810 (239 target-flexibility) (67 robustness) dml:Dmul_28300 (0 target-flexibility) (0 robustness) dml:Dmul_35620 (434 target-flexibility) (67 robustness) dml:Dmul_36880 (0 target-flexibility) (0 robustness) dml:Dmul_38810 (212 target-flexibility) (73 robustness) doa:AXF15_00335 (732 target-flexibility) (78 robustness) doa:AXF15_02145 (138 target-flexibility) (66 robustness) doa:AXF15_02215 (0 target-flexibility) (0 robustness) doa:AXF15_03265 (790 target-flexibility) (134 robustness) doa:AXF15_03465 (0 target-flexibility) (0 robustness) doa:AXF15_03650 (80 target-flexibility) (80 robustness) doa:AXF15_04445 (0 target-flexibility) (0 robustness) doa:AXF15_04820 (796 target-flexibility) (85 robustness) doa:AXF15_05040 (897 target-flexibility) (71 robustness) doa:AXF15_06400 (0 target-flexibility) (0 robustness) doa:AXF15_07625 (528 target-flexibility) (157 robustness) doa:AXF15_08605 (222 target-flexibility) (83 robustness) doa:AXF15_08610 (0 target-flexibility) (0 robustness) doa:AXF15_08670 (289 target-flexibility) (73 robustness) doa:AXF15_09390 (790 target-flexibility) (134 robustness) doa:AXF15_09515 (358 target-flexibility) (104 robustness) doa:AXF15_09785 (790 target-flexibility) (134 robustness) doa:AXF15_11375 (0 target-flexibility) (0 robustness) doa:AXF15_11595 (212 target-flexibility) (73 robustness) doa:AXF15_11865 (434 target-flexibility) (67 robustness) dol:Dole_0337 (0 target-flexibility) (0 robustness) dol:Dole_0514 (897 target-flexibility) (71 robustness) dol:Dole_0670 (752 target-flexibility) (76 robustness) dol:Dole_0679 (0 target-flexibility) (0 robustness) dol:Dole_1010 (0 target-flexibility) (0 robustness) dol:Dole_1130 (1041 target-flexibility) (243 robustness) dol:Dole_1191 (222 target-flexibility) (83 robustness) dol:Dole_1545 (80 target-flexibility) (80 robustness) dol:Dole_1662 (1169 target-flexibility) (76 robustness) dol:Dole_1729 (212 target-flexibility) (73 robustness) dol:Dole_1848 (0 target-flexibility) (0 robustness) dol:Dole_1908 (289 target-flexibility) (73 robustness) dol:Dole_1973 (790 target-flexibility) (134 robustness) dol:Dole_1975 (790 target-flexibility) (134 robustness) dol:Dole_2219 (434 target-flexibility) (67 robustness) dol:Dole_2324 (0 target-flexibility) (0 robustness) dol:Dole_2438 (0 target-flexibility) (0 robustness) dol:Dole_2492 (138 target-flexibility) (66 robustness) dol:Dole_2786 (70 target-flexibility) (70 robustness) dol:Dole_2791 (67 target-flexibility) (67 robustness) dol:Dole_2792 (239 target-flexibility) (67 robustness) dol:Dole_2847 (71 target-flexibility) (71 robustness) dpb:BABL1_gene_13 (0 target-flexibility) (0 robustness) dpb:BABL1_gene_199 (212 target-flexibility) (73 robustness) dpb:BABL1_gene_330 (752 target-flexibility) (76 robustness) dpb:BABL1_gene_705 (71 target-flexibility) (71 robustness) dpb:BABL1_gene_858 (222 target-flexibility) (83 robustness) dpg:DESPIGER_0283 (0 target-flexibility) (0 robustness) dpg:DESPIGER_0323 (0 target-flexibility) (0 robustness) dpg:DESPIGER_0969 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1079 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1250 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1284 (222 target-flexibility) (83 robustness) dpg:DESPIGER_1297 (790 target-flexibility) (134 robustness) dpg:DESPIGER_1531 (80 target-flexibility) (80 robustness) dpg:DESPIGER_1545 (434 target-flexibility) (67 robustness) dpg:DESPIGER_1797 (289 target-flexibility) (73 robustness) dpg:DESPIGER_1913 (0 target-flexibility) (0 robustness) dpg:DESPIGER_1949 (0 target-flexibility) (0 robustness) dpg:DESPIGER_2129 (212 target-flexibility) (73 robustness) dpi:BN4_10115 (434 target-flexibility) (67 robustness) dpi:BN4_10127 (0 target-flexibility) (0 robustness) dpi:BN4_10196 (71 target-flexibility) (71 robustness) dpi:BN4_10393 (222 target-flexibility) (83 robustness) dpi:BN4_10396 (528 target-flexibility) (157 robustness) dpi:BN4_11008 (358 target-flexibility) (104 robustness) dpi:BN4_11230 (528 target-flexibility) (157 robustness) dpi:BN4_11407 (289 target-flexibility) (73 robustness) dpi:BN4_11936 (212 target-flexibility) (73 robustness) dpi:BN4_11977 (752 target-flexibility) (76 robustness) dpi:BN4_12054 (790 target-flexibility) (134 robustness) dpi:BN4_12214 (0 target-flexibility) (0 robustness) dpi:BN4_12384 (790 target-flexibility) (134 robustness) dpi:BN4_12584 (790 target-flexibility) (134 robustness) dpi:BN4_12643 (0 target-flexibility) (0 robustness) dpi:BN4_12812 (0 target-flexibility) (0 robustness) dpr:Despr_0279 (0 target-flexibility) (0 robustness) dpr:Despr_0517 (138 target-flexibility) (66 robustness) dpr:Despr_0555 (0 target-flexibility) (0 robustness) dpr:Despr_0574 (289 target-flexibility) (73 robustness) dpr:Despr_0909 (434 target-flexibility) (67 robustness) dpr:Despr_0918 (71 target-flexibility) (71 robustness) dpr:Despr_1050 (1385 target-flexibility) (204 robustness) dpr:Despr_1832 (0 target-flexibility) (0 robustness) dpr:Despr_2394 (222 target-flexibility) (83 robustness) dpr:Despr_2467 (0 target-flexibility) (0 robustness) dpr:Despr_2776 (752 target-flexibility) (76 robustness) dpr:Despr_2958 (80 target-flexibility) (80 robustness) dpr:Despr_2989 (528 target-flexibility) (157 robustness) dpr:Despr_3037 (212 target-flexibility) (73 robustness) dpr:Despr_3156 (897 target-flexibility) (71 robustness) dpr:Despr_3168 (0 target-flexibility) (0 robustness) dpr:Despr_3183 (358 target-flexibility) (104 robustness) dps:DP0045 (0 target-flexibility) (0 robustness) dps:DP0106 (897 target-flexibility) (71 robustness) dps:DP0437 (138 target-flexibility) (66 robustness) dps:DP0555 (0 target-flexibility) (0 robustness) dps:DP0812 (80 target-flexibility) (80 robustness) dps:DP1331 (206 target-flexibility) (68 robustness) dps:DP1629 (71 target-flexibility) (71 robustness) dps:DP1796 (212 target-flexibility) (73 robustness) dps:DP2097 (790 target-flexibility) (134 robustness) dps:DP2220 (0 target-flexibility) (0 robustness) dps:DP2548 (0 target-flexibility) (0 robustness) dps:DP2552 (222 target-flexibility) (83 robustness) dps:DP2600 (0 target-flexibility) (0 robustness) dps:DP2716 (0 target-flexibility) (0 robustness) dps:DPPB37 (790 target-flexibility) (134 robustness) drt:Dret_0014 (752 target-flexibility) (76 robustness) drt:Dret_0143 (796 target-flexibility) (85 robustness) drt:Dret_0251 (212 target-flexibility) (73 robustness) drt:Dret_0307 (0 target-flexibility) (0 robustness) drt:Dret_0321 (732 target-flexibility) (78 robustness) drt:Dret_0439 (289 target-flexibility) (73 robustness) drt:Dret_0818 (790 target-flexibility) (134 robustness) drt:Dret_0830 (358 target-flexibility) (104 robustness) drt:Dret_1046 (0 target-flexibility) (0 robustness) drt:Dret_1100 (434 target-flexibility) (67 robustness) drt:Dret_1118 (222 target-flexibility) (83 robustness) drt:Dret_1384 (405 target-flexibility) (70 robustness) drt:Dret_1385 (528 target-flexibility) (157 robustness) drt:Dret_1409 (357 target-flexibility) (102 robustness) drt:Dret_1425 (0 target-flexibility) (0 robustness) drt:Dret_1756 (0 target-flexibility) (0 robustness) drt:Dret_2132 (790 target-flexibility) (134 robustness) drt:Dret_2234 (71 target-flexibility) (71 robustness) drt:Dret_2421 (80 target-flexibility) (80 robustness) drt:Dret_2481 (790 target-flexibility) (134 robustness) drt:Dret_2499 (0 target-flexibility) (0 robustness) dsa:Desal_0017 (897 target-flexibility) (71 robustness) dsa:Desal_0092 (790 target-flexibility) (134 robustness) dsa:Desal_0136 (528 target-flexibility) (157 robustness) dsa:Desal_0143 (752 target-flexibility) (76 robustness) dsa:Desal_0152 (790 target-flexibility) (134 robustness) dsa:Desal_0178 (0 target-flexibility) (0 robustness) dsa:Desal_0250 (212 target-flexibility) (73 robustness) dsa:Desal_0558 (1041 target-flexibility) (243 robustness) dsa:Desal_0574 (1041 target-flexibility) (243 robustness) dsa:Desal_0650 (0 target-flexibility) (0 robustness) dsa:Desal_0740 (1169 target-flexibility) (76 robustness) dsa:Desal_0743 (0 target-flexibility) (0 robustness) dsa:Desal_0753 (80 target-flexibility) (80 robustness) dsa:Desal_1093 (289 target-flexibility) (73 robustness) dsa:Desal_1585 (434 target-flexibility) (67 robustness) dsa:Desal_1645 (0 target-flexibility) (0 robustness) dsa:Desal_1784 (138 target-flexibility) (66 robustness) dsa:Desal_2004 (222 target-flexibility) (83 robustness) dsa:Desal_2033 (0 target-flexibility) (0 robustness) dsa:Desal_2170 (732 target-flexibility) (78 robustness) dsa:Desal_2527 (71 target-flexibility) (71 robustness) dsa:Desal_2682 (0 target-flexibility) (0 robustness) dsa:Desal_2829 (790 target-flexibility) (134 robustness) dsa:Desal_2862 (358 target-flexibility) (104 robustness) dsa:Desal_2978 (0 target-flexibility) (0 robustness) dsa:Desal_3407 (1385 target-flexibility) (204 robustness) dsa:Desal_3566 (796 target-flexibility) (85 robustness) dsa:Desal_3834 (0 target-flexibility) (0 robustness) dsf:UWK_00105 (528 target-flexibility) (157 robustness) dsf:UWK_00180 (212 target-flexibility) (73 robustness) dsf:UWK_00683 (138 target-flexibility) (66 robustness) dsf:UWK_00793 (897 target-flexibility) (71 robustness) dsf:UWK_01152 (752 target-flexibility) (76 robustness) dsf:UWK_01260 (732 target-flexibility) (78 robustness) dsf:UWK_01662 (80 target-flexibility) (80 robustness) dsf:UWK_01819 (358 target-flexibility) (104 robustness) dsf:UWK_02513 (0 target-flexibility) (0 robustness) dsf:UWK_02514 (1169 target-flexibility) (76 robustness) dsf:UWK_02797 (1041 target-flexibility) (243 robustness) dsf:UWK_02799 (0 target-flexibility) (0 robustness) dsf:UWK_03000 (72 target-flexibility) (72 robustness) dsf:UWK_03057 (0 target-flexibility) (0 robustness) dsf:UWK_03406 (0 target-flexibility) (0 robustness) dsf:UWK_03410 (222 target-flexibility) (83 robustness) dsf:UWK_03421 (0 target-flexibility) (0 robustness) dsf:UWK_03510 (796 target-flexibility) (85 robustness) dsf:UWK_03535 (71 target-flexibility) (71 robustness) dti:Desti_0148 (1041 target-flexibility) (243 robustness) dti:Desti_0219 (790 target-flexibility) (134 robustness) dti:Desti_0225 (0 target-flexibility) (0 robustness) dti:Desti_0353 (0 target-flexibility) (0 robustness) dti:Desti_0473 (0 target-flexibility) (0 robustness) dti:Desti_0901 (0 target-flexibility) (0 robustness) dti:Desti_1152 (206 target-flexibility) (68 robustness) dti:Desti_1259 (752 target-flexibility) (76 robustness) dti:Desti_1366 (0 target-flexibility) (0 robustness) dti:Desti_1457 (0 target-flexibility) (0 robustness) dti:Desti_1492 (1169 target-flexibility) (76 robustness) dti:Desti_1700 (387 target-flexibility) (72 robustness) dti:Desti_1808 (0 target-flexibility) (0 robustness) dti:Desti_2003 (0 target-flexibility) (0 robustness) dti:Desti_2341 (790 target-flexibility) (134 robustness) dti:Desti_2345 (790 target-flexibility) (134 robustness) dti:Desti_2348 (790 target-flexibility) (134 robustness) dti:Desti_2479 (0 target-flexibility) (0 robustness) dti:Desti_2739 (0 target-flexibility) (0 robustness) dti:Desti_2740 (0 target-flexibility) (0 robustness) dti:Desti_2797 (0 target-flexibility) (0 robustness) dti:Desti_3121 (71 target-flexibility) (71 robustness) dti:Desti_3164 (0 target-flexibility) (0 robustness) dti:Desti_3650 (0 target-flexibility) (0 robustness) dti:Desti_3684 (212 target-flexibility) (73 robustness) dti:Desti_3693 (0 target-flexibility) (0 robustness) dti:Desti_3747 (80 target-flexibility) (80 robustness) dti:Desti_3834 (0 target-flexibility) (0 robustness) dti:Desti_4083 (222 target-flexibility) (83 robustness) dti:Desti_4150 (434 target-flexibility) (67 robustness) dti:Desti_4164 (790 target-flexibility) (134 robustness) dti:Desti_4253 (289 target-flexibility) (73 robustness) dti:Desti_4337 (0 target-flexibility) (0 robustness) dti:Desti_4704 (239 target-flexibility) (67 robustness) dti:Desti_4705 (67 target-flexibility) (67 robustness) dti:Desti_4907 (0 target-flexibility) (0 robustness) dto:TOL2_C02640 (528 target-flexibility) (157 robustness) dto:TOL2_C05220 (790 target-flexibility) (134 robustness) dto:TOL2_C08210 (0 target-flexibility) (0 robustness) dto:TOL2_C12360 (0 target-flexibility) (0 robustness) dto:TOL2_C13310 (358 target-flexibility) (104 robustness) dto:TOL2_C16510 (212 target-flexibility) (73 robustness) dto:TOL2_C21050 (222 target-flexibility) (83 robustness) dto:TOL2_C21920 (897 target-flexibility) (71 robustness) dto:TOL2_C22640 (0 target-flexibility) (0 robustness) dto:TOL2_C23400 (0 target-flexibility) (0 robustness) dto:TOL2_C24560 (138 target-flexibility) (66 robustness) dto:TOL2_C26900 (0 target-flexibility) (0 robustness) dto:TOL2_C27090 (0 target-flexibility) (0 robustness) dto:TOL2_C27260 (0 target-flexibility) (0 robustness) dto:TOL2_C27460 (0 target-flexibility) (0 robustness) dto:TOL2_C27650 (0 target-flexibility) (0 robustness) dto:TOL2_C31520 (790 target-flexibility) (134 robustness) dto:TOL2_C35200 (0 target-flexibility) (0 robustness) dto:TOL2_C35290 (0 target-flexibility) (0 robustness) dto:TOL2_C37120 (0 target-flexibility) (0 robustness) dvu:DVU0477 (289 target-flexibility) (73 robustness) dvu:DVU0732 (212 target-flexibility) (73 robustness) dvu:DVU0748 (790 target-flexibility) (134 robustness) dvu:DVU1196 (0 target-flexibility) (0 robustness) dvu:DVU1350 (1169 target-flexibility) (76 robustness) dvu:DVU1360 (0 target-flexibility) (0 robustness) dvu:DVU1364 (0 target-flexibility) (0 robustness) dvu:DVU1453 (0 target-flexibility) (0 robustness) dvu:DVU1927 (222 target-flexibility) (83 robustness) dvu:DVU2250 (790 target-flexibility) (134 robustness) dvu:DVU2530 (1041 target-flexibility) (243 robustness) dvu:DVU2559 (0 target-flexibility) (0 robustness) dvu:DVU2969 (790 target-flexibility) (134 robustness) dvu:DVU2985 (434 target-flexibility) (67 robustness) dvu:DVU3119 (0 target-flexibility) (0 robustness) dvu:DVU3168 (80 target-flexibility) (80 robustness) dvu:DVU3356 (0 target-flexibility) (0 robustness) gao:A2G06_03585 (1169 target-flexibility) (76 robustness) gao:A2G06_05670 (0 target-flexibility) (0 robustness) gao:A2G06_05980 (71 target-flexibility) (71 robustness) gao:A2G06_06115 (0 target-flexibility) (0 robustness) gao:A2G06_06270 (0 target-flexibility) (0 robustness) gao:A2G06_06650 (212 target-flexibility) (73 robustness) gao:A2G06_08130 (1169 target-flexibility) (76 robustness) gao:A2G06_09675 (752 target-flexibility) (76 robustness) gao:A2G06_10540 (897 target-flexibility) (71 robustness) gao:A2G06_12745 (0 target-flexibility) (0 robustness) gao:A2G06_13760 (1041 target-flexibility) (243 robustness) gao:A2G06_14560 (0 target-flexibility) (0 robustness) gao:A2G06_14565 (0 target-flexibility) (0 robustness) gao:A2G06_14765 (222 target-flexibility) (83 robustness) gao:A2G06_15675 (138 target-flexibility) (66 robustness) gbm:Gbem_0280 (1041 target-flexibility) (243 robustness) gbm:Gbem_0486 (239 target-flexibility) (67 robustness) gbm:Gbem_0487 (67 target-flexibility) (67 robustness) gbm:Gbem_0751 (0 target-flexibility) (0 robustness) gbm:Gbem_0836 (71 target-flexibility) (71 robustness) gbm:Gbem_0861 (0 target-flexibility) (0 robustness) gbm:Gbem_1258 (1169 target-flexibility) (76 robustness) gbm:Gbem_1531 (212 target-flexibility) (73 robustness) gbm:Gbem_1896 (897 target-flexibility) (71 robustness) gbm:Gbem_2051 (0 target-flexibility) (0 robustness) gbm:Gbem_2903 (752 target-flexibility) (76 robustness) gbm:Gbem_3346 (0 target-flexibility) (0 robustness) gbm:Gbem_3362 (1169 target-flexibility) (76 robustness) gbm:Gbem_3637 (138 target-flexibility) (66 robustness) gbm:Gbem_3650 (222 target-flexibility) (83 robustness) gbm:Gbem_3700 (0 target-flexibility) (0 robustness) gbm:Gbem_3701 (0 target-flexibility) (0 robustness) gbm:Gbem_3927 (80 target-flexibility) (80 robustness) geb:GM18_0317 (1041 target-flexibility) (243 robustness) geb:GM18_0730 (71 target-flexibility) (71 robustness) geb:GM18_0750 (0 target-flexibility) (0 robustness) geb:GM18_0958 (790 target-flexibility) (134 robustness) geb:GM18_1116 (1169 target-flexibility) (76 robustness) geb:GM18_1366 (212 target-flexibility) (73 robustness) geb:GM18_1602 (0 target-flexibility) (0 robustness) geb:GM18_1720 (897 target-flexibility) (71 robustness) geb:GM18_2157 (0 target-flexibility) (0 robustness) geb:GM18_2790 (752 target-flexibility) (76 robustness) geb:GM18_3257 (0 target-flexibility) (0 robustness) geb:GM18_3424 (0 target-flexibility) (0 robustness) geb:GM18_3441 (1169 target-flexibility) (76 robustness) geb:GM18_3598 (0 target-flexibility) (0 robustness) geb:GM18_3889 (140 target-flexibility) (71 robustness) geb:GM18_3891 (67 target-flexibility) (67 robustness) geb:GM18_3892 (239 target-flexibility) (67 robustness) geb:GM18_4095 (138 target-flexibility) (66 robustness) geb:GM18_4108 (222 target-flexibility) (83 robustness) geb:GM18_4149 (0 target-flexibility) (0 robustness) geb:GM18_4150 (0 target-flexibility) (0 robustness) geb:GM18_4171 (0 target-flexibility) (0 robustness) geb:GM18_4391 (80 target-flexibility) (80 robustness) gem:GM21_0265 (1041 target-flexibility) (243 robustness) gem:GM21_0503 (239 target-flexibility) (67 robustness) gem:GM21_0504 (67 target-flexibility) (67 robustness) gem:GM21_0506 (140 target-flexibility) (71 robustness) gem:GM21_0509 (70 target-flexibility) (70 robustness) gem:GM21_0766 (0 target-flexibility) (0 robustness) gem:GM21_0883 (1169 target-flexibility) (76 robustness) gem:GM21_0899 (0 target-flexibility) (0 robustness) gem:GM21_1322 (752 target-flexibility) (76 robustness) gem:GM21_2166 (0 target-flexibility) (0 robustness) gem:GM21_2312 (897 target-flexibility) (71 robustness) gem:GM21_2685 (212 target-flexibility) (73 robustness) gem:GM21_3025 (1169 target-flexibility) (76 robustness) gem:GM21_3397 (1041 target-flexibility) (243 robustness) gem:GM21_3403 (0 target-flexibility) (0 robustness) gem:GM21_3424 (71 target-flexibility) (71 robustness) gem:GM21_3742 (138 target-flexibility) (66 robustness) gem:GM21_3757 (222 target-flexibility) (83 robustness) gem:GM21_3795 (0 target-flexibility) (0 robustness) gem:GM21_3796 (0 target-flexibility) (0 robustness) gem:GM21_4011 (80 target-flexibility) (80 robustness) geo:Geob_0284 (0 target-flexibility) (0 robustness) geo:Geob_0392 (222 target-flexibility) (83 robustness) geo:Geob_0461 (80 target-flexibility) (80 robustness) geo:Geob_0666 (1041 target-flexibility) (243 robustness) geo:Geob_0692 (0 target-flexibility) (0 robustness) geo:Geob_0693 (0 target-flexibility) (0 robustness) geo:Geob_0775 (239 target-flexibility) (67 robustness) geo:Geob_0776 (67 target-flexibility) (67 robustness) geo:Geob_0778 (140 target-flexibility) (71 robustness) geo:Geob_0781 (70 target-flexibility) (70 robustness) geo:Geob_1002 (1041 target-flexibility) (243 robustness) geo:Geob_1123 (138 target-flexibility) (66 robustness) geo:Geob_1368 (1041 target-flexibility) (243 robustness) geo:Geob_1870 (0 target-flexibility) (0 robustness) geo:Geob_2094 (71 target-flexibility) (71 robustness) geo:Geob_2171 (0 target-flexibility) (0 robustness) geo:Geob_2629 (1169 target-flexibility) (76 robustness) geo:Geob_2661 (752 target-flexibility) (76 robustness) geo:Geob_2923 (0 target-flexibility) (0 robustness) geo:Geob_3010 (0 target-flexibility) (0 robustness) geo:Geob_3082 (212 target-flexibility) (73 robustness) geo:Geob_3264 (897 target-flexibility) (71 robustness) geo:Geob_3664 (1169 target-flexibility) (76 robustness) glo:Glov_0479 (0 target-flexibility) (0 robustness) glo:Glov_0584 (357 target-flexibility) (102 robustness) glo:Glov_0674 (67 target-flexibility) (67 robustness) glo:Glov_0675 (239 target-flexibility) (67 robustness) glo:Glov_0757 (71 target-flexibility) (71 robustness) glo:Glov_0796 (1041 target-flexibility) (243 robustness) glo:Glov_0981 (222 target-flexibility) (83 robustness) glo:Glov_1018 (0 target-flexibility) (0 robustness) glo:Glov_1019 (0 target-flexibility) (0 robustness) glo:Glov_1622 (752 target-flexibility) (76 robustness) glo:Glov_1658 (0 target-flexibility) (0 robustness) glo:Glov_2085 (897 target-flexibility) (71 robustness) glo:Glov_2116 (0 target-flexibility) (0 robustness) glo:Glov_2128 (405 target-flexibility) (70 robustness) glo:Glov_2182 (1169 target-flexibility) (76 robustness) glo:Glov_2235 (1169 target-flexibility) (76 robustness) glo:Glov_2247 (0 target-flexibility) (0 robustness) glo:Glov_2538 (212 target-flexibility) (73 robustness) glo:Glov_3139 (80 target-flexibility) (80 robustness) glo:Glov_3149 (138 target-flexibility) (66 robustness) glo:Glov_3365 (0 target-flexibility) (0 robustness) gme:Gmet_0205 (138 target-flexibility) (66 robustness) gme:Gmet_0351 (222 target-flexibility) (83 robustness) gme:Gmet_0388 (0 target-flexibility) (0 robustness) gme:Gmet_0389 (0 target-flexibility) (0 robustness) gme:Gmet_0407 (239 target-flexibility) (67 robustness) gme:Gmet_0408 (67 target-flexibility) (67 robustness) gme:Gmet_0410 (140 target-flexibility) (71 robustness) gme:Gmet_0413 (70 target-flexibility) (70 robustness) gme:Gmet_0552 (1041 target-flexibility) (243 robustness) gme:Gmet_0956 (212 target-flexibility) (73 robustness) gme:Gmet_1357 (752 target-flexibility) (76 robustness) gme:Gmet_1580 (0 target-flexibility) (0 robustness) gme:Gmet_1613 (0 target-flexibility) (0 robustness) gme:Gmet_1769 (897 target-flexibility) (71 robustness) gme:Gmet_1934 (1169 target-flexibility) (76 robustness) gme:Gmet_2229 (0 target-flexibility) (0 robustness) gme:Gmet_2300 (0 target-flexibility) (0 robustness) gme:Gmet_2329 (0 target-flexibility) (0 robustness) gme:Gmet_2330 (0 target-flexibility) (0 robustness) gme:Gmet_2340 (790 target-flexibility) (134 robustness) gme:Gmet_2360 (71 target-flexibility) (71 robustness) gme:Gmet_2473 (0 target-flexibility) (0 robustness) gme:Gmet_2822 (1169 target-flexibility) (76 robustness) gme:Gmet_3356 (80 target-flexibility) (80 robustness) gpi:GPICK_00285 (405 target-flexibility) (70 robustness) gpi:GPICK_01450 (138 target-flexibility) (66 robustness) gpi:GPICK_02075 (222 target-flexibility) (83 robustness) gpi:GPICK_02235 (0 target-flexibility) (0 robustness) gpi:GPICK_02240 (0 target-flexibility) (0 robustness) gpi:GPICK_02335 (239 target-flexibility) (67 robustness) gpi:GPICK_02340 (67 target-flexibility) (67 robustness) gpi:GPICK_02900 (1041 target-flexibility) (243 robustness) gpi:GPICK_04075 (1169 target-flexibility) (76 robustness) gpi:GPICK_05460 (212 target-flexibility) (73 robustness) gpi:GPICK_06970 (357 target-flexibility) (102 robustness) gpi:GPICK_07275 (1169 target-flexibility) (76 robustness) gpi:GPICK_07650 (0 target-flexibility) (0 robustness) gpi:GPICK_07830 (0 target-flexibility) (0 robustness) gpi:GPICK_08380 (732 target-flexibility) (78 robustness) gpi:GPICK_08745 (752 target-flexibility) (76 robustness) gpi:GPICK_09850 (897 target-flexibility) (71 robustness) gpi:GPICK_10225 (0 target-flexibility) (0 robustness) gpi:GPICK_10370 (0 target-flexibility) (0 robustness) gpi:GPICK_10380 (0 target-flexibility) (0 robustness) gpi:GPICK_10520 (71 target-flexibility) (71 robustness) gpi:GPICK_11740 (0 target-flexibility) (0 robustness) gpi:GPICK_15315 (80 target-flexibility) (80 robustness) gpi:GPICK_15365 (796 target-flexibility) (85 robustness) gsb:GSUB_00615 (80 target-flexibility) (80 robustness) gsb:GSUB_01730 (222 target-flexibility) (83 robustness) gsb:GSUB_02190 (796 target-flexibility) (85 robustness) gsb:GSUB_02540 (0 target-flexibility) (0 robustness) gsb:GSUB_02545 (0 target-flexibility) (0 robustness) gsb:GSUB_02815 (1041 target-flexibility) (243 robustness) gsb:GSUB_03040 (138 target-flexibility) (66 robustness) gsb:GSUB_04800 (752 target-flexibility) (76 robustness) gsb:GSUB_06155 (1169 target-flexibility) (76 robustness) gsb:GSUB_07600 (0 target-flexibility) (0 robustness) gsb:GSUB_08195 (0 target-flexibility) (0 robustness) gsb:GSUB_08845 (0 target-flexibility) (0 robustness) gsb:GSUB_09020 (0 target-flexibility) (0 robustness) gsb:GSUB_09180 (897 target-flexibility) (71 robustness) gsb:GSUB_09375 (732 target-flexibility) (78 robustness) gsb:GSUB_10480 (71 target-flexibility) (71 robustness) gsb:GSUB_11175 (212 target-flexibility) (73 robustness) gsb:GSUB_12985 (70 target-flexibility) (70 robustness) gsb:GSUB_13010 (67 target-flexibility) (67 robustness) gsb:GSUB_13015 (239 target-flexibility) (67 robustness) gsb:GSUB_15430 (0 target-flexibility) (0 robustness) gsu:GSU0152 (138 target-flexibility) (66 robustness) gsu:GSU0337 (80 target-flexibility) (80 robustness) gsu:GSU0686 (1169 target-flexibility) (76 robustness) gsu:GSU1271 (897 target-flexibility) (71 robustness) gsu:GSU1463 (752 target-flexibility) (76 robustness) gsu:GSU1582 (0 target-flexibility) (0 robustness) gsu:GSU1764 (1169 target-flexibility) (76 robustness) gsu:GSU2045 (212 target-flexibility) (73 robustness) gsu:GSU2209 (0 target-flexibility) (0 robustness) gsu:GSU2241 (0 target-flexibility) (0 robustness) gsu:GSU2271 (71 target-flexibility) (71 robustness) gsu:GSU2366 (0 target-flexibility) (0 robustness) gsu:GSU2918 (1041 target-flexibility) (243 robustness) gsu:GSU3095 (0 target-flexibility) (0 robustness) gsu:GSU3096 (0 target-flexibility) (0 robustness) gsu:GSU3136 (222 target-flexibility) (83 robustness) gur:Gura_0227 (138 target-flexibility) (66 robustness) gur:Gura_0492 (1041 target-flexibility) (243 robustness) gur:Gura_1018 (1169 target-flexibility) (76 robustness) gur:Gura_1685 (0 target-flexibility) (0 robustness) gur:Gura_1799 (212 target-flexibility) (73 robustness) gur:Gura_1856 (897 target-flexibility) (71 robustness) gur:Gura_2175 (1169 target-flexibility) (76 robustness) gur:Gura_2196 (752 target-flexibility) (76 robustness) gur:Gura_2244 (0 target-flexibility) (0 robustness) gur:Gura_2598 (0 target-flexibility) (0 robustness) gur:Gura_3134 (0 target-flexibility) (0 robustness) gur:Gura_3240 (71 target-flexibility) (71 robustness) gur:Gura_3273 (0 target-flexibility) (0 robustness) gur:Gura_3978 (67 target-flexibility) (67 robustness) gur:Gura_3979 (239 target-flexibility) (67 robustness) gur:Gura_4053 (0 target-flexibility) (0 robustness) gur:Gura_4054 (0 target-flexibility) (0 robustness) gur:Gura_4245 (80 target-flexibility) (80 robustness) gur:Gura_4313 (222 target-flexibility) (83 robustness) hmr:Hipma_0012 (1041 target-flexibility) (243 robustness) hmr:Hipma_0121 (138 target-flexibility) (66 robustness) hmr:Hipma_0215 (0 target-flexibility) (0 robustness) hmr:Hipma_0301 (222 target-flexibility) (83 robustness) hmr:Hipma_0341 (71 target-flexibility) (71 robustness) hmr:Hipma_0412 (0 target-flexibility) (0 robustness) hmr:Hipma_0431 (752 target-flexibility) (76 robustness) hmr:Hipma_0501 (897 target-flexibility) (71 robustness) hmr:Hipma_0845 (80 target-flexibility) (80 robustness) hmr:Hipma_0985 (1169 target-flexibility) (76 robustness) hmr:Hipma_1016 (212 target-flexibility) (73 robustness) hmr:Hipma_1025 (1385 target-flexibility) (204 robustness) hmr:Hipma_1045 (0 target-flexibility) (0 robustness) hmr:Hipma_1167 (0 target-flexibility) (0 robustness) hmr:Hipma_1401 (0 target-flexibility) (0 robustness) hmr:Hipma_1516 (0 target-flexibility) (0 robustness) hmr:Hipma_1703 (0 target-flexibility) (0 robustness) hoh:Hoch_0379 (0 target-flexibility) (0 robustness) hoh:Hoch_0394 (138 target-flexibility) (66 robustness) hoh:Hoch_1849 (0 target-flexibility) (0 robustness) hoh:Hoch_2693 (0 target-flexibility) (0 robustness) hoh:Hoch_3186 (752 target-flexibility) (76 robustness) hoh:Hoch_3189 (212 target-flexibility) (73 robustness) hoh:Hoch_3975 (71 target-flexibility) (71 robustness) hoh:Hoch_4463 (796 target-flexibility) (85 robustness) hoh:Hoch_4475 (80 target-flexibility) (80 robustness) hoh:Hoch_5324 (897 target-flexibility) (71 robustness) hoh:Hoch_5556 (732 target-flexibility) (78 robustness) hoh:Hoch_5889 (222 target-flexibility) (83 robustness) hoh:Hoch_6383 (0 target-flexibility) (0 robustness) hoh:Hoch_6458 (0 target-flexibility) (0 robustness) hoh:Hoch_6609 (0 target-flexibility) (0 robustness) hoh:Hoch_6893 (0 target-flexibility) (0 robustness) lip:LI0152 (0 target-flexibility) (0 robustness) lip:LI0379 (0 target-flexibility) (0 robustness) lip:LI0466 (0 target-flexibility) (0 robustness) lip:LI0580 (0 target-flexibility) (0 robustness) lip:LI0648 (212 target-flexibility) (73 robustness) lip:LI1051 (222 target-flexibility) (83 robustness) lip:LI1066 (0 target-flexibility) (0 robustness) lip:LIC023 (0 target-flexibility) (0 robustness) llu:AKJ09_00381 (0 target-flexibility) (0 robustness) llu:AKJ09_00976 (0 target-flexibility) (0 robustness) llu:AKJ09_01495 (0 target-flexibility) (0 robustness) llu:AKJ09_02991 (0 target-flexibility) (0 robustness) llu:AKJ09_03567 (752 target-flexibility) (76 robustness) llu:AKJ09_04269 (796 target-flexibility) (85 robustness) llu:AKJ09_04272 (434 target-flexibility) (67 robustness) llu:AKJ09_04690 (239 target-flexibility) (67 robustness) llu:AKJ09_04691 (67 target-flexibility) (67 robustness) llu:AKJ09_04767 (71 target-flexibility) (71 robustness) llu:AKJ09_05314 (0 target-flexibility) (0 robustness) llu:AKJ09_05466 (0 target-flexibility) (0 robustness) llu:AKJ09_06149 (790 target-flexibility) (134 robustness) llu:AKJ09_07370 (790 target-flexibility) (134 robustness) llu:AKJ09_08130 (0 target-flexibility) (0 robustness) llu:AKJ09_08203 (0 target-flexibility) (0 robustness) llu:AKJ09_08534 (0 target-flexibility) (0 robustness) llu:AKJ09_08899 (222 target-flexibility) (83 robustness) llu:AKJ09_09399 (0 target-flexibility) (0 robustness) llu:AKJ09_10333 (732 target-flexibility) (78 robustness) llu:AKJ09_10397 (289 target-flexibility) (73 robustness) llu:AKJ09_10905 (212 target-flexibility) (73 robustness) mbd:MEBOL_000129 (0 target-flexibility) (0 robustness) mbd:MEBOL_000749 (790 target-flexibility) (134 robustness) mbd:MEBOL_002196 (222 target-flexibility) (83 robustness) mbd:MEBOL_003759 (0 target-flexibility) (0 robustness) mbd:MEBOL_003801 (222 target-flexibility) (83 robustness) mbd:MEBOL_003822 (80 target-flexibility) (80 robustness) mbd:MEBOL_004362 (790 target-flexibility) (134 robustness) mbd:MEBOL_004563 (732 target-flexibility) (78 robustness) mbd:MEBOL_004893 (796 target-flexibility) (85 robustness) mbd:MEBOL_005080 (0 target-flexibility) (0 robustness) mbd:MEBOL_005988 (0 target-flexibility) (0 robustness) mbd:MEBOL_006001 (71 target-flexibility) (71 robustness) mbd:MEBOL_006836 (0 target-flexibility) (0 robustness) mbd:MEBOL_006837 (0 target-flexibility) (0 robustness) mbd:MEBOL_006840 (897 target-flexibility) (71 robustness) mbd:MEBOL_007627 (0 target-flexibility) (0 robustness) mbd:MEBOL_007700 (138 target-flexibility) (66 robustness) mbd:MEBOL_007910 (212 target-flexibility) (73 robustness) mbd:MEBOL_007979 (0 target-flexibility) (0 robustness) mbd:MEBOL_008059 (0 target-flexibility) (0 robustness) mbd:MEBOL_008079 (752 target-flexibility) (76 robustness) mfu:LILAB_01860 (796 target-flexibility) (85 robustness) mfu:LILAB_03115 (732 target-flexibility) (78 robustness) mfu:LILAB_06720 (80 target-flexibility) (80 robustness) mfu:LILAB_06880 (222 target-flexibility) (83 robustness) mfu:LILAB_07065 (0 target-flexibility) (0 robustness) mfu:LILAB_15365 (222 target-flexibility) (83 robustness) mfu:LILAB_24705 (1385 target-flexibility) (204 robustness) mfu:LILAB_25505 (0 target-flexibility) (0 robustness) mfu:LILAB_25510 (0 target-flexibility) (0 robustness) mfu:LILAB_28080 (0 target-flexibility) (0 robustness) mfu:LILAB_28305 (0 target-flexibility) (0 robustness) mfu:LILAB_30430 (212 target-flexibility) (73 robustness) mfu:LILAB_31010 (0 target-flexibility) (0 robustness) mfu:LILAB_31365 (752 target-flexibility) (76 robustness) mfu:LILAB_31605 (71 target-flexibility) (71 robustness) mfu:LILAB_31675 (0 target-flexibility) (0 robustness) mfu:LILAB_35480 (70 target-flexibility) (70 robustness) mfu:LILAB_35505 (67 target-flexibility) (67 robustness) mmas:MYMAC_000346 (0 target-flexibility) (0 robustness) mmas:MYMAC_000385 (222 target-flexibility) (83 robustness) mmas:MYMAC_000432 (80 target-flexibility) (80 robustness) mmas:MYMAC_001135 (732 target-flexibility) (78 robustness) mmas:MYMAC_001379 (796 target-flexibility) (85 robustness) mmas:MYMAC_003338 (1385 target-flexibility) (204 robustness) mmas:MYMAC_003448 (0 target-flexibility) (0 robustness) mmas:MYMAC_003449 (0 target-flexibility) (0 robustness) mmas:MYMAC_003905 (0 target-flexibility) (0 robustness) mmas:MYMAC_003947 (0 target-flexibility) (0 robustness) mmas:MYMAC_004501 (0 target-flexibility) (0 robustness) mmas:MYMAC_004575 (752 target-flexibility) (76 robustness) mmas:MYMAC_004629 (71 target-flexibility) (71 robustness) mmas:MYMAC_004643 (0 target-flexibility) (0 robustness) mmas:MYMAC_005398 (70 target-flexibility) (70 robustness) mmas:MYMAC_005403 (67 target-flexibility) (67 robustness) mmas:MYMAC_005404 (239 target-flexibility) (67 robustness) mmas:MYMAC_005959 (222 target-flexibility) (83 robustness) mrm:A7982_02481 (0 target-flexibility) (0 robustness) mrm:A7982_02519 (790 target-flexibility) (134 robustness) mrm:A7982_02611 (222 target-flexibility) (83 robustness) mrm:A7982_02766 (0 target-flexibility) (0 robustness) mrm:A7982_05402 (0 target-flexibility) (0 robustness) mrm:A7982_06955 (289 target-flexibility) (73 robustness) mrm:A7982_07040 (212 target-flexibility) (73 robustness) mrm:A7982_07443 (0 target-flexibility) (0 robustness) mrm:A7982_08337 (790 target-flexibility) (134 robustness) mrm:A7982_09042 (0 target-flexibility) (0 robustness) mrm:A7982_09160 (0 target-flexibility) (0 robustness) mrm:A7982_09221 (434 target-flexibility) (67 robustness) mrm:A7982_09539 (790 target-flexibility) (134 robustness) mrm:A7982_09715 (80 target-flexibility) (80 robustness) mrm:A7982_10056 (0 target-flexibility) (0 robustness) mrm:A7982_10954 (0 target-flexibility) (0 robustness) msd:MYSTI_00373 (222 target-flexibility) (83 robustness) msd:MYSTI_00991 (790 target-flexibility) (134 robustness) msd:MYSTI_01146 (732 target-flexibility) (78 robustness) msd:MYSTI_01404 (796 target-flexibility) (85 robustness) msd:MYSTI_01655 (0 target-flexibility) (0 robustness) msd:MYSTI_01751 (0 target-flexibility) (0 robustness) msd:MYSTI_02961 (790 target-flexibility) (134 robustness) msd:MYSTI_03928 (0 target-flexibility) (0 robustness) msd:MYSTI_04466 (0 target-flexibility) (0 robustness) msd:MYSTI_04467 (0 target-flexibility) (0 robustness) msd:MYSTI_04815 (0 target-flexibility) (0 robustness) msd:MYSTI_04946 (212 target-flexibility) (73 robustness) msd:MYSTI_05067 (0 target-flexibility) (0 robustness) msd:MYSTI_05093 (1169 target-flexibility) (76 robustness) msd:MYSTI_05139 (752 target-flexibility) (76 robustness) msd:MYSTI_05188 (71 target-flexibility) (71 robustness) msd:MYSTI_05203 (0 target-flexibility) (0 robustness) msd:MYSTI_06468 (790 target-flexibility) (134 robustness) msd:MYSTI_06805 (222 target-flexibility) (83 robustness) msd:MYSTI_06833 (1041 target-flexibility) (243 robustness) mxa:MXAN_0318 (0 target-flexibility) (0 robustness) mxa:MXAN_0358 (222 target-flexibility) (83 robustness) mxa:MXAN_0395 (80 target-flexibility) (80 robustness) mxa:MXAN_0501 (796 target-flexibility) (85 robustness) mxa:MXAN_0949 (790 target-flexibility) (134 robustness) mxa:MXAN_1103 (732 target-flexibility) (78 robustness) mxa:MXAN_1283 (434 target-flexibility) (67 robustness) mxa:MXAN_1386 (796 target-flexibility) (85 robustness) mxa:MXAN_1528 (0 target-flexibility) (0 robustness) mxa:MXAN_3506 (0 target-flexibility) (0 robustness) mxa:MXAN_3507 (0 target-flexibility) (0 robustness) mxa:MXAN_3537 (289 target-flexibility) (73 robustness) mxa:MXAN_3987 (0 target-flexibility) (0 robustness) mxa:MXAN_4051 (0 target-flexibility) (0 robustness) mxa:MXAN_4460 (212 target-flexibility) (73 robustness) mxa:MXAN_4613 (0 target-flexibility) (0 robustness) mxa:MXAN_4684 (752 target-flexibility) (76 robustness) mxa:MXAN_4731 (71 target-flexibility) (71 robustness) mxa:MXAN_4745 (0 target-flexibility) (0 robustness) mxa:MXAN_5608 (67 target-flexibility) (67 robustness) mxa:MXAN_5609 (239 target-flexibility) (67 robustness) mxa:MXAN_6220 (222 target-flexibility) (83 robustness) mym:A176_000682 (222 target-flexibility) (83 robustness) mym:A176_001499 (0 target-flexibility) (0 robustness) mym:A176_002147 (0 target-flexibility) (0 robustness) mym:A176_002161 (71 target-flexibility) (71 robustness) mym:A176_002210 (752 target-flexibility) (76 robustness) mym:A176_002255 (1169 target-flexibility) (76 robustness) mym:A176_002284 (0 target-flexibility) (0 robustness) mym:A176_002437 (212 target-flexibility) (73 robustness) mym:A176_002926 (0 target-flexibility) (0 robustness) mym:A176_003407 (0 target-flexibility) (0 robustness) mym:A176_003408 (0 target-flexibility) (0 robustness) mym:A176_003863 (1041 target-flexibility) (243 robustness) mym:A176_005454 (0 target-flexibility) (0 robustness) mym:A176_005616 (796 target-flexibility) (85 robustness) mym:A176_005864 (732 target-flexibility) (78 robustness) mym:A176_006029 (790 target-flexibility) (134 robustness) mym:A176_006642 (222 target-flexibility) (83 robustness) mym:A176_007563 (0 target-flexibility) (0 robustness) pace:A6070_01880 (796 target-flexibility) (85 robustness) pace:A6070_02940 (222 target-flexibility) (83 robustness) pace:A6070_03240 (138 target-flexibility) (66 robustness) pace:A6070_03835 (212 target-flexibility) (73 robustness) pace:A6070_04260 (239 target-flexibility) (67 robustness) pace:A6070_04265 (67 target-flexibility) (67 robustness) pace:A6070_04975 (71 target-flexibility) (71 robustness) pace:A6070_05385 (732 target-flexibility) (78 robustness) pace:A6070_05790 (0 target-flexibility) (0 robustness) pace:A6070_06035 (0 target-flexibility) (0 robustness) pace:A6070_06075 (0 target-flexibility) (0 robustness) pace:A6070_06120 (0 target-flexibility) (0 robustness) pace:A6070_06815 (1169 target-flexibility) (76 robustness) pace:A6070_07185 (897 target-flexibility) (71 robustness) pace:A6070_10090 (752 target-flexibility) (76 robustness) pace:A6070_12850 (0 target-flexibility) (0 robustness) pace:A6070_13195 (0 target-flexibility) (0 robustness) pace:A6070_13200 (0 target-flexibility) (0 robustness) pace:A6070_13365 (1041 target-flexibility) (243 robustness) pace:A6070_14665 (80 target-flexibility) (80 robustness) pca:Pcar_0266 (80 target-flexibility) (80 robustness) pca:Pcar_1040 (752 target-flexibility) (76 robustness) pca:Pcar_1248 (71 target-flexibility) (71 robustness) pca:Pcar_1326 (732 target-flexibility) (78 robustness) pca:Pcar_1413 (0 target-flexibility) (0 robustness) pca:Pcar_1460 (0 target-flexibility) (0 robustness) pca:Pcar_1467 (0 target-flexibility) (0 robustness) pca:Pcar_1615 (897 target-flexibility) (71 robustness) pca:Pcar_1667 (1169 target-flexibility) (76 robustness) pca:Pcar_1804 (0 target-flexibility) (0 robustness) pca:Pcar_1805 (796 target-flexibility) (85 robustness) pca:Pcar_1807 (0 target-flexibility) (0 robustness) pca:Pcar_2206 (67 target-flexibility) (67 robustness) pca:Pcar_2207 (239 target-flexibility) (67 robustness) pca:Pcar_2315 (212 target-flexibility) (73 robustness) pca:Pcar_2415 (138 target-flexibility) (66 robustness) pca:Pcar_2455 (222 target-flexibility) (83 robustness) pca:Pcar_2593 (0 target-flexibility) (0 robustness) pca:Pcar_2684 (0 target-flexibility) (0 robustness) pca:Pcar_2685 (0 target-flexibility) (0 robustness) pca:Pcar_2719 (1041 target-flexibility) (243 robustness) pca:Pcar_2933 (796 target-flexibility) (85 robustness) pef:A7E78_00350 (0 target-flexibility) (0 robustness) pef:A7E78_01045 (0 target-flexibility) (0 robustness) pef:A7E78_01330 (71 target-flexibility) (71 robustness) pef:A7E78_01430 (0 target-flexibility) (0 robustness) pef:A7E78_02400 (0 target-flexibility) (0 robustness) pef:A7E78_02600 (732 target-flexibility) (78 robustness) pef:A7E78_02750 (1169 target-flexibility) (76 robustness) pef:A7E78_02985 (897 target-flexibility) (71 robustness) pef:A7E78_03875 (0 target-flexibility) (0 robustness) pef:A7E78_04875 (434 target-flexibility) (67 robustness) pef:A7E78_05895 (752 target-flexibility) (76 robustness) pef:A7E78_05905 (289 target-flexibility) (73 robustness) pef:A7E78_06630 (212 target-flexibility) (73 robustness) pef:A7E78_08220 (0 target-flexibility) (0 robustness) pef:A7E78_08225 (0 target-flexibility) (0 robustness) pef:A7E78_11150 (1041 target-flexibility) (243 robustness) pef:A7E78_11715 (796 target-flexibility) (85 robustness) pef:A7E78_13520 (222 target-flexibility) (83 robustness) pef:A7E78_13795 (138 target-flexibility) (66 robustness) ppd:Ppro_1177 (0 target-flexibility) (0 robustness) ppd:Ppro_1580 (212 target-flexibility) (73 robustness) ppd:Ppro_1725 (405 target-flexibility) (70 robustness) ppd:Ppro_1731 (0 target-flexibility) (0 robustness) ppd:Ppro_2098 (0 target-flexibility) (0 robustness) ppd:Ppro_2329 (752 target-flexibility) (76 robustness) ppd:Ppro_2529 (897 target-flexibility) (71 robustness) ppd:Ppro_2666 (80 target-flexibility) (80 robustness) ppd:Ppro_2973 (0 target-flexibility) (0 robustness) ppd:Ppro_3014 (71 target-flexibility) (71 robustness) ppd:Ppro_3055 (0 target-flexibility) (0 robustness) ppd:Ppro_3056 (0 target-flexibility) (0 robustness) ppd:Ppro_3172 (138 target-flexibility) (66 robustness) ppd:Ppro_3288 (70 target-flexibility) (70 robustness) ppd:Ppro_3293 (67 target-flexibility) (67 robustness) ppd:Ppro_3294 (239 target-flexibility) (67 robustness) ppd:Ppro_3406 (0 target-flexibility) (0 robustness) ppd:Ppro_3484 (357 target-flexibility) (102 robustness) ppd:Ppro_3596 (222 target-flexibility) (83 robustness) pprf:DPRO_0151 (434 target-flexibility) (67 robustness) pprf:DPRO_0163 (0 target-flexibility) (0 robustness) pprf:DPRO_0799 (528 target-flexibility) (157 robustness) pprf:DPRO_0802 (222 target-flexibility) (83 robustness) pprf:DPRO_1333 (0 target-flexibility) (0 robustness) pprf:DPRO_1336 (0 target-flexibility) (0 robustness) pprf:DPRO_1432 (0 target-flexibility) (0 robustness) pprf:DPRO_1502 (790 target-flexibility) (134 robustness) pprf:DPRO_1657 (80 target-flexibility) (80 robustness) pprf:DPRO_1802 (790 target-flexibility) (134 robustness) pprf:DPRO_1945 (0 target-flexibility) (0 robustness) pprf:DPRO_2174 (790 target-flexibility) (134 robustness) pprf:DPRO_2470 (212 target-flexibility) (73 robustness) pprf:DPRO_2602 (0 target-flexibility) (0 robustness) pprf:DPRO_2879 (289 target-flexibility) (73 robustness) pprf:DPRO_2976 (358 target-flexibility) (104 robustness) samy:DB32_001023 (752 target-flexibility) (76 robustness) samy:DB32_001708 (434 target-flexibility) (67 robustness) samy:DB32_002852 (0 target-flexibility) (0 robustness) samy:DB32_003553 (212 target-flexibility) (73 robustness) samy:DB32_003678 (289 target-flexibility) (73 robustness) samy:DB32_003711 (0 target-flexibility) (0 robustness) samy:DB32_003728 (222 target-flexibility) (83 robustness) samy:DB32_003841 (0 target-flexibility) (0 robustness) samy:DB32_003842 (0 target-flexibility) (0 robustness) samy:DB32_004135 (0 target-flexibility) (0 robustness) samy:DB32_004322 (0 target-flexibility) (0 robustness) samy:DB32_004445 (239 target-flexibility) (67 robustness) samy:DB32_004448 (140 target-flexibility) (71 robustness) samy:DB32_005205 (434 target-flexibility) (67 robustness) samy:DB32_005406 (71 target-flexibility) (71 robustness) samy:DB32_006581 (0 target-flexibility) (0 robustness) samy:DB32_007268 (790 target-flexibility) (134 robustness) sat:SYN_00075 (358 target-flexibility) (104 robustness) sat:SYN_00446 (528 target-flexibility) (157 robustness) sat:SYN_00583 (80 target-flexibility) (80 robustness) sat:SYN_00761 (0 target-flexibility) (0 robustness) sat:SYN_01112 (0 target-flexibility) (0 robustness) sat:SYN_01125 (0 target-flexibility) (0 robustness) sat:SYN_01130 (0 target-flexibility) (0 robustness) sat:SYN_01223 (790 target-flexibility) (134 robustness) sat:SYN_01253 (528 target-flexibility) (157 robustness) sat:SYN_01451 (0 target-flexibility) (0 robustness) sat:SYN_01454 (222 target-flexibility) (83 robustness) sat:SYN_01532 (897 target-flexibility) (71 robustness) sat:SYN_01740 (239 target-flexibility) (67 robustness) sat:SYN_01742 (67 target-flexibility) (67 robustness) sat:SYN_01747 (70 target-flexibility) (70 robustness) sat:SYN_02156 (138 target-flexibility) (66 robustness) sat:SYN_02374 (0 target-flexibility) (0 robustness) sat:SYN_02563 (0 target-flexibility) (0 robustness) sat:SYN_02635 (790 target-flexibility) (134 robustness) sat:SYN_02640 (0 target-flexibility) (0 robustness) sat:SYN_02643 (0 target-flexibility) (0 robustness) sat:SYN_02661 (0 target-flexibility) (0 robustness) sat:SYN_02866 (0 target-flexibility) (0 robustness) sat:SYN_02886 (212 target-flexibility) (73 robustness) sat:SYN_03128 (0 target-flexibility) (0 robustness) scl:sce0693 (0 target-flexibility) (0 robustness) scl:sce2813 (0 target-flexibility) (0 robustness) scl:sce4236 (222 target-flexibility) (83 robustness) scl:sce4320 (732 target-flexibility) (78 robustness) scl:sce5134 (212 target-flexibility) (73 robustness) scl:sce5886 (0 target-flexibility) (0 robustness) scl:sce7407 (796 target-flexibility) (85 robustness) scl:sce7417 (0 target-flexibility) (0 robustness) scl:sce7927 (790 target-flexibility) (134 robustness) scl:sce8012 (0 target-flexibility) (0 robustness) scl:sce9167 (80 target-flexibility) (80 robustness) sfu:Sfum_0007 (732 target-flexibility) (78 robustness) sfu:Sfum_0062 (138 target-flexibility) (66 robustness) sfu:Sfum_0108 (0 target-flexibility) (0 robustness) sfu:Sfum_0122 (222 target-flexibility) (83 robustness) sfu:Sfum_0179 (0 target-flexibility) (0 robustness) sfu:Sfum_0192 (212 target-flexibility) (73 robustness) sfu:Sfum_0478 (358 target-flexibility) (104 robustness) sfu:Sfum_0483 (0 target-flexibility) (0 robustness) sfu:Sfum_0745 (790 target-flexibility) (134 robustness) sfu:Sfum_1215 (0 target-flexibility) (0 robustness) sfu:Sfum_1302 (1041 target-flexibility) (243 robustness) sfu:Sfum_1418 (1169 target-flexibility) (76 robustness) sfu:Sfum_1608 (80 target-flexibility) (80 robustness) sfu:Sfum_2084 (0 target-flexibility) (0 robustness) sfu:Sfum_2090 (897 target-flexibility) (71 robustness) sfu:Sfum_2264 (0 target-flexibility) (0 robustness) sfu:Sfum_2580 (796 target-flexibility) (85 robustness) sfu:Sfum_2681 (528 target-flexibility) (157 robustness) sfu:Sfum_2989 (434 target-flexibility) (67 robustness) sfu:Sfum_3031 (434 target-flexibility) (67 robustness) sfu:Sfum_3365 (752 target-flexibility) (76 robustness) sfu:Sfum_3454 (790 target-flexibility) (134 robustness) sfu:Sfum_3692 (0 target-flexibility) (0 robustness) sfu:Sfum_3719 (0 target-flexibility) (0 robustness) sfu:Sfum_3742 (71 target-flexibility) (71 robustness) sfu:Sfum_3896 (289 target-flexibility) (73 robustness) sur:STAUR_0056 (1041 target-flexibility) (243 robustness) sur:STAUR_0531 (212 target-flexibility) (73 robustness) sur:STAUR_1671 (732 target-flexibility) (78 robustness) sur:STAUR_2146 (796 target-flexibility) (85 robustness) sur:STAUR_2302 (0 target-flexibility) (0 robustness) sur:STAUR_3279 (0 target-flexibility) (0 robustness) sur:STAUR_3296 (790 target-flexibility) (134 robustness) sur:STAUR_3549 (0 target-flexibility) (0 robustness) sur:STAUR_4027 (0 target-flexibility) (0 robustness) sur:STAUR_4028 (0 target-flexibility) (0 robustness) sur:STAUR_4050 (289 target-flexibility) (73 robustness) sur:STAUR_4815 (212 target-flexibility) (73 robustness) sur:STAUR_4874 (434 target-flexibility) (67 robustness) sur:STAUR_5425 (1169 target-flexibility) (76 robustness) sur:STAUR_5486 (752 target-flexibility) (76 robustness) sur:STAUR_5581 (71 target-flexibility) (71 robustness) sur:STAUR_5595 (0 target-flexibility) (0 robustness) sur:STAUR_5774 (222 target-flexibility) (83 robustness) sur:STAUR_6266 (67 target-flexibility) (67 robustness) sur:STAUR_6267 (239 target-flexibility) (67 robustness) sur:STAUR_7055 (790 target-flexibility) (134 robustness) sur:STAUR_8101 (80 target-flexibility) (80 robustness) sur:STAUR_8129 (222 target-flexibility) (83 robustness) sur:STAUR_8226 (0 target-flexibility) (0 robustness) vin:AKJ08_0051 (732 target-flexibility) (78 robustness) vin:AKJ08_0163 (138 target-flexibility) (66 robustness) vin:AKJ08_0731 (1041 target-flexibility) (243 robustness) vin:AKJ08_0977 (0 target-flexibility) (0 robustness) vin:AKJ08_1190 (222 target-flexibility) (83 robustness) vin:AKJ08_1262 (1169 target-flexibility) (76 robustness) vin:AKJ08_1405 (289 target-flexibility) (73 robustness) vin:AKJ08_1411 (897 target-flexibility) (71 robustness) vin:AKJ08_1417 (0 target-flexibility) (0 robustness) vin:AKJ08_1882 (434 target-flexibility) (67 robustness) vin:AKJ08_2065 (212 target-flexibility) (73 robustness) vin:AKJ08_2249 (70 target-flexibility) (70 robustness) vin:AKJ08_2252 (140 target-flexibility) (71 robustness) vin:AKJ08_2254 (67 target-flexibility) (67 robustness) vin:AKJ08_2255 (239 target-flexibility) (67 robustness) vin:AKJ08_2528 (796 target-flexibility) (85 robustness) vin:AKJ08_2627 (0 target-flexibility) (0 robustness) vin:AKJ08_3214 (222 target-flexibility) (83 robustness)

Target-flexibility contribution: 39.14994391125514% Robustness contribution: 15.106568615231211%

Conclusion

15% of robust enzymes have at least one neofunctionales enzyme on one of their alternative paths. 39% of target-flexible enzymes have at least one neofunctionales enzyme on one of their alternative paths. Due to the definition of flexible, this means that they have an edge leading away from at least one of their products, which belongs to a neofunctionalised enzyme.

This does not answer the question whether an enzyme would not be robust/flexible if the neofunctionalised enzymes did not exist!

FEV_KEGG.Experiments.47.getCladeA()[source]
FEV_KEGG.Experiments.48 module
Question

Which “neofunctionalised” EC numbers exist in Deltaproteobacteria? Does their existence increase redundancy? If yes, how much?

Method
  • get Deltaproteobacteria
  • get “neofunctionalised” ECs
  • calculate redundancy
  • REPEAT for each “neofunctionalised” EC
  • print number of ECs the “neofunctionalised” EC provides redundancy for (robustness and flexibility)
  • print ECs which have “neofunctionalised” ECs contributing to their robustness
Result
::

core metabolism majority: 80% neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)

Deltaproteobacteria:

core metabolism ECs: 228

“neofunctionalised” ECs: 36 (16%) 1.1.1.42 (0 target-flexibility) (0 robustness) 1.1.1.85 (0 target-flexibility) (0 robustness) 2.1.3.2 (0 target-flexibility) (0 robustness) 2.1.3.3 (1 target-flexibility) (0 robustness) 2.2.1.1 (6 target-flexibility) (2 robustness) 2.2.1.7 (7 target-flexibility) (2 robustness) 2.4.2.14 (2 target-flexibility) (0 robustness) 2.5.1.47 (0 target-flexibility) (0 robustness) 2.6.1.1 (2 target-flexibility) (0 robustness) 2.6.1.16 (2 target-flexibility) (0 robustness) 2.6.1.62 (0 target-flexibility) (0 robustness) 2.6.1.9 (0 target-flexibility) (0 robustness) 4.1.3.- (1 target-flexibility) (1 robustness) 4.2.1.46 (0 target-flexibility) (0 robustness) 5.1.1.1 (1 target-flexibility) (0 robustness) 5.1.3.2 (2 target-flexibility) (0 robustness) 5.1.3.6 (1 target-flexibility) (0 robustness) 5.3.1.16 (0 target-flexibility) (0 robustness) 5.4.3.8 (0 target-flexibility) (0 robustness) 5.4.99.18 (1 target-flexibility) (0 robustness) 6.1.1.12 (1 target-flexibility) (0 robustness) 6.1.1.16 (0 target-flexibility) (0 robustness) 6.1.1.17 (0 target-flexibility) (0 robustness) 6.1.1.18 (1 target-flexibility) (0 robustness) 6.1.1.22 (0 target-flexibility) (0 robustness) 6.1.1.4 (0 target-flexibility) (0 robustness) 6.1.1.5 (0 target-flexibility) (0 robustness) 6.1.1.6 (0 target-flexibility) (0 robustness) 6.1.1.9 (0 target-flexibility) (0 robustness) 6.2.1.1 (3 target-flexibility) (0 robustness) 6.2.1.3 (0 target-flexibility) (0 robustness) 6.3.2.10 (0 target-flexibility) (0 robustness) 6.3.2.13 (0 target-flexibility) (0 robustness) 6.3.2.8 (0 target-flexibility) (0 robustness) 6.3.2.9 (0 target-flexibility) (0 robustness) 6.3.4.13 (0 target-flexibility) (0 robustness)

Target-flexibility: 17.1% Target-flexibility contribution: 46.2%

Robustness: 7.0% Robustness contribution: 31.2%

Robust ECs contributed by “neofunctionalised” ECs: [1.2.1.12, 2.2.1.2, 2.4.2.-, 2.7.9.2, 5.1.3.1]

Conclusion

31.2% of the core metabolism’s robust EC numbers have at least one redundant path, making this EC number robust, which contains a “neofunctionalised” EC number. 7% of the core metabolism’s EC numbers are robust. This makes a total of 7% * 31.2% = 2.18% * 228 ECs in the core metabolism = 5 EC numbers in the core metabolism, which are robust with a “neofunctionalised” EC number on at least one of their alternative paths.

FEV_KEGG.Experiments.48.getCladeA()[source]
FEV_KEGG.Experiments.49 module
Question

Which neofunctionalised enzymes cause the core metabolism of Deltaproteobacteria to have increased redundancy? How much do they contribute?

Method
  • get clade
  • get core metabolism
  • calculate “neofunctionalised” ECs
  • calculate redundancy
  • REPEAT for each “neofunctionalised” EC contributing to redundancy
  • report enzyme pairs of neofunctionalisations, which caused the EC to be considered “neofunctionalised”, and are in return contributing to redundancy
Result
::

core metabolism majority: 80% neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)

Deltaproteobacteria:

core metabolism ECs: 228

“neofunctionalised” ECs: 36 (16%)

Neofunctionalisations contributing to robustness: 84 (afw:Anae109_3317 [2.2.1.1], afw:Anae109_1136 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (ccx:COCOR_06741 [2.2.1.1], ccx:COCOR_04847 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (daf:Desaf_0090 [2.2.1.1], daf:Desaf_2970 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (daf:Desaf_0304 [2.2.1.1], daf:Desaf_2970 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dal:Dalk_1064 [2.2.1.1], dal:Dalk_0836 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (das:Daes_0077 [2.2.1.1], das:Daes_0911 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (das:Daes_1972 [2.2.1.1], das:Daes_0911 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dav:DESACE_00060 [2.2.1.1], dav:DESACE_03180 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (des:DSOUD_0657 [2.2.1.1], des:DSOUD_2394 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (deu:DBW_3054 [2.2.1.1], deu:DBW_2425 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dfi:AXF13_13965 [2.2.1.1], dfi:AXF13_05800 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dgg:DGI_1348 [2.2.1.1], dgg:DGI_2795 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dhy:DESAM_21173 [2.2.1.1], dhy:DESAM_20160 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dol:Dole_1130 [2.2.1.1], dol:Dole_1662 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dsa:Desal_0558 [2.2.1.1], dsa:Desal_0740 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dsa:Desal_0574 [2.2.1.1], dsa:Desal_0740 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dsf:UWK_02797 [2.2.1.1], dsf:UWK_02514 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dti:Desti_0148 [2.2.1.1], dti:Desti_1492 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dvu:DVU2530 [2.2.1.1], dvu:DVU1350 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gao:A2G06_13760 [2.2.1.1], gao:A2G06_03585 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gao:A2G06_13760 [2.2.1.1], gao:A2G06_08130 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gbm:Gbem_0280 [2.2.1.1], gbm:Gbem_1258 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gbm:Gbem_0280 [2.2.1.1], gbm:Gbem_3362 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (geb:GM18_0317 [2.2.1.1], geb:GM18_1116 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (geb:GM18_0317 [2.2.1.1], geb:GM18_3441 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gem:GM21_0265 [2.2.1.1], gem:GM21_0883 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gem:GM21_0265 [2.2.1.1], gem:GM21_3025 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gem:GM21_3397 [2.2.1.1], gem:GM21_0883 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gem:GM21_3397 [2.2.1.1], gem:GM21_3025 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (geo:Geob_0666 [2.2.1.1], geo:Geob_2629 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (geo:Geob_0666 [2.2.1.1], geo:Geob_3664 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (geo:Geob_1002 [2.2.1.1], geo:Geob_3664 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (geo:Geob_1368 [2.2.1.1], geo:Geob_2629 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (geo:Geob_1368 [2.2.1.1], geo:Geob_3664 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (glo:Glov_0796 [2.2.1.1], glo:Glov_2182 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (glo:Glov_0796 [2.2.1.1], glo:Glov_2235 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gme:Gmet_0552 [2.2.1.1], gme:Gmet_1934 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gme:Gmet_0552 [2.2.1.1], gme:Gmet_2822 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gpi:GPICK_02900 [2.2.1.1], gpi:GPICK_04075 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gpi:GPICK_02900 [2.2.1.1], gpi:GPICK_07275 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gsb:GSUB_02815 [2.2.1.1], gsb:GSUB_06155 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gsu:GSU2918 [2.2.1.1], gsu:GSU0686 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gsu:GSU2918 [2.2.1.1], gsu:GSU1764 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gur:Gura_0492 [2.2.1.1], gur:Gura_1018 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (gur:Gura_0492 [2.2.1.1], gur:Gura_2175 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (hmr:Hipma_0012 [2.2.1.1], hmr:Hipma_0985 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (msd:MYSTI_06833 [2.2.1.1], msd:MYSTI_05093 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (mym:A176_003863 [2.2.1.1], mym:A176_002255 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (pace:A6070_13365 [2.2.1.1], pace:A6070_06815 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (pca:Pcar_2719 [2.2.1.1], pca:Pcar_1667 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (pef:A7E78_11150 [2.2.1.1], pef:A7E78_02750 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (sfu:Sfum_1302 [2.2.1.1], sfu:Sfum_1418 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (sur:STAUR_0056 [2.2.1.1], sur:STAUR_5425 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (vin:AKJ08_0731 [2.2.1.1], vin:AKJ08_1262 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1] (dao:Desac_2517 [4.1.3.-], dao:Desac_2262 [5.3.1.16]) => [2.4.2.-] (des:DSOUD_3191 [4.1.3.-], des:DSOUD_3192 [5.3.1.16]) => [2.4.2.-] (deu:DBW_3264 [4.1.3.-], deu:DBW_3265 [5.3.1.16]) => [2.4.2.-] (dml:Dmul_22810 [4.1.3.-], dml:Dmul_24040 [5.3.1.16]) => [2.4.2.-] (gao:A2G06_12745 [4.1.3.-], gao:A2G06_14565 [5.3.1.16]) => [2.4.2.-] (gao:A2G06_14560 [4.1.3.-], gao:A2G06_14565 [5.3.1.16]) => [2.4.2.-] (gbm:Gbem_3700 [4.1.3.-], gbm:Gbem_3701 [5.3.1.16]) => [2.4.2.-] (geb:GM18_4149 [4.1.3.-], geb:GM18_4150 [5.3.1.16]) => [2.4.2.-] (gem:GM21_3795 [4.1.3.-], gem:GM21_3796 [5.3.1.16]) => [2.4.2.-] (geo:Geob_0693 [4.1.3.-], geo:Geob_0692 [5.3.1.16]) => [2.4.2.-] (glo:Glov_1018 [4.1.3.-], glo:Glov_1019 [5.3.1.16]) => [2.4.2.-] (gme:Gmet_0389 [4.1.3.-], gme:Gmet_0388 [5.3.1.16]) => [2.4.2.-] (gpi:GPICK_02240 [4.1.3.-], gpi:GPICK_02235 [5.3.1.16]) => [2.4.2.-] (gsb:GSUB_02545 [4.1.3.-], gsb:GSUB_02540 [5.3.1.16]) => [2.4.2.-] (gsb:GSUB_08845 [4.1.3.-], gsb:GSUB_02540 [5.3.1.16]) => [2.4.2.-] (gsu:GSU3095 [4.1.3.-], gsu:GSU3096 [5.3.1.16]) => [2.4.2.-] (gur:Gura_4053 [4.1.3.-], gur:Gura_4054 [5.3.1.16]) => [2.4.2.-] (hmr:Hipma_0215 [4.1.3.-], hmr:Hipma_1516 [5.3.1.16]) => [2.4.2.-] (hoh:Hoch_6609 [4.1.3.-], hoh:Hoch_0379 [5.3.1.16]) => [2.4.2.-] (llu:AKJ09_08130 [4.1.3.-], llu:AKJ09_08203 [5.3.1.16]) => [2.4.2.-] (pace:A6070_12850 [4.1.3.-], pace:A6070_13200 [5.3.1.16]) => [2.4.2.-] (pace:A6070_13195 [4.1.3.-], pace:A6070_13200 [5.3.1.16]) => [2.4.2.-] (pca:Pcar_2684 [4.1.3.-], pca:Pcar_2685 [5.3.1.16]) => [2.4.2.-] (pef:A7E78_08220 [4.1.3.-], pef:A7E78_08225 [5.3.1.16]) => [2.4.2.-] (ppd:Ppro_3055 [4.1.3.-], ppd:Ppro_3056 [5.3.1.16]) => [2.4.2.-] (samy:DB32_003842 [4.1.3.-], samy:DB32_003841 [5.3.1.16]) => [2.4.2.-] (sat:SYN_01451 [4.1.3.-], sat:SYN_00761 [5.3.1.16]) => [2.4.2.-] (scl:sce5886 [4.1.3.-], scl:sce2813 [5.3.1.16]) => [2.4.2.-] (sfu:Sfum_0483 [4.1.3.-], sfu:Sfum_1215 [5.3.1.16]) => [2.4.2.-] (sfu:Sfum_3692 [4.1.3.-], sfu:Sfum_1215 [5.3.1.16]) => [2.4.2.-]

Neofunctionalisations contributing to target-flexibility: 637 (dbr:Deba_2503, dbr:Deba_2748) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gpi:GPICK_07650, gpi:GPICK_10380) => {1.1.1.22, 2.7.7.9} (dps:DP0045, dps:DP2716) => {1.1.1.22} (geb:GM18_4171, geb:GM18_0750) => {1.1.1.22, 2.7.7.9} (dti:Desti_2341, dti:Desti_2003) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dhy:DESAM_22470, dhy:DESAM_20338) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (glo:Glov_3365, glo:Glov_0479) => {1.1.1.22, 2.7.7.9} (gao:A2G06_13760, gao:A2G06_03585) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (mxa:MXAN_4684, mxa:MXAN_4731) => {2.1.3.2} (dbr:Deba_2140, dbr:Deba_2773) => {1.1.1.22, 2.7.7.9} (dti:Desti_0219, dti:Desti_1457) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dpi:BN4_12584, dpi:BN4_12643) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (deu:DBW_3264, deu:DBW_3265) => {2.4.2.-} (pca:Pcar_1804, pca:Pcar_1467) => {1.1.1.22, 2.7.7.9} (dma:DMR_28600, dma:DMR_00110) => {1.1.1.22} (gur:Gura_4053, gur:Gura_4054) => {2.4.2.-} (gem:GM21_0265, gem:GM21_0883) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (gpi:GPICK_02900, gpi:GPICK_07275) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dal:Dalk_1693, dal:Dalk_1699) => {1.1.1.22, 2.7.7.9} (mbd:MEBOL_004563, mbd:MEBOL_004893) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (pca:Pcar_1807, pca:Pcar_1467) => {1.1.1.22, 2.7.7.9} (dbr:Deba_3187, dbr:Deba_0581) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (cfus:CYFUS_002855, cfus:CYFUS_004967) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dto:TOL2_C21920, dto:TOL2_C24560) => {2.1.3.2} (gur:Gura_0492, gur:Gura_2175) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dps:DPPB37, dps:DP0555) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dhy:DESAM_20564, dhy:DESAM_20933) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (doa:AXF15_02215, doa:AXF15_03465) => {1.1.1.22} (sur:STAUR_7055, sur:STAUR_3279) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dml:Dmul_21830, dml:Dmul_24630) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (glo:Glov_2085, glo:Glov_3149) => {2.1.3.2} (dps:DP0106, dps:DP0437) => {2.1.3.2} (age:AA314_04350, age:AA314_05003) => {1.1.1.22, 2.7.7.9} (mmas:MYMAC_004501, mmas:MYMAC_003449) => {1.1.1.22, 2.7.7.9} (cfus:CYFUS_002855, cfus:CYFUS_002381) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (llu:AKJ09_07370, llu:AKJ09_00976) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sat:SYN_02661, sat:SYN_01112) => {1.1.1.22, 2.7.7.9} (dgg:DGI_0581, dgg:DGI_2476) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pace:A6070_07185, pace:A6070_03240) => {2.1.3.2} (ccro:CMC5_012520, ccro:CMC5_049960) => {1.1.1.22, 2.7.7.9} (dal:Dalk_2329, dal:Dalk_4640) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dpi:BN4_11977, dpi:BN4_10196) => {2.1.3.2} (mym:A176_002210, mym:A176_002161) => {2.1.3.2} (mxa:MXAN_3506, mxa:MXAN_3987) => {1.1.1.22} (pca:Pcar_2684, pca:Pcar_2685) => {2.4.2.-} (dpr:Despr_1050, dpr:Despr_3168) => {2.1.3.2, 2.3.3.1} (dto:TOL2_C05220, dto:TOL2_C27090) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sat:SYN_01130, sat:SYN_01125) => {1.1.1.22, 2.7.7.9} (scl:sce7927, scl:sce8012) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pca:Pcar_2719, pca:Pcar_1667) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dbr:Deba_2288, dbr:Deba_2140) => {1.1.1.22, 2.7.7.9} (geb:GM18_1720, geb:GM18_4095) => {2.1.3.2} (ank:AnaeK_1925, ank:AnaeK_0232) => {1.1.1.22, 2.7.7.9} (das:Daes_0665, das:Daes_2972) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dgg:DGI_1737, dgg:DGI_2476) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dde:Dde_3691, dde:Dde_0033) => {1.1.1.22, 2.7.7.9} (dal:Dalk_0475, dal:Dalk_1693) => {1.1.1.22, 2.7.7.9} (sfu:Sfum_0007, sfu:Sfum_2580) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (ank:AnaeK_4338, ank:AnaeK_4069) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (msd:MYSTI_02961, msd:MYSTI_04815) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mbd:MEBOL_006837, mbd:MEBOL_007627) => {1.1.1.22, 2.7.7.9} (geo:Geob_3264, geo:Geob_1123) => {2.1.3.2} (pace:A6070_10090, pace:A6070_04975) => {2.1.3.2} (sat:SYN_01223, sat:SYN_02643) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (geb:GM18_0958, geb:GM18_1602) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2345, dti:Desti_2797) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dal:Dalk_2756, dal:Dalk_1784) => {2.1.3.2} (dti:Desti_2348, dti:Desti_3164) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (llu:AKJ09_08130, llu:AKJ09_08203) => {2.4.2.-} (dti:Desti_0219, dti:Desti_1808) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dao:Desac_0009, dao:Desac_2478) => {2.1.3.2} (gur:Gura_0492, gur:Gura_1018) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dhy:DESAM_20710, dhy:DESAM_22412) => {2.1.3.2} (dpr:Despr_0555, dpr:Despr_2467) => {1.1.1.22} (gme:Gmet_2340, gme:Gmet_2229) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dsa:Desal_0092, dsa:Desal_0743) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dfi:AXF13_13965, dfi:AXF13_05800) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dsf:UWK_00793, dsf:UWK_00683) => {2.1.3.2} (das:Daes_0687, das:Daes_2857) => {2.1.3.2, 2.3.3.1} (dpr:Despr_2776, dpr:Despr_0918) => {2.1.3.2} (gme:Gmet_2473, gme:Gmet_2330) => {1.1.1.22} (sur:STAUR_7055, sur:STAUR_2302) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ank:AnaeK_2705, ank:AnaeK_1224) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gem:GM21_3397, gem:GM21_3025) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (gpi:GPICK_10370, gpi:GPICK_10380) => {1.1.1.22, 2.7.7.9} (dpi:BN4_12384, dpi:BN4_12643) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dbr:Deba_2503, dbr:Deba_1780) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dvu:DVU2969, dvu:DVU3119) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dto:TOL2_C35290, dto:TOL2_C12360) => {1.1.1.22, 2.7.7.9} (sfu:Sfum_2264, sfu:Sfum_0179) => {1.1.1.22} (mxa:MXAN_1103, mxa:MXAN_1386) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (msd:MYSTI_02961, msd:MYSTI_01751) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pef:A7E78_00350, pef:A7E78_03875) => {1.1.1.22} (cfus:CYFUS_001210, cfus:CYFUS_002381) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ccx:COCOR_04815, ccx:COCOR_04535) => {1.1.1.22, 2.7.7.9} (dsa:Desal_0558, dsa:Desal_0740) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (drt:Dret_1409, drt:Dret_1384) => {2.6.1.16} (cfus:CYFUS_006116, cfus:CYFUS_003523) => {2.1.3.2} (cfus:CYFUS_006014, cfus:CYFUS_005495) => {1.1.1.22} (scl:sce5886, scl:sce2813) => {2.4.2.-} (samy:DB32_004322, samy:DB32_006581) => {1.1.1.22, 2.7.7.9} (dej:AWY79_00595, dej:AWY79_17820) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dao:Desac_2544, dao:Desac_2541) => {1.1.1.22, 2.7.7.9} (dbr:Deba_0585, dbr:Deba_0581) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_0219, dti:Desti_2003) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2345, dti:Desti_0901) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mmas:MYMAC_003448, mmas:MYMAC_003449) => {1.1.1.22, 2.7.7.9} (gsu:GSU3095, gsu:GSU3096) => {2.4.2.-} (llu:AKJ09_00381, llu:AKJ09_09399) => {1.1.1.22, 2.7.7.9} (lip:LI1066, lip:LI0466) => {1.1.1.22, 2.7.7.9} (llu:AKJ09_05314, llu:AKJ09_09399) => {1.1.1.22, 2.7.7.9} (gbm:Gbem_0280, gbm:Gbem_1258) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dsf:UWK_03057, dsf:UWK_03000) => {6.3.2.6} (dpg:DESPIGER_1297, dpg:DESPIGER_0283) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2341, dti:Desti_4907) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (hmr:Hipma_0431, hmr:Hipma_0341) => {2.1.3.2} (dgg:DGI_1348, dgg:DGI_2795) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (mym:A176_003408, mym:A176_003407) => {1.1.1.22, 2.7.7.9} (dde:Dde_2182, dde:Dde_0033) => {1.1.1.22} (mym:A176_002284, mym:A176_003407) => {1.1.1.22, 2.7.7.9} (dbr:Deba_2288, dbr:Deba_2773) => {1.1.1.22} (geo:Geob_2661, geo:Geob_2094) => {2.1.3.2} (msd:MYSTI_05139, msd:MYSTI_05188) => {2.1.3.2} (gem:GM21_3795, gem:GM21_3796) => {2.4.2.-} (afw:Anae109_1901, afw:Anae109_4196) => {1.1.1.22, 2.7.7.9} (das:Daes_1318, das:Daes_3345) => {1.1.1.22} (dat:HRM2_11950, dat:HRM2_47820) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2345, dti:Desti_0353) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dvu:DVU1360, dvu:DVU3356) => {1.1.1.22, 2.7.7.9} (dde:Dde_2182, dde:Dde_3691) => {1.1.1.22, 2.7.7.9} (dgg:DGI_4014, dgg:DGI_0864) => {1.1.1.22, 2.7.7.9} (mfu:LILAB_31010, mfu:LILAB_28080) => {1.1.1.22} (vin:AKJ08_0051, vin:AKJ08_2528) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (pca:Pcar_1615, pca:Pcar_2415) => {2.1.3.2} (gbm:Gbem_3700, gbm:Gbem_3701) => {2.4.2.-} (dgg:DGI_0026, dgg:DGI_0864) => {1.1.1.22, 2.7.7.9} (afw:Anae109_3170, afw:Anae109_1212) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mrm:A7982_09160, mrm:A7982_02481) => {1.1.1.22, 2.7.7.9} (dhy:DESAM_21837, dhy:DESAM_20726) => {1.1.1.22, 2.7.7.9} (pprf:DPRO_2174, pprf:DPRO_1432) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dol:Dole_1010, dol:Dole_2324) => {1.1.1.22} (gbm:Gbem_2903, gbm:Gbem_0836) => {2.1.3.2} (pace:A6070_13365, pace:A6070_06815) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (ank:AnaeK_4425, ank:AnaeK_1925) => {1.1.1.22, 2.7.7.9} (mxa:MXAN_1103, mxa:MXAN_0501) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (lip:LI0466, lip:LI0580) => {1.1.1.22, 2.7.7.9} (age:AA314_05002, age:AA314_05840) => {1.1.1.22} (ppd:Ppro_2098, ppd:Ppro_2973) => {1.1.1.22, 2.7.7.9} (dto:TOL2_C05220, dto:TOL2_C37120) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (afw:Anae109_4443, afw:Anae109_1901) => {1.1.1.22, 2.7.7.9} (mbd:MEBOL_004362, mbd:MEBOL_008059) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2345, dti:Desti_1457) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sur:STAUR_3549, sur:STAUR_4028) => {1.1.1.22, 2.7.7.9} (des:DSOUD_1879, des:DSOUD_0923) => {2.1.3.2} (drt:Dret_0014, drt:Dret_2234) => {2.1.3.2} (ade:Adeh_4288, ade:Adeh_1954) => {1.1.1.22, 2.7.7.9} (deu:DBW_3054, deu:DBW_2425) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dpg:DESPIGER_0323, dpg:DESPIGER_1250) => {1.1.1.22, 2.7.7.9} (dti:Desti_4164, dti:Desti_1808) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gsu:GSU2918, gsu:GSU1764) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dti:Desti_4164, dti:Desti_4907) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (das:Daes_0235, das:Daes_1396) => {2.1.3.2} (pace:A6070_13195, pace:A6070_13200) => {2.4.2.-} (ade:Adeh_1955, ade:Adeh_0221) => {1.1.1.22} (dol:Dole_1130, dol:Dole_1662) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (geb:GM18_3424, geb:GM18_4171) => {1.1.1.22, 2.7.7.9} (dao:Desac_2541, dao:Desac_0239) => {1.1.1.22, 2.7.7.9} (dat:HRM2_47210, dat:HRM2_47820) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dhy:DESAM_20574, dhy:DESAM_10054) => {2.1.3.2} (dml:Dmul_07490, dml:Dmul_09580) => {1.1.1.22} (sat:SYN_01451, sat:SYN_00761) => {2.4.2.-} (mrm:A7982_09160, mrm:A7982_05402) => {1.1.1.22, 2.7.7.9} (ppd:Ppro_2329, ppd:Ppro_3014) => {2.1.3.2} (llu:AKJ09_07370, llu:AKJ09_05466) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dto:TOL2_C05220, dto:TOL2_C27260) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gur:Gura_1685, gur:Gura_2598) => {1.1.1.22, 2.7.7.9} (msd:MYSTI_00991, msd:MYSTI_04815) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (msd:MYSTI_00991, msd:MYSTI_01655) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (samy:DB32_004322, samy:DB32_004135) => {1.1.1.22} (gme:Gmet_0389, gme:Gmet_0388) => {2.4.2.-} (gpi:GPICK_11740, gpi:GPICK_10370) => {1.1.1.22, 2.7.7.9} (glo:Glov_1658, glo:Glov_3365) => {1.1.1.22, 2.7.7.9} (ccx:COCOR_04536, ccx:COCOR_04535) => {1.1.1.22, 2.7.7.9} (lip:LI0379, lip:LI0580) => {1.1.1.22, 2.7.7.9} (dti:Desti_2740, dti:Desti_2739) => {1.1.1.22, 2.7.7.9} (dav:DESACE_00060, dav:DESACE_03180) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (doa:AXF15_00335, doa:AXF15_04820) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (llu:AKJ09_01495, llu:AKJ09_05314) => {1.1.1.22, 2.7.7.9} (sfu:Sfum_2090, sfu:Sfum_0062) => {2.1.3.2} (des:DSOUD_0657, des:DSOUD_2394) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (mrm:A7982_08337, mrm:A7982_02766) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sfu:Sfum_0745, sfu:Sfum_0108) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dml:Dmul_24260, dml:Dmul_09580) => {1.1.1.22, 2.7.7.9} (dml:Dmul_23280, dml:Dmul_09580) => {1.1.1.22, 2.7.7.9} (dto:TOL2_C05220, dto:TOL2_C27460) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ccx:COCOR_04536, ccx:COCOR_03939) => {1.1.1.22} (msd:MYSTI_04467, msd:MYSTI_04466) => {1.1.1.22, 2.7.7.9} (dml:Dmul_07490, dml:Dmul_23280) => {1.1.1.22, 2.7.7.9} (hoh:Hoch_6383, hoh:Hoch_2693) => {1.1.1.22, 2.7.7.9} (dbr:Deba_0585, dbr:Deba_1780) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mfu:LILAB_31010, mfu:LILAB_25510) => {1.1.1.22, 2.7.7.9} (mrm:A7982_09539, mrm:A7982_07443) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sat:SYN_01130, sat:SYN_01112) => {1.1.1.22} (gsu:GSU2366, gsu:GSU2241) => {1.1.1.22} (mbd:MEBOL_000749, mbd:MEBOL_005080) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (das:Daes_1972, das:Daes_0911) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dal:Dalk_2329, dal:Dalk_0853) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dsa:Desal_2170, dsa:Desal_3566) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (glo:Glov_1658, glo:Glov_0479) => {1.1.1.22} (dbr:Deba_0146, dbr:Deba_2773) => {1.1.1.22, 2.7.7.9} (mbd:MEBOL_006840, mbd:MEBOL_007700) => {2.1.3.2} (afw:Anae109_1900, afw:Anae109_1901) => {1.1.1.22, 2.7.7.9} (glo:Glov_1018, glo:Glov_1019) => {2.4.2.-} (dbr:Deba_2654, dbr:Deba_1882) => {2.1.3.2} (dti:Desti_0219, dti:Desti_0901) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pca:Pcar_1326, pca:Pcar_1805) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (mbd:MEBOL_007979, mbd:MEBOL_007627) => {1.1.1.22} (dsa:Desal_1645, dsa:Desal_3834) => {1.1.1.22} (dat:HRM2_11950, dat:HRM2_47830) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dvu:DVU0748, dvu:DVU1453) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (cfus:CYFUS_006014, cfus:CYFUS_001311) => {1.1.1.22, 2.7.7.9} (cfus:CYFUS_001311, cfus:CYFUS_005495) => {1.1.1.22, 2.7.7.9} (dak:DaAHT2_1636, dak:DaAHT2_2371) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (geo:Geob_1002, geo:Geob_3664) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dbr:Deba_0419, dbr:Deba_2773) => {1.1.1.22, 2.7.7.9} (dvu:DVU1364, dvu:DVU3356) => {1.1.1.22} (age:AA314_05003, age:AA314_05840) => {1.1.1.22, 2.7.7.9} (dgg:DGI_1737, dgg:DGI_3014) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ccx:COCOR_06741, ccx:COCOR_04847) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (mrm:A7982_02519, mrm:A7982_07443) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (glo:Glov_0584, glo:Glov_2128) => {2.6.1.16} (ccx:COCOR_01049, ccx:COCOR_01272) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (hoh:Hoch_6609, hoh:Hoch_0379) => {2.4.2.-} (age:AA314_01912, age:AA314_03054) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dde:Dde_3207, dde:Dde_1725) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mym:A176_002284, mym:A176_002926) => {1.1.1.22} (hoh:Hoch_5556, hoh:Hoch_4463) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (hmr:Hipma_0012, hmr:Hipma_0985) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (hoh:Hoch_3186, hoh:Hoch_3975) => {2.1.3.2} (pprf:DPRO_0163, pprf:DPRO_1945) => {1.1.1.22} (mmas:MYMAC_003448, mmas:MYMAC_003905) => {1.1.1.22} (dps:DP2220, dps:DP2716) => {1.1.1.22} (dti:Desti_2348, dti:Desti_2797) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dgg:DGI_1438, dgg:DGI_3014) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dej:AWY79_10850, dej:AWY79_02820) => {1.1.1.22} (deu:DBW_1746, deu:DBW_0616) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (msd:MYSTI_01146, msd:MYSTI_01404) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dvu:DVU1364, dvu:DVU1360) => {1.1.1.22, 2.7.7.9} (afw:Anae109_3317, afw:Anae109_1136) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (gme:Gmet_2473, gme:Gmet_2329) => {1.1.1.22, 2.7.7.9} (gem:GM21_1322, gem:GM21_3424) => {2.1.3.2} (hoh:Hoch_6383, hoh:Hoch_1849) => {1.1.1.22, 2.7.7.9} (daf:Desaf_0304, daf:Desaf_2970) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (geo:Geob_1870, geo:Geob_2923) => {1.1.1.22} (dml:Dmul_23620, dml:Dmul_08540) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mfu:LILAB_25505, mfu:LILAB_28080) => {1.1.1.22} (pace:A6070_06120, pace:A6070_06075) => {1.1.1.22, 2.7.7.9} (dti:Desti_4164, dti:Desti_2003) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_1700, dti:Desti_4705) => {1.4.1.1} (gsb:GSUB_02815, gsb:GSUB_06155) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (gme:Gmet_1769, gme:Gmet_0205) => {2.1.3.2} (daf:Desaf_1013, daf:Desaf_2305) => {1.1.1.22, 2.7.7.9} (ccx:COCOR_00905, ccx:COCOR_01538) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ppd:Ppro_2098, ppd:Ppro_3406) => {1.1.1.22} (geb:GM18_3424, geb:GM18_3257) => {1.1.1.22, 2.7.7.9} (dti:Desti_2348, dti:Desti_4907) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sfu:Sfum_3365, sfu:Sfum_3742) => {2.1.3.2} (dti:Desti_2348, dti:Desti_0901) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dsa:Desal_0143, dsa:Desal_2527) => {2.1.3.2} (dti:Desti_0219, dti:Desti_4337) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sat:SYN_02635, sat:SYN_02640) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (cfus:CYFUS_001210, cfus:CYFUS_007908) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2348, dti:Desti_1808) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (scl:sce4320, scl:sce7407) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dal:Dalk_2329, dal:Dalk_1587) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ade:Adeh_2619, ade:Adeh_1165) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pca:Pcar_2593, pca:Pcar_1467) => {1.1.1.22} (gao:A2G06_13760, gao:A2G06_08130) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dpi:BN4_10127, dpi:BN4_12214) => {1.1.1.22} (dti:Desti_1700, dti:Desti_4704) => {1.4.1.1} (dml:Dmul_21830, dml:Dmul_08540) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (geo:Geob_0666, geo:Geob_3664) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (geo:Geob_1368, geo:Geob_3664) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dti:Desti_1259, dti:Desti_3121) => {2.1.3.2} (llu:AKJ09_03567, llu:AKJ09_04767) => {2.1.3.2} (dti:Desti_2348, dti:Desti_0353) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (das:Daes_0202, das:Daes_2972) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mrm:A7982_02519, mrm:A7982_02766) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dba:Dbac_3212, dba:Dbac_2833) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (gur:Gura_3273, gur:Gura_1685) => {1.1.1.22, 2.7.7.9} (daf:Desaf_2132, daf:Desaf_2305) => {1.1.1.22, 2.7.7.9} (dhy:DESAM_22057, dhy:DESAM_20726) => {1.1.1.22} (drt:Dret_2481, drt:Dret_1756) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dbr:Deba_2288, dbr:Deba_0419) => {1.1.1.22, 2.7.7.9} (mxa:MXAN_4613, mxa:MXAN_3507) => {1.1.1.22, 2.7.7.9} (llu:AKJ09_01495, llu:AKJ09_09399) => {1.1.1.22} (ade:Adeh_4288, ade:Adeh_0221) => {1.1.1.22} (dsf:UWK_03421, dsf:UWK_02513) => {1.1.1.22} (mbd:MEBOL_007979, mbd:MEBOL_006837) => {1.1.1.22, 2.7.7.9} (msd:MYSTI_00991, msd:MYSTI_01751) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (llu:AKJ09_10333, llu:AKJ09_04269) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dba:Dbac_0109, dba:Dbac_1611) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (glo:Glov_0796, glo:Glov_2235) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dol:Dole_0514, dol:Dole_2492) => {2.1.3.2} (dti:Desti_0148, dti:Desti_1492) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dak:DaAHT2_1831, dak:DaAHT2_1792) => {1.1.1.22} (daf:Desaf_0322, daf:Desaf_2909) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (des:DSOUD_3191, des:DSOUD_3192) => {2.4.2.-} (cfus:CYFUS_006014, cfus:CYFUS_004500) => {1.1.1.22, 2.7.7.9} (gem:GM21_0899, gem:GM21_3403) => {1.1.1.22} (dti:Desti_0219, dti:Desti_4907) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (daf:Desaf_1013, daf:Desaf_2415) => {1.1.1.22} (dti:Desti_2345, dti:Desti_1808) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (afw:Anae109_2586, afw:Anae109_1212) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dbr:Deba_3187, dbr:Deba_2748) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dgg:DGI_0069, dgg:DGI_0864) => {1.1.1.22} (dti:Desti_0219, dti:Desti_2797) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pprf:DPRO_1802, pprf:DPRO_1432) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_0473, dti:Desti_2739) => {1.1.1.22} (dol:Dole_1973, dol:Dole_0337) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dpr:Despr_3156, dpr:Despr_0517) => {2.1.3.2} (cfus:CYFUS_001210, cfus:CYFUS_002221) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (geo:Geob_0284, geo:Geob_2923) => {1.1.1.22, 2.7.7.9} (das:Daes_0077, das:Daes_0911) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (sur:STAUR_3296, sur:STAUR_3279) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (doa:AXF15_09390, doa:AXF15_11375) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dat:HRM2_23040, dat:HRM2_29750) => {1.1.1.22} (glo:Glov_1622, glo:Glov_0757) => {2.1.3.2} (dat:HRM2_47210, dat:HRM2_13680) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dpg:DESPIGER_1250, dpg:DESPIGER_1949) => {1.1.1.22, 2.7.7.9} (geb:GM18_0317, geb:GM18_1116) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dbr:Deba_0585, dbr:Deba_2748) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mfu:LILAB_25505, mfu:LILAB_25510) => {1.1.1.22, 2.7.7.9} (pprf:DPRO_1333, pprf:DPRO_1945) => {1.1.1.22, 2.7.7.9} (dbr:Deba_2288, dbr:Deba_0146) => {1.1.1.22, 2.7.7.9} (hmr:Hipma_0501, hmr:Hipma_0121) => {2.1.3.2} (mym:A176_003407, mym:A176_002926) => {1.1.1.22, 2.7.7.9} (dml:Dmul_23620, dml:Dmul_36880) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gem:GM21_3397, gem:GM21_0883) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dto:TOL2_C35290, dto:TOL2_C08210) => {1.1.1.22, 2.7.7.9} (msd:MYSTI_02961, msd:MYSTI_01655) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dal:Dalk_1064, dal:Dalk_0836) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dat:HRM2_08850, dat:HRM2_47820) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_4164, dti:Desti_0353) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (daf:Desaf_0111, daf:Desaf_1564) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (daf:Desaf_2132, daf:Desaf_2415) => {1.1.1.22} (gao:A2G06_05670, gao:A2G06_06115) => {1.1.1.22} (dti:Desti_0219, dti:Desti_2479) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ank:AnaeK_1924, ank:AnaeK_1925) => {1.1.1.22, 2.7.7.9} (gsb:GSUB_09375, gsb:GSUB_02190) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (sat:SYN_01223, sat:SYN_02640) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gsu:GSU2918, gsu:GSU0686) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (ade:Adeh_4206, ade:Adeh_3959) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dhy:DESAM_21612, dhy:DESAM_20933) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dak:DaAHT2_1794, dak:DaAHT2_1792) => {1.1.1.22, 2.7.7.9} (sat:SYN_02866, sat:SYN_02661) => {1.1.1.22, 2.7.7.9} (des:DSOUD_1686, des:DSOUD_2288) => {1.1.1.22} (ank:AnaeK_1316, ank:AnaeK_1137) => {2.1.3.2} (mxa:MXAN_3506, mxa:MXAN_3507) => {1.1.1.22, 2.7.7.9} (daf:Desaf_0090, daf:Desaf_2970) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (sur:STAUR_5486, sur:STAUR_5581) => {2.1.3.2} (dvu:DVU2969, dvu:DVU1453) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dvu:DVU2530, dvu:DVU1350) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dti:Desti_2341, dti:Desti_3164) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (doa:AXF15_03265, doa:AXF15_11375) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_4164, dti:Desti_0901) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dpg:DESPIGER_0323, dpg:DESPIGER_1949) => {1.1.1.22} (mfu:LILAB_25510, mfu:LILAB_28080) => {1.1.1.22, 2.7.7.9} (dde:Dde_2823, dde:Dde_1725) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ade:Adeh_1618, ade:Adeh_2691) => {2.1.3.2} (dsa:Desal_2829, dsa:Desal_0743) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mym:A176_003408, mym:A176_002926) => {1.1.1.22} (llu:AKJ09_01495, llu:AKJ09_00381) => {1.1.1.22, 2.7.7.9} (gao:A2G06_12745, gao:A2G06_14565) => {2.4.2.-} (samy:DB32_006581, samy:DB32_004135) => {1.1.1.22, 2.7.7.9} (daf:Desaf_1251, daf:Desaf_2909) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mrm:A7982_08337, mrm:A7982_07443) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ank:AnaeK_4425, ank:AnaeK_0232) => {1.1.1.22} (dsa:Desal_1645, dsa:Desal_2033) => {1.1.1.22, 2.7.7.9} (dol:Dole_1848, dol:Dole_2324) => {1.1.1.22, 2.7.7.9} (doa:AXF15_09785, doa:AXF15_11375) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gme:Gmet_1357, gme:Gmet_2360) => {2.1.3.2} (msd:MYSTI_05067, msd:MYSTI_04466) => {1.1.1.22, 2.7.7.9} (gsb:GSUB_04800, gsb:GSUB_10480) => {2.1.3.2} (gur:Gura_2196, gur:Gura_3240) => {2.1.3.2} (dba:Dbac_3166, dba:Dbac_1611) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ade:Adeh_2533, ade:Adeh_1078) => {2.1.3.2} (dml:Dmul_19320, dml:Dmul_08540) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mym:A176_005864, mym:A176_005616) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (mfu:LILAB_03115, mfu:LILAB_01860) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (sur:STAUR_1671, sur:STAUR_2146) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (mbd:MEBOL_000749, mbd:MEBOL_008059) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mrm:A7982_09539, mrm:A7982_02766) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dal:Dalk_4104, dal:Dalk_1699) => {1.1.1.22, 2.7.7.9} (dde:Dde_2182, dde:Dde_2187) => {1.1.1.22, 2.7.7.9} (drt:Dret_0307, drt:Dret_2499) => {1.1.1.22} (dti:Desti_0219, dti:Desti_0353) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mmas:MYMAC_004575, mmas:MYMAC_004629) => {2.1.3.2} (sat:SYN_01532, sat:SYN_02156) => {2.1.3.2} (dml:Dmul_22850, dml:Dmul_18930) => {2.1.3.2} (sfu:Sfum_1302, sfu:Sfum_1418) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (vin:AKJ08_1417, vin:AKJ08_2627) => {1.1.1.22, 2.7.7.9} (dto:TOL2_C05220, dto:TOL2_C27650) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (cfus:CYFUS_004500, cfus:CYFUS_005495) => {1.1.1.22, 2.7.7.9} (gme:Gmet_0552, gme:Gmet_1934) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dml:Dmul_23620, dml:Dmul_24630) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (afw:Anae109_4354, afw:Anae109_0462) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (age:AA314_04350, age:AA314_05840) => {1.1.1.22} (dds:Ddes_1748, dds:Ddes_1253) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_4164, dti:Desti_2797) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (des:DSOUD_1782, des:DSOUD_0047) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dbr:Deba_3187, dbr:Deba_1780) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dat:HRM2_08850, dat:HRM2_47830) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ank:AnaeK_1924, ank:AnaeK_0232) => {1.1.1.22} (gpi:GPICK_08380, gpi:GPICK_15365) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dml:Dmul_21830, dml:Dmul_28300) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dsa:Desal_3407, dsa:Desal_0178) => {2.1.3.2, 2.3.3.1} (dhy:DESAM_20863, dhy:DESAM_20155) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (das:Daes_0542, das:Daes_2972) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gme:Gmet_0552, gme:Gmet_2822) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (geo:Geob_0666, geo:Geob_2629) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dto:TOL2_C35290, dto:TOL2_C23400) => {1.1.1.22} (dej:AWY79_03870, dej:AWY79_13255) => {2.1.3.2} (dej:AWY79_00980, dej:AWY79_17820) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (msd:MYSTI_06833, msd:MYSTI_05093) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (sat:SYN_02635, sat:SYN_03128) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gpi:GPICK_02900, gpi:GPICK_04075) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (mmas:MYMAC_003449, mmas:MYMAC_003905) => {1.1.1.22, 2.7.7.9} (ccx:COCOR_04535, ccx:COCOR_03939) => {1.1.1.22, 2.7.7.9} (dao:Desac_0519, dao:Desac_2462) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (ccx:COCOR_05520, ccx:COCOR_02172) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gpi:GPICK_11740, gpi:GPICK_10380) => {1.1.1.22} (dsa:Desal_2682, dsa:Desal_3834) => {1.1.1.22, 2.7.7.9} (dgg:DGI_0581, dgg:DGI_3014) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mfu:LILAB_24705, mfu:LILAB_28305) => {2.1.3.2, 2.3.3.1} (age:AA314_05002, age:AA314_05003) => {1.1.1.22, 2.7.7.9} (ank:AnaeK_2242, ank:AnaeK_2784) => {2.1.3.2} (daf:Desaf_1391, daf:Desaf_2909) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2345, dti:Desti_4907) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gpi:GPICK_08745, gpi:GPICK_10520) => {2.1.3.2} (ccx:COCOR_02713, ccx:COCOR_02664) => {2.1.3.2} (dsf:UWK_01260, dsf:UWK_03510) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dto:TOL2_C12360, dto:TOL2_C23400) => {1.1.1.22, 2.7.7.9} (mbd:MEBOL_006836, mbd:MEBOL_006837) => {1.1.1.22, 2.7.7.9} (dml:Dmul_22810, dml:Dmul_24040) => {2.4.2.-} (age:AA314_05007, age:AA314_05880) => {2.1.3.2} (hmr:Hipma_1703, hmr:Hipma_1401) => {1.1.1.22} (sat:SYN_01223, sat:SYN_03128) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dsa:Desal_0574, dsa:Desal_0740) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (cfus:CYFUS_001459, cfus:CYFUS_002029) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dat:HRM2_08850, dat:HRM2_13680) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gpi:GPICK_02240, gpi:GPICK_02235) => {2.4.2.-} (def:CNY67_14075, def:CNY67_08465) => {2.6.1.16} (geo:Geob_1368, geo:Geob_2629) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dak:DaAHT2_2315, dak:DaAHT2_2211) => {2.1.3.2} (dds:Ddes_1950, dds:Ddes_0025) => {1.1.1.22, 2.7.7.9} (deu:DBW_1942, deu:DBW_0911) => {2.1.3.2} (dsf:UWK_02797, dsf:UWK_02514) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dat:HRM2_28720, dat:HRM2_13680) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2341, dti:Desti_1457) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (geb:GM18_2790, geb:GM18_0730) => {2.1.3.2} (dti:Desti_0225, dti:Desti_2739) => {1.1.1.22, 2.7.7.9} (dat:HRM2_28720, dat:HRM2_47820) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dhy:DESAM_20633, dhy:DESAM_20155) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (samy:DB32_003842, samy:DB32_003841) => {2.4.2.-} (mfu:LILAB_31365, mfu:LILAB_31605) => {2.1.3.2} (mxa:MXAN_4613, mxa:MXAN_3987) => {1.1.1.22} (cfus:CYFUS_004499, cfus:CYFUS_004500) => {1.1.1.22, 2.7.7.9} (dhy:DESAM_22057, dhy:DESAM_20916) => {1.1.1.22, 2.7.7.9} (dml:Dmul_19320, dml:Dmul_36880) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dpg:DESPIGER_1297, dpg:DESPIGER_1913) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ppd:Ppro_2529, ppd:Ppro_3172) => {2.1.3.2} (dol:Dole_1010, dol:Dole_1848) => {1.1.1.22, 2.7.7.9} (dfi:AXF13_10380, dfi:AXF13_05975) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (glo:Glov_0796, glo:Glov_2182) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (cfus:CYFUS_004504, cfus:CYFUS_005533) => {2.1.3.2} (geb:GM18_4149, geb:GM18_4150) => {2.4.2.-} (llu:AKJ09_01495, llu:AKJ09_02991) => {1.1.1.22, 2.7.7.9} (age:AA314_04258, age:AA314_04205) => {2.1.3.2} (dti:Desti_0219, dti:Desti_3164) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gao:A2G06_14560, gao:A2G06_14565) => {2.4.2.-} (llu:AKJ09_06149, llu:AKJ09_05466) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2348, dti:Desti_2003) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dhy:DESAM_20916, dhy:DESAM_20726) => {1.1.1.22, 2.7.7.9} (dba:Dbac_1478, dba:Dbac_1611) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_0219, dti:Desti_1366) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mym:A176_006029, mym:A176_005454) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pprf:DPRO_1502, pprf:DPRO_1432) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mym:A176_003863, mym:A176_002255) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (gpi:GPICK_09850, gpi:GPICK_01450) => {2.1.3.2} (age:AA314_02310, age:AA314_02714) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dde:Dde_2648, dde:Dde_0626) => {2.6.1.16} (gur:Gura_3273, gur:Gura_2598) => {1.1.1.22} (ade:Adeh_2533, ade:Adeh_2728) => {2.1.3.2} (gpi:GPICK_06970, gpi:GPICK_00285) => {2.6.1.16} (gsb:GSUB_08845, gsb:GSUB_02540) => {2.4.2.-} (dhy:DESAM_20633, dhy:DESAM_20933) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gsu:GSU1463, gsu:GSU2271) => {2.1.3.2} (msd:MYSTI_06468, msd:MYSTI_01751) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mxa:MXAN_0949, mxa:MXAN_1528) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dat:HRM2_11950, dat:HRM2_13680) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_4164, dti:Desti_2479) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dps:DP2097, dps:DP0555) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_4164, dti:Desti_1457) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dao:Desac_2544, dao:Desac_0239) => {1.1.1.22} (sur:STAUR_0056, sur:STAUR_5425) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dat:HRM2_47210, dat:HRM2_47830) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dol:Dole_0670, dol:Dole_2847) => {2.1.3.2} (dml:Dmul_19320, dml:Dmul_24630) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ppd:Ppro_3484, ppd:Ppro_1725) => {2.6.1.16} (mbd:MEBOL_008079, mbd:MEBOL_006001) => {2.1.3.2} (lip:LI1066, lip:LI0580) => {1.1.1.22} (mym:A176_006029, mym:A176_007563) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dba:Dbac_2884, dba:Dbac_3039) => {1.1.1.22} (ade:Adeh_1954, ade:Adeh_0221) => {1.1.1.22, 2.7.7.9} (sfu:Sfum_3692, sfu:Sfum_1215) => {2.4.2.-} (dto:TOL2_C08210, dto:TOL2_C23400) => {1.1.1.22, 2.7.7.9} (sat:SYN_01130, sat:SYN_02661) => {1.1.1.22, 2.7.7.9} (pef:A7E78_05895, pef:A7E78_01330) => {2.1.3.2} (dma:DMR_39860, dma:DMR_44510) => {2.6.1.16} (dti:Desti_2345, dti:Desti_2003) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dal:Dalk_3370, dal:Dalk_0935) => {2.1.3.2, 2.3.3.1} (dsf:UWK_01152, dsf:UWK_03535) => {2.1.3.2} (dml:Dmul_19320, dml:Dmul_28300) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pca:Pcar_1326, pca:Pcar_2933) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dbr:Deba_0994, dbr:Deba_2773) => {1.1.1.22, 2.7.7.9} (dsa:Desal_2033, dsa:Desal_3834) => {1.1.1.22, 2.7.7.9} (hmr:Hipma_1025, hmr:Hipma_1045) => {2.1.3.2, 2.3.3.1} (afw:Anae109_1900, afw:Anae109_4196) => {1.1.1.22} (mmas:MYMAC_004501, mmas:MYMAC_003905) => {1.1.1.22} (dti:Desti_2341, dti:Desti_2479) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (vin:AKJ08_1411, vin:AKJ08_0163) => {2.1.3.2} (dto:TOL2_C35290, dto:TOL2_C35200) => {1.1.1.22, 2.7.7.9} (drt:Dret_0818, drt:Dret_1756) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dol:Dole_1975, dol:Dole_0337) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gem:GM21_0265, gem:GM21_3025) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dat:HRM2_27780, dat:HRM2_27560) => {2.1.3.2} (dal:Dalk_2329, dal:Dalk_3333) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_0219, dti:Desti_3693) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dpb:BABL1_gene_330, dpb:BABL1_gene_705) => {2.1.3.2} (sur:STAUR_3296, sur:STAUR_2302) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pef:A7E78_11150, pef:A7E78_02750) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (sur:STAUR_4027, sur:STAUR_4028) => {1.1.1.22, 2.7.7.9} (gao:A2G06_09675, gao:A2G06_05980) => {2.1.3.2} (drt:Dret_2132, drt:Dret_1756) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (daf:Desaf_1251, daf:Desaf_1333) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dhy:DESAM_20564, dhy:DESAM_20155) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ccro:CMC5_012520, ccro:CMC5_019230) => {1.1.1.22, 2.7.7.9} (sfu:Sfum_0483, sfu:Sfum_1215) => {2.4.2.-} (sat:SYN_02866, sat:SYN_01112) => {1.1.1.22} (dhy:DESAM_20863, dhy:DESAM_20933) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pca:Pcar_1040, pca:Pcar_1248) => {2.1.3.2} (afw:Anae109_1329, afw:Anae109_1117) => {2.1.3.2} (des:DSOUD_1475, des:DSOUD_1660) => {2.1.3.2} (dvu:DVU2250, dvu:DVU1453) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dto:TOL2_C05220, dto:TOL2_C26900) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2345, dti:Desti_3164) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dgg:DGI_1438, dgg:DGI_2476) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (vin:AKJ08_0731, vin:AKJ08_1262) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (afw:Anae109_4443, afw:Anae109_4196) => {1.1.1.22} (gem:GM21_2312, gem:GM21_3742) => {2.1.3.2} (dml:Dmul_23620, dml:Dmul_28300) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dbr:Deba_2122, dbr:Deba_0581) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gao:A2G06_10540, gao:A2G06_15675) => {2.1.3.2} (def:CNY67_03710, def:CNY67_08360) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (cfus:CYFUS_001210, cfus:CYFUS_004967) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dao:Desac_2517, dao:Desac_2262) => {2.4.2.-} (pca:Pcar_2593, pca:Pcar_1807) => {1.1.1.22, 2.7.7.9} (dml:Dmul_07490, dml:Dmul_24260) => {1.1.1.22, 2.7.7.9} (dti:Desti_4164, dti:Desti_3164) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pef:A7E78_01045, pef:A7E78_03875) => {1.1.1.22, 2.7.7.9} (doa:AXF15_05040, doa:AXF15_02145) => {2.1.3.2} (dti:Desti_2341, dti:Desti_0901) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (mxa:MXAN_3507, mxa:MXAN_3987) => {1.1.1.22, 2.7.7.9} (gsu:GSU1271, gsu:GSU0152) => {2.1.3.2} (ccx:COCOR_04815, ccx:COCOR_03939) => {1.1.1.22} (dpi:BN4_12054, dpi:BN4_12643) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dbr:Deba_2122, dbr:Deba_2748) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2348, dti:Desti_1457) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pef:A7E78_02600, pef:A7E78_11715) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dbr:Deba_2503, dbr:Deba_0581) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dti:Desti_2348, dti:Desti_2479) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (hmr:Hipma_0215, hmr:Hipma_1516) => {2.4.2.-} (dhy:DESAM_21173, dhy:DESAM_20160) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (dto:TOL2_C31520, dto:TOL2_C37120) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dsa:Desal_0017, dsa:Desal_1784) => {2.1.3.2} (gbm:Gbem_3346, gbm:Gbem_0861) => {1.1.1.22} (gsb:GSUB_02545, gsb:GSUB_02540) => {2.4.2.-} (gur:Gura_1856, gur:Gura_0227) => {2.1.3.2} (geb:GM18_0317, geb:GM18_3441) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1} (hoh:Hoch_5324, hoh:Hoch_0394) => {2.1.3.2} (dbr:Deba_3125, dbr:Deba_0292) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (msd:MYSTI_04466, msd:MYSTI_03928) => {1.1.1.22, 2.7.7.9} (lip:LIC023, lip:LI0580) => {1.1.1.22, 2.7.7.9} (dhy:DESAM_22216, dhy:DESAM_20726) => {1.1.1.22, 2.7.7.9} (ppd:Ppro_3055, ppd:Ppro_3056) => {2.4.2.-} (dto:TOL2_C35200, dto:TOL2_C23400) => {1.1.1.22, 2.7.7.9} (mmas:MYMAC_003338, mmas:MYMAC_003947) => {2.1.3.2, 2.3.3.1} (msd:MYSTI_05067, msd:MYSTI_03928) => {1.1.1.22} (deu:DBW_2313, deu:DBW_2132) => {1.1.1.22, 2.7.7.9} (pef:A7E78_02985, pef:A7E78_13795) => {2.1.3.2} (drt:Dret_0321, drt:Dret_0143) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dhy:DESAM_21612, dhy:DESAM_20155) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (doa:AXF15_02215, doa:AXF15_08610) => {1.1.1.22, 2.7.7.9} (dak:DaAHT2_1791, dak:DaAHT2_1792) => {1.1.1.22} (age:AA314_04350, age:AA314_04970) => {1.1.1.22, 2.7.7.9} (dti:Desti_2341, dti:Desti_2797) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dat:HRM2_28720, dat:HRM2_47830) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (sfu:Sfum_3454, sfu:Sfum_0108) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pef:A7E78_08220, pef:A7E78_08225) => {2.4.2.-} (gme:Gmet_2340, gme:Gmet_1613) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dal:Dalk_0475, dal:Dalk_4104) => {1.1.1.22, 2.7.7.9} (pace:A6070_05385, pace:A6070_01880) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (sat:SYN_02635, sat:SYN_02643) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ade:Adeh_1955, ade:Adeh_1954) => {1.1.1.22, 2.7.7.9} (mmas:MYMAC_001135, mmas:MYMAC_001379) => {2.7.6.1, 2.6.1.16, 2.2.1.2, 2.2.1.1} (dti:Desti_2345, dti:Desti_2479) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (geb:GM18_3424, geb:GM18_0750) => {1.1.1.22} (llu:AKJ09_02991, llu:AKJ09_09399) => {1.1.1.22, 2.7.7.9} (gsb:GSUB_08195, gsb:GSUB_15430) => {1.1.1.22} (geo:Geob_0693, geo:Geob_0692) => {2.4.2.-} (gsb:GSUB_09180, gsb:GSUB_03040) => {2.1.3.2} (afw:Anae109_2193, afw:Anae109_2685) => {2.1.3.2} (mrm:A7982_02519, mrm:A7982_09042) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gbm:Gbem_1896, gbm:Gbem_3637) => {2.1.3.2} (dej:AWY79_01195, dej:AWY79_17820) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dhy:DESAM_22057, dhy:DESAM_22216) => {1.1.1.22, 2.7.7.9} (dbr:Deba_2122, dbr:Deba_1780) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (samy:DB32_007268, samy:DB32_002852) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (ccx:COCOR_00905, ccx:COCOR_02172) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pace:A6070_12850, pace:A6070_13200) => {2.4.2.-} (samy:DB32_001023, samy:DB32_005406) => {2.1.3.2} (dde:Dde_2317, dde:Dde_1725) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (dsa:Desal_0152, dsa:Desal_0743) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (pef:A7E78_01430, pef:A7E78_03875) => {1.1.1.22} (mbd:MEBOL_004362, mbd:MEBOL_005080) => {2.3.1.180, 6.4.1.2, 2.3.3.1} (gbm:Gbem_0280, gbm:Gbem_3362) => {2.2.1.2, 5.1.3.1, 2.7.1.40, 2.7.6.1, 2.2.1.1, 5.3.1.1, 2.6.1.16, 1.2.1.12, 2.7.9.2, 1.4.1.1}

Conclusion

Many neofunctionalisation events contribute to the redundancy of their function changes’ EC numbers. There are more contributing neofunctionalisations than contributing “neofunctionalised” ECs, which is to be expected, because usually several neofunctionalisations are responsible for the same function change. Also, many more neofunctionalisations contribute to flexibility than robustness, which is to be expected, too, because flexibility is by far the weaker (i.e. more common) type of redundancy.

FEV_KEGG.Experiments.49.getCladeA()[source]
FEV_KEGG.Experiments.50 module
Question

How do the core metabolisms of Alphaproteobacteria and Betaproteobacteria compare? Which neofunctionalised enzymes cause the core metabolism of Alphaproteobacteria or Betaproteobacteria to have increased redundancy? How much do they contribute?

Method
  • get clades
  • get core metabolisms
  • calculate “neofunctionalised” ECs
  • calculate redundancies
  • REPEAT for each clade
  • print size of each core metabolism and “neofunctionalised” ECs, including their contribution to redundancy
  • print enzyme pairs of neofunctionalisations, which caused the EC to be considered “neofunctionalised”, and are in return contributing to redundancy
Result 
core metabolism majority: 80%
neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)
type of redundancy: ROBUSTNESS

Alphaproteobacteria:

core metabolism ECs: 215

"neofunctionalised" ECs: 46 (21%)
1.1.1.100
1.1.1.42
1.1.1.85
1.17.7.4
1.2.1.41
1.2.4.1
1.8.1.4
1.8.1.7
2.1.2.2
2.1.3.2
2.1.3.3
2.2.1.1
2.2.1.7
2.3.1.12
2.3.1.39
2.3.1.61
2.4.2.14
2.5.1.90
2.6.1.1
2.6.1.16
2.6.1.9
2.7.4.9
3.1.3.25
3.1.3.7
4.1.1.17
4.1.1.20
4.1.3.-
4.1.3.27
4.3.2.1
4.3.2.2
4.4.1.8
5.3.1.16
6.1.1.12
6.1.1.15
6.1.1.3
6.1.1.4
6.1.1.5
6.1.1.6
6.1.1.9
6.2.1.1
6.3.2.10
6.3.2.13
6.3.2.8
6.3.2.9
6.3.4.18
6.3.5.5

"neofunctionalised" ECs contributing to redundancy: 5 ( 2%)
1.2.4.1 => [1.1.1.40]
2.1.3.3 => [2.1.3.2]
2.2.1.1 => [5.1.3.1, 5.3.1.6]
2.6.1.1 => [2.1.3.2]
4.1.3.- => [2.4.2.-]

Neofunctionalisations contributing to redundancy: 828 (22%)
(aace:A0U92_07025 [1.2.4.1],    aace:A0U92_07030 [2.3.1.12])    => [1.1.1.40]
(aak:AA2016_3788 [1.2.4.1],     aak:AA2016_3787 [2.3.1.12])     => [1.1.1.40]
(aay:WYH_00471 [1.2.4.1],       aay:WYH_00533 [2.3.1.12])       => [1.1.1.40]
(abg:Asbog_01243 [1.2.4.1],     abg:Asbog_01244 [2.3.1.12])     => [1.1.1.40]
(acr:Acry_2820 [1.2.4.1],       acr:Acry_2821 [2.3.1.12])       => [1.1.1.40]
(ado:A6F68_02189 [1.2.4.1],     ado:A6F68_02343 [2.3.1.12])     => [1.1.1.40]
(aep:AMC99_01209 [1.2.4.1],     aep:AMC99_01171 [2.3.1.12])     => [1.1.1.40]
(aex:Astex_2920 [1.2.4.1],      aex:Astex_2919 [2.3.1.12])      => [1.1.1.40]
(agc:BSY240_693 [1.2.4.1],      agc:BSY240_692 [2.3.1.12])      => [1.1.1.40]
(agr:AGROH133_05921 [1.2.4.1],  agr:AGROH133_05922 [2.3.1.12])  => [1.1.1.40]
(aht:ANTHELSMS3_03039 [1.2.4.1],aht:ANTHELSMS3_03037 [2.3.1.12])=> [1.1.1.40]
(ahu:A6A40_05280 [1.2.4.1],     ahu:A6A40_05275 [2.3.1.12])     => [1.1.1.40]
(amv:ACMV_31580 [1.2.4.1],      amv:ACMV_31590 [2.3.1.12])      => [1.1.1.40]
(amx:AM2010_985 [1.2.4.1],      amx:AM2010_922 [2.3.1.12])      => [1.1.1.40]
(anh:A6F65_01749 [1.2.4.1],     anh:A6F65_01679 [2.3.1.12])     => [1.1.1.40]
(aol:S58_35510 [1.2.4.1],       aol:S58_35530 [2.3.1.12])       => [1.1.1.40]
(apb:SAR116_0206 [1.2.4.1],     apb:SAR116_0207 [2.3.1.12])     => [1.1.1.40]
(aper:A0U91_02040 [1.2.4.1],    aper:A0U91_02045 [2.3.1.12])    => [1.1.1.40]
(apm:HIMB5_00012850 [1.2.4.1],  apm:HIMB5_00012840 [2.3.1.12])  => [1.1.1.40]
(apom:CPF11_01350 [1.2.4.1],    apom:CPF11_01355 [2.3.1.12])    => [1.1.1.40]
(apt:APA01_12170 [1.2.4.1],     apt:APA01_12160 [2.3.1.12])     => [1.1.1.40]
(ara:Arad_2247 [1.2.4.1],       ara:Arad_2249 [2.3.1.12])       => [1.1.1.40]
(aro:B0909_06395 [1.2.4.1],     aro:B0909_06390 [2.3.1.12])     => [1.1.1.40]
(asv:WG31_06600 [1.2.4.1],      asv:WG31_06595 [2.3.1.12])      => [1.1.1.40]
(asz:ASN_3632 [1.2.4.1],        asz:ASN_3633 [2.3.1.12])        => [1.1.1.40]
(ati:AL072_12260 [1.2.4.1],     ati:AL072_12255 [2.3.1.12])     => [1.1.1.40]
(ato:CIW82_12980 [1.2.4.1],     ato:CIW82_12975 [2.3.1.12])     => [1.1.1.40]
(aua:M673_11260 [1.2.4.1],      aua:M673_11265 [2.3.1.12])      => [1.1.1.40]
(avi:Avi_2114 [1.2.4.1],        avi:Avi_2115 [2.3.1.12])        => [1.1.1.40]
(azc:AZC_1743 [1.2.4.1],        azc:AZC_1744 [2.3.1.12])        => [1.1.1.40]
(azl:AZL_015200 [1.2.4.1],      azl:AZL_015190 [2.3.1.12])      => [1.1.1.40]
(banc:PU02_1123 [1.2.4.1],      banc:PU02_1122 [2.3.1.12])      => [1.1.1.40]
(bapi:BBC0122_009290 [1.2.4.1], bapi:BBC0122_009300 [2.3.1.12]) => [1.1.1.40]
(bara:BA1379B_006780 [1.2.4.1], bara:BA1379B_006770 [2.3.1.12]) => [1.1.1.40]
(barr:Bra60_007650 [1.2.4.1],   barr:Bra60_007640 [2.3.1.12])   => [1.1.1.40]
(bart:BJB15x_004370 [1.2.4.1],  bart:BJB15x_004380 [2.3.1.12])  => [1.1.1.40]
(barw:BWD162_003840 [1.2.4.1],  barw:BWD162_003850 [2.3.1.12])  => [1.1.1.40]
(baus:BAnh1_05010 [1.2.4.1],    baus:BAnh1_05020 [2.3.1.12])    => [1.1.1.40]
(bbk:BARBAKC583_0535 [1.2.4.1], bbk:BARBAKC583_0536 [2.3.1.12]) => [1.1.1.40]
(bbt:BBta_4462 [1.2.4.1],       bbt:BBta_4460 [2.3.1.12])       => [1.1.1.40]
(bcd:BARCL_0594 [1.2.4.1],      bcd:BARCL_0595 [2.3.1.12])      => [1.1.1.40]
(bcet:V910_100859 [1.2.4.1],    bcet:V910_100860 [2.3.1.12])    => [1.1.1.40]
(bcet:V910_100859 [1.2.4.1],    bcet:V910_200058 [2.3.1.12])    => [1.1.1.40]
(bcs:BCAN_A1147 [1.2.4.1],      bcs:BCAN_A1146 [2.3.1.12])      => [1.1.1.40]
(bcs:BCAN_A1147 [1.2.4.1],      bcs:BCAN_B0035 [2.3.1.12])      => [1.1.1.40]
(bgr:Bgr_06590 [1.2.4.1],       bgr:Bgr_06600 [2.3.1.12])       => [1.1.1.40]
(bhe:BH05760 [1.2.4.1],         bhe:BH05770 [2.3.1.12])         => [1.1.1.40]
(bic:LMTR13_19285 [1.2.4.1],    bic:LMTR13_19295 [2.3.1.12])    => [1.1.1.40]
(bid:Bind_1506 [1.2.4.1],       bid:Bind_1507 [2.3.1.12])       => [1.1.1.40]
(bja:bll4782 [1.2.4.1],         bja:bll4779 [2.3.1.12])         => [1.1.1.40]
(bju:BJ6T_49290 [1.2.4.1],      bju:BJ6T_49320 [2.3.1.12])      => [1.1.1.40]
(blas:BSY18_579 [1.2.4.1],      blas:BSY18_1020 [2.3.1.12])     => [1.1.1.40]
(bme:BMEI0855 [1.2.4.1],        bme:BMEI0856 [2.3.1.12])        => [1.1.1.40]
(bme:BMEI0855 [1.2.4.1],        bme:BMEII0060 [2.3.1.12])       => [1.1.1.40]
(bmf:BAB1_1151 [1.2.4.1],       bmf:BAB1_1150 [2.3.1.12])       => [1.1.1.40]
(bmf:BAB1_1151 [1.2.4.1],       bmf:BAB2_0032 [2.3.1.12])       => [1.1.1.40]
(bmr:BMI_I1140 [1.2.4.1],       bmr:BMI_II33 [2.3.1.12])        => [1.1.1.40]
(bms:BR1128 [1.2.4.1],          bms:BR1127 [2.3.1.12])          => [1.1.1.40]
(bms:BR1128 [1.2.4.1],          bms:BRA0033 [2.3.1.12])         => [1.1.1.40]
(bne:DA69_05795 [1.2.4.1],      bne:DA69_05785 [2.3.1.12])      => [1.1.1.40]
(bop:AXW83_07560 [1.2.4.1],     bop:AXW83_07555 [2.3.1.12])     => [1.1.1.40]
(bos:BSY19_2691 [1.2.4.1],      bos:BSY19_2692 [2.3.1.12])      => [1.1.1.40]
(bov:BOV_1086 [1.2.4.1],        bov:BOV_1085 [2.3.1.12])        => [1.1.1.40]
(bpp:BPI_I1175 [1.2.4.1],       bpp:BPI_I1174 [2.3.1.12])       => [1.1.1.40]
(bpp:BPI_I1175 [1.2.4.1],       bpp:BPI_II33 [2.3.1.12])        => [1.1.1.40]
(bqu:BQ04920 [1.2.4.1],         bqu:BQ04930 [2.3.1.12])         => [1.1.1.40]
(bra:BRADO4086 [1.2.4.1],       bra:BRADO4084 [2.3.1.12])       => [1.1.1.40]
(brad:BF49_6759 [1.2.4.1],      brad:BF49_6762 [2.3.1.12])      => [1.1.1.40]
(brc:BCCGELA001_20310 [1.2.4.1],brc:BCCGELA001_20295 [2.3.1.12])=> [1.1.1.40]
(brd:JL11_12170 [1.2.4.1],      brd:JL11_12165 [2.3.1.12])      => [1.1.1.40]
(brg:A4249_04935 [1.2.4.1],     brg:A4249_04945 [2.3.1.12])     => [1.1.1.40]
(brk:CWS35_25570 [1.2.4.1],     brk:CWS35_25560 [2.3.1.12])     => [1.1.1.40]
(brl:BZG35_09905 [1.2.4.1],     brl:BZG35_09895 [2.3.1.12])     => [1.1.1.40]
(bro:BRAD285_3292 [1.2.4.1],    bro:BRAD285_3294 [2.3.1.12])    => [1.1.1.40]
(brs:S23_33850 [1.2.4.1],       brs:S23_33880 [2.3.1.12])       => [1.1.1.40]
(bsb:Bresu_1984 [1.2.4.1],      bsb:Bresu_1985 [2.3.1.12])      => [1.1.1.40]
(btr:BT_0862 [1.2.4.1],         btr:BT_0863 [2.3.1.12])         => [1.1.1.40]
(bvc:CEP68_16215 [1.2.4.1],     bvc:CEP68_16220 [2.3.1.12])     => [1.1.1.40]
(bvl:BF3285c1_1939 [1.2.4.1],   bvl:BF3285c1_1938 [2.3.1.12])   => [1.1.1.40]
(bvl:BF3285c1_1939 [1.2.4.1],   bvl:BF3285c2_0762 [2.3.1.12])   => [1.1.1.40]
(bvn:BVwin_05150 [1.2.4.1],     bvn:BVwin_05160 [2.3.1.12])     => [1.1.1.40]
(bvr:BVIR_1927 [1.2.4.1],       bvr:BVIR_1926 [2.3.1.12])       => [1.1.1.40]
(bvv:BHK69_19470 [1.2.4.1],     bvv:BHK69_19475 [2.3.1.12])     => [1.1.1.40]
(cak:Caul_2759 [1.2.4.1],       cak:Caul_2757 [2.3.1.12])       => [1.1.1.40]
(cbot:ATE48_00565 [1.2.4.1],    cbot:ATE48_00550 [2.3.1.12])    => [1.1.1.40]
(ccr:CC_1727 [1.2.4.1],         ccr:CC_1729 [2.3.1.12])         => [1.1.1.40]
(cdq:BOQ54_09390 [1.2.4.1],     cdq:BOQ54_09395 [2.3.1.12])     => [1.1.1.40]
(ceh:CEW89_06310 [1.2.4.1],     ceh:CEW89_05925 [2.3.1.12])     => [1.1.1.40]
(ceh:CEW89_06310 [1.2.4.1],     ceh:CEW89_06315 [2.3.1.12])     => [1.1.1.40]
(ceh:CEW89_06310 [1.2.4.1],     ceh:CEW89_12460 [2.2.1.7])      => [1.1.1.40]
(chel:AL346_17915 [1.2.4.1],    chel:AL346_17920 [2.3.1.12])    => [1.1.1.40]
(chq:AQ619_08905 [1.2.4.1],     chq:AQ619_08900 [2.3.1.12])     => [1.1.1.40]
(cid:P73_1703 [1.2.4.1],        cid:P73_1702 [2.3.1.12])        => [1.1.1.40]
(cij:WG74_09325 [1.2.4.1],      cij:WG74_09505 [2.3.1.12])      => [1.1.1.40]
(cmag:CBW24_10350 [1.2.4.1],    cmag:CBW24_10345 [2.3.1.12])    => [1.1.1.40]
(cman:A9D14_07905 [1.2.4.1],    cman:A9D14_07640 [2.3.1.12])    => [1.1.1.40]
(cmar:IMCC12053_2102 [1.2.4.1], cmar:IMCC12053_2103 [2.3.1.12]) => [1.1.1.40]
(cmb:CSW64_11565 [1.2.4.1],     cmb:CSW64_11555 [2.3.1.12])     => [1.1.1.40]
(cna:AB433_08375 [1.2.4.1],     cna:AB433_01620 [2.2.1.7])      => [1.1.1.40]
(cna:AB433_08375 [1.2.4.1],     cna:AB433_08610 [2.3.1.12])     => [1.1.1.40]
(con:TQ29_08210 [1.2.4.1],      con:TQ29_08205 [2.3.1.12])      => [1.1.1.40]
(cse:Cseg_1968 [1.2.4.1],       cse:Cseg_1969 [2.3.1.12])       => [1.1.1.40]
(daa:AKL17_2657 [1.2.4.1],      daa:AKL17_2658 [2.3.1.12])      => [1.1.1.40]
(deq:XM25_06740 [1.2.4.1],      deq:XM25_06735 [2.3.1.12])      => [1.1.1.40]
(don:BSK21_07650 [1.2.4.1],     don:BSK21_07655 [2.3.1.12])     => [1.1.1.40]
(dsh:Dshi_2159 [1.2.4.1],       dsh:Dshi_2160 [2.3.1.12])       => [1.1.1.40]
(ead:OV14_2519 [1.2.4.1],       ead:OV14_2520 [2.3.1.12])       => [1.1.1.40]
(efv:CHH26_08090 [1.2.4.1],     efv:CHH26_08270 [2.3.1.12])     => [1.1.1.40]
(egn:BMF35_a1962 [1.2.4.1],     egn:BMF35_a1940 [2.3.1.12])     => [1.1.1.40]
(eli:ELI_06400 [1.2.4.1],       eli:ELI_06130 [2.3.1.12])       => [1.1.1.40]
(ery:CP97_09725 [1.2.4.1],      ery:CP97_10070 [2.3.1.12])      => [1.1.1.40]
(esj:SJ05684_c12890 [1.2.4.1],  esj:SJ05684_c12900 [2.3.1.12])  => [1.1.1.40]
(gal:A0U94_06330 [1.2.4.1],     gal:A0U94_06335 [2.3.1.12])     => [1.1.1.40]
(gbe:GbCGDNIH1_1184 [1.2.4.1],  gbe:GbCGDNIH1_1185 [2.3.1.12])  => [1.1.1.40]
(gdi:GDI1940 [1.2.4.1],         gdi:GDI1941 [2.3.1.12])         => [1.1.1.40]
(gox:GOX2290 [1.2.4.1],         gox:GOX2291 [2.3.1.12])         => [1.1.1.40]
(gxl:H845_1900 [1.2.4.1],       gxl:H845_1899 [2.3.1.12])       => [1.1.1.40]
(gxy:GLX_07550 [1.2.4.1],       gxy:GLX_07540 [2.3.1.12])       => [1.1.1.40]
(hat:RC74_15005 [1.2.4.1],      hat:RC74_15000 [2.3.1.12])      => [1.1.1.40]
(hba:Hbal_1687 [1.2.4.1],       hba:Hbal_1686 [2.3.1.12])       => [1.1.1.40]
(hbc:AEM38_08000 [1.2.4.1],     hbc:AEM38_07995 [2.3.1.12])     => [1.1.1.40]
(hdi:HDIA_1538 [1.2.4.1],       hdi:HDIA_1539 [2.3.1.12])       => [1.1.1.40]
(hjo:AY555_08080 [1.2.4.1],     hjo:AY555_08085 [2.3.1.12])     => [1.1.1.40]
(hne:HNE_1976 [1.2.4.1],        hne:HNE_1975 [2.3.1.12])        => [1.1.1.40]
(hoe:IMCC20628_02090 [1.2.4.1], hoe:IMCC20628_02089 [2.3.1.12]) => [1.1.1.40]
(jan:Jann_1690 [1.2.4.1],       jan:Jann_1688 [2.3.1.12])       => [1.1.1.40]
(kba:A0U89_06665 [1.2.4.1],     kba:A0U89_06670 [2.3.1.12])     => [1.1.1.40]
(keu:S101446_01150 [1.2.4.1],   keu:S101446_01149 [2.3.1.12])   => [1.1.1.40]
(kna:B0W47_03380 [1.2.4.1],     kna:B0W47_03375 [2.3.1.12])     => [1.1.1.40]
(kro:BVG79_00934 [1.2.4.1],     kro:BVG79_00933 [2.3.1.12])     => [1.1.1.40]
(kvu:EIO_1168 [1.2.4.1],        kvu:EIO_1167 [2.3.1.12])        => [1.1.1.40]
(labr:CHH27_06240 [1.2.4.1],    labr:CHH27_06235 [2.3.1.12])    => [1.1.1.40]
(lagg:B0E33_26190 [1.2.4.1],    lagg:B0E33_26195 [2.3.1.12])    => [1.1.1.40]
(lap:ACP90_14360 [1.2.4.1],     lap:ACP90_14365 [2.3.1.12])     => [1.1.1.40]
(lar:lam_319 [1.2.4.1],         lar:lam_318 [2.3.1.12])         => [1.1.1.40]
(las:CLIBASIA_02800 [1.2.4.1],  las:CLIBASIA_02805 [2.3.1.12])  => [1.1.1.40]
(lcc:B488_11020 [1.2.4.1],      lcc:B488_11030 [2.3.1.12])      => [1.1.1.40]
(lmd:METH_09250 [1.2.4.1],      lmd:METH_09255 [2.3.1.12])      => [1.1.1.40]
(lvs:LOKVESSMR4R_01694 [1.2.4.1],      lvs:LOKVESSMR4R_01695 [2.3.1.12])       => [1.1.1.40]
(maad:AZF01_10055 [1.2.4.1],    maad:AZF01_10045 [2.3.1.12])    => [1.1.1.40]
(mag:amb2317 [1.2.4.1],         mag:amb2318 [2.3.1.12])         => [1.1.1.40]
(magn:WV31_06605 [1.2.4.1],     magn:WV31_06610 [2.3.1.12])     => [1.1.1.40]
(magq:MGMAQ_2051 [1.2.4.1],     magq:MGMAQ_2050 [2.3.1.12])     => [1.1.1.40]
(magx:XM1_3336 [1.2.4.1],       magx:XM1_3335 [2.3.1.12])       => [1.1.1.40]
(malg:MALG_02099 [1.2.4.1],     malg:MALG_02101 [2.3.1.12])     => [1.1.1.40]
(mam:Mesau_04179 [1.2.4.1],     mam:Mesau_04178 [2.3.1.12])     => [1.1.1.40]
(mamo:A6B35_19500 [1.2.4.1],    mamo:A6B35_19495 [2.3.1.12])    => [1.1.1.40]
(maqu:Maq22A_c16995 [1.2.4.1],  maqu:Maq22A_c16980 [2.3.1.12])  => [1.1.1.40]
(mci:Mesci_3696 [1.2.4.1],      mci:Mesci_3697 [2.3.1.12])      => [1.1.1.40]
(mes:Meso_1629 [1.2.4.1],       mes:Meso_1628 [2.3.1.12])       => [1.1.1.40]
(meso:BSQ44_15320 [1.2.4.1],    meso:BSQ44_15310 [2.3.1.12])    => [1.1.1.40]
(mesw:A9K65_019865 [1.2.4.1],   mesw:A9K65_019870 [2.3.1.12])   => [1.1.1.40]
(met:M446_5897 [1.2.4.1],       met:M446_5900 [2.3.1.12])       => [1.1.1.40]
(meta:Y590_13445 [1.2.4.1],     meta:Y590_13455 [2.3.1.12])     => [1.1.1.40]
(mex:Mext_2787 [1.2.4.1],       mex:Mext_2789 [2.3.1.12])       => [1.1.1.40]
(mey:TM49_16605 [1.2.4.1],      mey:TM49_16600 [2.3.1.12])      => [1.1.1.40]
(mgy:MGMSRv2__0967 [1.2.4.1],   mgy:MGMSRv2__0968 [2.3.1.12])   => [1.1.1.40]
(mln:A9174_23275 [1.2.4.1],     mln:A9174_23270 [2.3.1.12])     => [1.1.1.40]
(mlo:mlr0384 [1.2.4.1],         mlo:mlr0385 [2.3.1.12])         => [1.1.1.40]
(mmed:Mame_02759 [1.2.4.1],     mmed:Mame_02760 [2.3.1.12])     => [1.1.1.40]
(mmr:Mmar10_1418 [1.2.4.1],     mmr:Mmar10_1420 [2.3.1.12])     => [1.1.1.40]
(mno:Mnod_6516 [1.2.4.1],       mno:Mnod_6518 [2.3.1.12])       => [1.1.1.40]
(moc:BB934_27340 [1.2.4.1],     moc:BB934_27350 [2.3.1.12])     => [1.1.1.40]
(mop:Mesop_4545 [1.2.4.1],      mop:Mesop_4544 [2.3.1.12])      => [1.1.1.40]
(mor:MOC_1206 [1.2.4.1],        mor:MOC_1209 [2.3.1.12])        => [1.1.1.40]
(mphy:MCBMB27_00584 [1.2.4.1],  mphy:MCBMB27_00587 [2.3.1.12])  => [1.1.1.40]
(mpo:Mpop_2910 [1.2.4.1],       mpo:Mpop_2912 [2.3.1.12])       => [1.1.1.40]
(mrd:Mrad2831_0989 [1.2.4.1],   mrd:Mrad2831_0992 [2.3.1.12])   => [1.1.1.40]
(msl:Msil_0520 [1.2.4.1],       msl:Msil_0521 [2.3.1.12])       => [1.1.1.40]
(mza:B2G69_21495 [1.2.4.1],     mza:B2G69_21505 [2.3.1.12])     => [1.1.1.40]
(nao:Y958_07910 [1.2.4.1],      nao:Y958_07905 [2.3.1.12])      => [1.1.1.40]
(nar:Saro_1909 [1.2.4.1],       nar:Saro_1946 [2.3.1.12])       => [1.1.1.40]
(ncb:C0V82_02645 [1.2.4.1],     ncb:C0V82_02650 [2.3.1.12])     => [1.1.1.40]
(nch:A0U93_04645 [1.2.4.1],     nch:A0U93_04640 [2.3.1.12])     => [1.1.1.40]
(ngl:RG1141_CH15540 [1.2.4.1],  ngl:RG1141_CH15550 [2.3.1.12])  => [1.1.1.40]
(nha:Nham_1750 [1.2.4.1],       nha:Nham_1751 [2.3.1.12])       => [1.1.1.40]
(npn:JI59_03450 [1.2.4.1],      npn:JI59_03675 [2.3.1.12])      => [1.1.1.40]
(npn:JI59_03450 [1.2.4.1],      npn:JI59_10595 [2.2.1.7])       => [1.1.1.40]
(npn:JI59_03450 [1.2.4.1],      npn:JI59_22060 [2.3.1.12])      => [1.1.1.40]
(npp:PP1Y_AT26298 [1.2.4.1],    npp:PP1Y_AT2120 [2.2.1.7])      => [1.1.1.40]
(npp:PP1Y_AT26298 [1.2.4.1],    npp:PP1Y_AT25743 [2.3.1.12])    => [1.1.1.40]
(nre:BES08_04330 [1.2.4.1],     nre:BES08_03975 [2.3.1.12])     => [1.1.1.40]
(nre:BES08_04330 [1.2.4.1],     nre:BES08_18280 [2.3.1.12])     => [1.1.1.40]
(nwi:Nwi_1817 [1.2.4.1],        nwi:Nwi_1816 [2.3.1.12])        => [1.1.1.40]
(oan:Oant_2060 [1.2.4.1],       oan:Oant_2061 [2.3.1.12])       => [1.1.1.40]
(oar:OA238_c11030 [1.2.4.1],    oar:OA238_c11020 [2.3.1.12])    => [1.1.1.40]
(oat:OAN307_c27940 [1.2.4.1],   oat:OAN307_c27950 [2.3.1.12])   => [1.1.1.40]
(oca:OCAR_6285 [1.2.4.1],       oca:OCAR_6284 [2.3.1.12])       => [1.1.1.40]
(och:CES85_1265 [1.2.4.1],      och:CES85_1264 [2.3.1.12])      => [1.1.1.40]
(ops:A8A54_05250 [1.2.4.1],     ops:A8A54_05245 [2.3.1.12])     => [1.1.1.40]
(otm:OSB_19370 [1.2.4.1],       otm:OSB_19380 [2.3.1.12])       => [1.1.1.40]
(paby:Ga0080574_TMP4725 [1.2.4.1],      paby:Ga0080574_TMP142 [2.3.1.12])       => [1.1.1.40]
(paby:Ga0080574_TMP4725 [1.2.4.1],      paby:Ga0080574_TMP4727 [2.3.1.12])      => [1.1.1.40]
(pami:JCM7686_1054 [1.2.4.1],   pami:JCM7686_1053 [2.3.1.12])   => [1.1.1.40]
(paro:CUV01_02990 [1.2.4.1],    paro:CUV01_02995 [2.3.1.12])    => [1.1.1.40]
(paru:CYR75_07680 [1.2.4.1],    paru:CYR75_07685 [2.3.1.12])    => [1.1.1.40]
(pbr:PB2503_08834 [1.2.4.1],    pbr:PB2503_08849 [2.3.1.12])    => [1.1.1.40]
(pcon:B0A89_07015 [1.2.4.1],    pcon:B0A89_07005 [2.3.1.12])    => [1.1.1.40]
(pde:Pden_3891 [1.2.4.1],       pde:Pden_3890 [2.3.1.12])       => [1.1.1.40]
(pel:SAR11G3_00622 [1.2.4.1],   pel:SAR11G3_00621 [2.3.1.12])   => [1.1.1.40]
(pga:PGA1_c17560 [1.2.4.1],     pga:PGA1_c17570 [2.3.1.12])     => [1.1.1.40]
(pgd:Gal_01568 [1.2.4.1],       pgd:Gal_01567 [2.3.1.12])       => [1.1.1.40]
(pgv:SL003B_1083 [1.2.4.1],     pgv:SL003B_3299 [2.2.1.7])      => [1.1.1.40]
(phl:KKY_1384 [1.2.4.1],        phl:KKY_1385 [2.3.1.12])        => [1.1.1.40]
(php:PhaeoP97_01777 [1.2.4.1],  php:PhaeoP97_01778 [2.3.1.12])  => [1.1.1.40]
(pht:BLM14_08405 [1.2.4.1],     pht:BLM14_08410 [2.3.1.12])     => [1.1.1.40]
(pla:Plav_3140 [1.2.4.1],       pla:Plav_3139 [2.3.1.12])       => [1.1.1.40]
(pns:A9D12_12435 [1.2.4.1],     pns:A9D12_04905 [2.2.1.7])      => [1.1.1.40]
(pns:A9D12_12435 [1.2.4.1],     pns:A9D12_12255 [2.3.1.12])     => [1.1.1.40]
(porl:BG023_111981 [1.2.4.1],   porl:BG023_111945 [2.3.1.12])   => [1.1.1.40]
(porl:BG023_111981 [1.2.4.1],   porl:BG023_11354 [2.2.1.7])     => [1.1.1.40]
(pphr:APZ00_18065 [1.2.4.1],    pphr:APZ00_18070 [2.3.1.12])    => [1.1.1.40]
(ppic:PhaeoP14_01654 [1.2.4.1], ppic:PhaeoP14_01655 [2.3.1.12]) => [1.1.1.40]
(psf:PSE_3295 [1.2.4.1],        psf:PSE_3294 [2.3.1.12])        => [1.1.1.40]
(psin:CAK95_23135 [1.2.4.1],    psin:CAK95_23140 [2.3.1.12])    => [1.1.1.40]
(ptp:RCA23_c18000 [1.2.4.1],    ptp:RCA23_c18010 [2.3.1.12])    => [1.1.1.40]
(pub:SAR11_0429 [1.2.4.1],      pub:SAR11_0430 [2.3.1.12])      => [1.1.1.40]
(pye:A6J80_12750 [1.2.4.1],     pye:A6J80_12745 [2.3.1.12])     => [1.1.1.40]
(pzh:CX676_18090 [1.2.4.1],     pzh:CX676_10325 [2.2.1.7])      => [1.1.1.40]
(pzh:CX676_18090 [1.2.4.1],     pzh:CX676_18085 [2.3.1.12])     => [1.1.1.40]
(pzu:PHZ_c1743 [1.2.4.1],       pzu:PHZ_c0912 [2.2.1.7])        => [1.1.1.40]
(pzu:PHZ_c1743 [1.2.4.1],       pzu:PHZ_c1741 [2.3.1.12])       => [1.1.1.40]
(rbg:BG454_12650 [1.2.4.1],     rbg:BG454_12655 [2.3.1.12])     => [1.1.1.40]
(rbm:TEF_09655 [1.2.4.1],       rbm:TEF_09660 [2.3.1.12])       => [1.1.1.40]
(rce:RC1_0120 [1.2.4.1],        rce:RC1_0121 [2.3.1.12])        => [1.1.1.40]
(rcp:RCAP_rcc01704 [1.2.4.1],   rcp:RCAP_rcc01703 [2.3.1.12])   => [1.1.1.40]
(rde:RD1_3013 [1.2.4.1],        rde:RD1_3014 [2.3.1.12])        => [1.1.1.40]
(rdi:CMV14_08920 [1.2.4.1],     rdi:CMV14_07905 [2.3.1.12])     => [1.1.1.40]
(ret:RHE_CH01934 [1.2.4.1],     ret:RHE_CH01935 [2.3.1.12])     => [1.1.1.40]
(rga:RGR602_CH01828 [1.2.4.1],  rga:RGR602_CH01829 [2.3.1.12])  => [1.1.1.40]
(rgi:RGI145_09000 [1.2.4.1],    rgi:RGI145_08995 [2.3.1.12])    => [1.1.1.40]
(rhi:NGR_c12830 [1.2.4.1],      rhi:NGR_c12850 [2.3.1.12])      => [1.1.1.40]
(rhl:LPU83_2559 [1.2.4.1],      rhl:LPU83_2558 [2.3.1.12])      => [1.1.1.40]
(rhm:B5V46_11575 [1.2.4.1],     rhm:B5V46_00795 [2.2.1.7])      => [1.1.1.40]
(rhm:B5V46_11575 [1.2.4.1],     rhm:B5V46_11580 [2.3.1.12])     => [1.1.1.40]
(rhn:AMJ98_CH01997 [1.2.4.1],   rhn:AMJ98_CH01998 [2.3.1.12])   => [1.1.1.40]
(rhp:LPB142_08045 [1.2.4.1],    rhp:LPB142_08040 [2.3.1.12])    => [1.1.1.40]
(rht:NT26_1619 [1.2.4.1],       rht:NT26_1620 [2.3.1.12])       => [1.1.1.40]
(rhx:AMK02_CH02005 [1.2.4.1],   rhx:AMK02_CH02006 [2.3.1.12])   => [1.1.1.40]
(rhz:RHPLAN_39510 [1.2.4.1],    rhz:RHPLAN_39530 [2.3.1.12])    => [1.1.1.40]
(rir:BN877_I1389 [1.2.4.1],     rir:BN877_I1390 [2.3.1.12])     => [1.1.1.40]
(rle:RL2242 [1.2.4.1],          rle:RL2243 [2.3.1.12])          => [1.1.1.40]
(rli:RLO149_c014190 [1.2.4.1],  rli:RLO149_c014180 [2.3.1.12])  => [1.1.1.40]
(rmb:K529_008000 [1.2.4.1],     rmb:K529_008005 [2.3.1.12])     => [1.1.1.40]
(rmm:ROSMUCSMR3_03446 [1.2.4.1],rmm:ROSMUCSMR3_00895 [2.2.1.7]) => [1.1.1.40]
(rmm:ROSMUCSMR3_03446 [1.2.4.1],rmm:ROSMUCSMR3_03447 [2.3.1.12])=> [1.1.1.40]
(ros:CTJ15_08415 [1.2.4.1],     ros:CTJ15_08420 [2.3.1.12])     => [1.1.1.40]
(rpa:RPA2866 [1.2.4.1],         rpa:RPA2864 [2.3.1.12])         => [1.1.1.40]
(rpha:AMC79_CH02115 [1.2.4.1],  rpha:AMC79_CH02116 [2.3.1.12])  => [1.1.1.40]
(rru:Rru_A1880 [1.2.4.1],       rru:Rru_A1879 [2.3.1.12])       => [1.1.1.40]
(rsp:RSP_4049 [1.2.4.1],        rsp:RSP_4050 [2.3.1.12])        => [1.1.1.40]
(rsu:NHU_02744 [1.2.4.1],       rsu:NHU_02745 [2.3.1.12])       => [1.1.1.40]
(rsu:NHU_02744 [1.2.4.1],       rsu:NHU_03965 [2.2.1.7])        => [1.1.1.40]
(rtr:RTCIAT899_CH08600 [1.2.4.1],       rtr:RTCIAT899_CH08605 [2.3.1.12])       => [1.1.1.40]
(rva:Rvan_1333 [1.2.4.1],       rva:Rvan_1331 [2.3.1.12])       => [1.1.1.40]
(sagu:CDO87_01050 [1.2.4.1],    sagu:CDO87_01060 [2.3.1.12])    => [1.1.1.40]
(sal:Sala_0526 [1.2.4.1],       sal:Sala_1235 [2.3.1.12])       => [1.1.1.40]
(same:SAMCFNEI73_Ch1575 [1.2.4.1],      same:SAMCFNEI73_Ch1576 [2.3.1.12])      => [1.1.1.40]
(sbd:ATN00_16165 [1.2.4.1],     sbd:ATN00_14290 [2.3.1.12])     => [1.1.1.40]
(sch:Sphch_0554 [1.2.4.1],      sch:Sphch_1066 [2.3.1.12])      => [1.1.1.40]
(sch:Sphch_0554 [1.2.4.1],      sch:Sphch_1123 [2.2.1.7])       => [1.1.1.40]
(sch:Sphch_0554 [1.2.4.1],      sch:Sphch_3446 [2.3.1.12])      => [1.1.1.40]
(sch:Sphch_3732 [1.2.4.1],      sch:Sphch_1066 [2.3.1.12])      => [1.1.1.40]
(sch:Sphch_3732 [1.2.4.1],      sch:Sphch_1123 [2.2.1.7])       => [1.1.1.40]
(sch:Sphch_3732 [1.2.4.1],      sch:Sphch_3446 [2.3.1.12])      => [1.1.1.40]
(sclo:SCLO_1011100 [1.2.4.1],   sclo:SCLO_1007870 [2.3.1.12])   => [1.1.1.40]
(sfla:SPHFLASMR4Y_01022 [1.2.4.1],      sfla:SPHFLASMR4Y_00806 [2.3.1.12])      => [1.1.1.40]
(sgi:SGRAN_2407 [1.2.4.1],      sgi:SGRAN_2017 [2.3.1.12])      => [1.1.1.40]
(shyd:CJD35_14800 [1.2.4.1],    shyd:CJD35_13420 [2.3.1.12])    => [1.1.1.40]
(shyd:CJD35_14800 [1.2.4.1],    shyd:CJD35_19880 [2.3.1.12])    => [1.1.1.40]
(shyd:CJD35_19885 [1.2.4.1],    shyd:CJD35_13420 [2.3.1.12])    => [1.1.1.40]
(shyd:CJD35_19885 [1.2.4.1],    shyd:CJD35_19880 [2.3.1.12])    => [1.1.1.40]
(shz:shn_09760 [1.2.4.1],       shz:shn_09755 [2.3.1.12])       => [1.1.1.40]
(sil:SPO2241 [1.2.4.1],         sil:SPO2242 [2.3.1.12])         => [1.1.1.40]
(sinb:SIDU_07350 [1.2.4.1],     sinb:SIDU_05035 [2.3.1.12])     => [1.1.1.40]
(sino:SS05631_c12270 [1.2.4.1], sino:SS05631_c12280 [2.3.1.12]) => [1.1.1.40]
(sit:TM1040_1078 [1.2.4.1],     sit:TM1040_1077 [2.3.1.12])     => [1.1.1.40]
(six:BSY16_1059 [1.2.4.1],      six:BSY16_1060 [2.3.1.12])      => [1.1.1.40]
(sjp:SJA_C1-14500 [1.2.4.1],    sjp:SJA_C1-20640 [2.3.1.12])    => [1.1.1.40]
(sjp:SJA_C1-14500 [1.2.4.1],    sjp:SJA_C1-22860 [2.2.1.7])     => [1.1.1.40]
(skr:BRX40_13200 [1.2.4.1],     skr:BRX40_18075 [2.3.1.12])     => [1.1.1.40]
(smag:AN936_10165 [1.2.4.1],    smag:AN936_07930 [2.3.1.12])    => [1.1.1.40]
(smd:Smed_1077 [1.2.4.1],       smd:Smed_1078 [2.3.1.12])       => [1.1.1.40]
(sme:SMc01031 [1.2.4.1],        sme:SMc01032 [2.3.1.12])        => [1.1.1.40]
(smy:BJP26_08800 [1.2.4.1],     smy:BJP26_12395 [2.3.1.12])     => [1.1.1.40]
(sno:Snov_1793 [1.2.4.1],       sno:Snov_1792 [2.3.1.12])       => [1.1.1.40]
(span:AWL63_13955 [1.2.4.1],    span:AWL63_12490 [2.3.1.12])    => [1.1.1.40]
(sphb:EP837_00372 [1.2.4.1],    sphb:EP837_02576 [2.3.1.12])    => [1.1.1.40]
(sphc:CVN68_05200 [1.2.4.1],    sphc:CVN68_09945 [2.3.1.12])    => [1.1.1.40]
(sphc:CVN68_05200 [1.2.4.1],    sphc:CVN68_09985 [2.2.1.7])     => [1.1.1.40]
(sphg:AZE99_06590 [1.2.4.1],    sphg:AZE99_07785 [2.3.1.12])    => [1.1.1.40]
(sphi:TS85_06520 [1.2.4.1],     sphi:TS85_12485 [2.2.1.7])      => [1.1.1.40]
(sphi:TS85_06520 [1.2.4.1],     sphi:TS85_15585 [2.3.1.12])     => [1.1.1.40]
(sphj:BSL82_06255 [1.2.4.1],    sphj:BSL82_06245 [2.3.1.12])    => [1.1.1.40]
(sphj:BSL82_06255 [1.2.4.1],    sphj:BSL82_17315 [2.3.1.12])    => [1.1.1.40]
(sphk:SKP52_07200 [1.2.4.1],    sphk:SKP52_03350 [2.3.1.61])    => [1.1.1.40]
(sphk:SKP52_07200 [1.2.4.1],    sphk:SKP52_08850 [2.3.1.12])    => [1.1.1.40]
(sphl:LPB140_07965 [1.2.4.1],   sphl:LPB140_07605 [2.3.1.12])   => [1.1.1.40]
(sphm:G432_13100 [1.2.4.1],     sphm:G432_08190 [2.3.1.12])     => [1.1.1.40]
(sphp:LH20_07705 [1.2.4.1],     sphp:LH20_12785 [2.3.1.12])     => [1.1.1.40]
(sphq:BWQ93_04105 [1.2.4.1],    sphq:BWQ93_07255 [2.3.1.12])    => [1.1.1.40]
(sphr:BSY17_395 [1.2.4.1],      sphr:BSY17_2932 [2.3.1.12])     => [1.1.1.40]
(spht:K426_11970 [1.2.4.1],     spht:K426_14090 [2.3.1.12])     => [1.1.1.40]
(spht:K426_11970 [1.2.4.1],     spht:K426_14385 [2.2.1.7])      => [1.1.1.40]
(spht:K426_11970 [1.2.4.1],     spht:K426_25354 [2.3.1.12])     => [1.1.1.40]
(spht:K426_11970 [1.2.4.1],     spht:K426_28270 [2.3.1.12])     => [1.1.1.40]
(sphy:CHN51_16395 [1.2.4.1],    sphy:CHN51_15230 [2.3.1.12])    => [1.1.1.40]
(spkc:KC8_08660 [1.2.4.1],      spkc:KC8_15420 [2.3.1.12])      => [1.1.1.40]
(splk:AV944_08790 [1.2.4.1],    splk:AV944_08370 [2.2.1.7])     => [1.1.1.40]
(splk:AV944_08790 [1.2.4.1],    splk:AV944_14570 [2.3.1.12])    => [1.1.1.40]
(splm:BXU08_05470 [1.2.4.1],    splm:BXU08_09200 [2.3.1.12])    => [1.1.1.40]
(splm:BXU08_05470 [1.2.4.1],    splm:BXU08_09240 [2.2.1.7])     => [1.1.1.40]
(spmi:K663_06930 [1.2.4.1],     spmi:K663_06115 [2.2.1.7])      => [1.1.1.40]
(spmi:K663_06930 [1.2.4.1],     spmi:K663_09835 [2.3.1.12])     => [1.1.1.40]
(spmi:K663_06930 [1.2.4.1],     spmi:K663_16085 [2.3.1.12])     => [1.1.1.40]
(spse:SULPSESMR1_01103 [1.2.4.1],       spse:SULPSESMR1_01102 [2.3.1.12])       => [1.1.1.40]
(ssan:NX02_15375 [1.2.4.1],     ssan:NX02_14100 [2.2.1.7])      => [1.1.1.40]
(ssan:NX02_15375 [1.2.4.1],     ssan:NX02_20525 [2.3.1.12])     => [1.1.1.40]
(ssy:SLG_18970 [1.2.4.1],       ssy:SLG_36230 [2.3.1.12])       => [1.1.1.40]
(ssy:SLG_23990 [1.2.4.1],       ssy:SLG_36230 [2.3.1.12])       => [1.1.1.40]
(stax:MC45_00715 [1.2.4.1],     stax:MC45_01905 [2.2.1.7])      => [1.1.1.40]
(stax:MC45_00715 [1.2.4.1],     stax:MC45_09385 [2.3.1.12])     => [1.1.1.40]
(ster:AOA14_13235 [1.2.4.1],    ster:AOA14_10505 [2.2.1.7])     => [1.1.1.40]
(ster:AOA14_13235 [1.2.4.1],    ster:AOA14_14760 [2.3.1.12])    => [1.1.1.40]
(suam:BOO69_10560 [1.2.4.1],    suam:BOO69_10570 [2.3.1.12])    => [1.1.1.40]
(swi:Swit_1225 [1.2.4.1],       swi:Swit_1367 [2.3.1.12])       => [1.1.1.40]
(swi:Swit_1225 [1.2.4.1],       swi:Swit_5152 [2.3.1.12])       => [1.1.1.40]
(swi:Swit_5153 [1.2.4.1],       swi:Swit_1367 [2.3.1.12])       => [1.1.1.40]
(swi:Swit_5153 [1.2.4.1],       swi:Swit_5152 [2.3.1.12])       => [1.1.1.40]
(sya:A6768_03935 [1.2.4.1],     sya:A6768_06065 [2.2.1.7])      => [1.1.1.40]
(sya:A6768_03935 [1.2.4.1],     sya:A6768_10825 [2.3.1.12])     => [1.1.1.40]
(syb:TZ53_16805 [1.2.4.1],      syb:TZ53_00420 [2.3.1.12])      => [1.1.1.40]
(syb:TZ53_16805 [1.2.4.1],      syb:TZ53_19895 [2.3.1.12])      => [1.1.1.40]
(syb:TZ53_16805 [1.2.4.1],      syb:TZ53_20205 [2.2.1.7])       => [1.1.1.40]
(thac:CSC3H3_10045 [1.2.4.1],   thac:CSC3H3_10040 [2.3.1.12])   => [1.1.1.40]
(thd:BHV28_08270 [1.2.4.1],     thd:BHV28_08280 [2.3.1.12])     => [1.1.1.40]
(thw:BMG03_12070 [1.2.4.1],     thw:BMG03_12075 [2.3.1.12])     => [1.1.1.40]
(tom:BWR18_05285 [1.2.4.1],     tom:BWR18_05280 [2.3.1.12])     => [1.1.1.40]
(tpro:Ga0080559_TMP606 [1.2.4.1],       tpro:Ga0080559_TMP608 [2.3.1.12])       => [1.1.1.40]
(txi:TH3_10320 [1.2.4.1],       txi:TH3_10315 [2.3.1.12])       => [1.1.1.40]
(vgo:GJW-30_1_02979 [1.2.4.1],  vgo:GJW-30_1_02982 [2.3.1.12])  => [1.1.1.40]
(xau:Xaut_3890 [1.2.4.1],       xau:Xaut_1572 [2.3.1.12])       => [1.1.1.40]
(xau:Xaut_3890 [1.2.4.1],       xau:Xaut_3891 [2.3.1.12])       => [1.1.1.40]
(yan:AYJ57_13670 [1.2.4.1],     yan:AYJ57_13665 [2.3.1.12])     => [1.1.1.40]
(zmo:ZMO1605 [1.2.4.1],         zmo:ZMO0510 [2.3.1.12])         => [1.1.1.40]
(zmo:ZMO1605 [1.2.4.1],         zmo:ZMO1234 [2.2.1.7])          => [1.1.1.40]
(zmo:ZMO1605 [1.2.4.1],         zmo:ZMO1598 [2.2.1.7])          => [1.1.1.40]
(mop:Mesop_2825 [1.2.4.1],      mop:Mesop_5537 [2.2.1.1])       => [1.1.1.40, 5.1.3.1, 5.3.1.6]
(paro:CUV01_02990 [1.2.4.1],    paro:CUV01_06065 [2.2.1.1])     => [1.1.1.40, 5.1.3.1, 5.3.1.6]
(span:AWL63_13955 [1.2.4.1],    span:AWL63_00225 [2.2.1.1])     => [1.1.1.40, 5.1.3.1, 5.3.1.6]
(aace:A0U92_09345 [2.1.3.2],    aace:A0U92_16215 [2.1.3.3])     => [2.1.3.2]
(aak:AA2016_0641 [2.6.1.1],     aak:AA2016_4478 [4.4.1.8])      => [2.1.3.2]
(aak:AA2016_3853 [2.1.3.2],     aak:AA2016_5307 [2.1.3.3])      => [2.1.3.2]
(abg:Asbog_02489 [2.1.3.2],     abg:Asbog_02520 [2.1.3.3])      => [2.1.3.2]
(abs:AZOBR_p1130184 [2.1.3.2],  abs:AZOBR_p1110081 [2.1.3.3])   => [2.1.3.2]
(acr:Acry_0733 [2.1.3.2],       acr:Acry_2540 [2.1.3.3])        => [2.1.3.2]
(agr:AGROH133_05748 [2.1.3.2],  agr:AGROH133_03710 [2.1.3.3])   => [2.1.3.2]
(ahu:A6A40_05495 [2.1.3.2],     ahu:A6A40_01080 [2.1.3.3])      => [2.1.3.2]
(amv:ACMV_11390 [2.1.3.2],      amv:ACMV_28640 [2.1.3.3])       => [2.1.3.2]
(anh:A6F65_00628 [2.6.1.1],     anh:A6F65_00752 [2.6.1.9])      => [2.1.3.2]
(aol:S58_32410 [2.1.3.2],       aol:S58_06810 [2.1.3.3])        => [2.1.3.2]
(apb:SAR116_0613 [2.1.3.2],     apb:SAR116_1883 [2.1.3.3])      => [2.1.3.2]
(apm:HIMB5_00001730 [2.6.1.1],  apm:HIMB5_00000410 [2.6.1.9])   => [2.1.3.2]
(apm:HIMB5_00007360 [2.1.3.2],  apm:HIMB5_00011580 [2.1.3.3])   => [2.1.3.2]
(apom:CPF11_03680 [2.1.3.2],    apom:CPF11_03820 [2.1.3.3])     => [2.1.3.2]
(apt:APA01_07610 [2.1.3.2],     apt:APA01_07290 [2.1.3.3])      => [2.1.3.2]
(aro:B0909_06865 [2.1.3.2],     aro:B0909_11305 [2.1.3.3])      => [2.1.3.2]
(asv:WG31_04290 [2.1.3.2],      asv:WG31_04145 [2.1.3.3])       => [2.1.3.2]
(asz:ASN_388 [2.1.3.2],         asz:ASN_423 [2.1.3.3])          => [2.1.3.2]
(ato:CIW82_10605 [2.1.3.2],     ato:CIW82_10450 [2.1.3.3])      => [2.1.3.2]
(atu:Atu1308 [2.1.3.2],         atu:Atu0429 [2.1.3.3])          => [2.1.3.2]
(aua:M673_11640 [2.1.3.2],      aua:M673_15920 [2.1.3.3])       => [2.1.3.2]
(azc:AZC_2851 [2.1.3.2],        azc:AZC_4027 [2.1.3.3])         => [2.1.3.2]
(azl:AZL_015630 [2.1.3.2],      azl:AZL_004170 [2.1.3.3])       => [2.1.3.2]
(bapi:BBC0122_012900 [2.1.3.2], bapi:BBC0122_002560 [2.1.3.3])  => [2.1.3.2]
(bbk:BARBAKC583_0839 [2.1.3.2], bbk:BARBAKC583_1291 [2.1.3.3])  => [2.1.3.2]
(bbt:BBta_4725 [2.1.3.2],       bbt:BBta_0760 [2.1.3.3])        => [2.1.3.2]
(bcd:BARCL_0788 [2.1.3.2],      bcd:BARCL_0120 [2.1.3.3])       => [2.1.3.2]
(bic:LMTR13_17950 [2.1.3.2],    bic:LMTR13_36225 [2.1.3.3])     => [2.1.3.2]
(bid:Bind_3418 [2.1.3.2],       bid:Bind_0151 [2.1.3.3])        => [2.1.3.2]
(bja:blr5099 [2.1.3.2],         bja:blr1099 [2.1.3.3])          => [2.1.3.2]
(bju:BJ6T_46190 [2.1.3.2],      bju:BJ6T_11290 [2.1.3.3])       => [2.1.3.2]
(blas:BSY18_1271 [2.1.3.2],     blas:BSY18_3543 [2.1.3.3])      => [2.1.3.2]
(bop:AXW83_05525 [2.1.3.2],     bop:AXW83_20595 [2.1.3.3])      => [2.1.3.2]
(bos:BSY19_803 [2.6.1.1],       bos:BSY19_3540 [4.4.1.8])       => [2.1.3.2]
(bra:BRADO4502 [2.1.3.2],       bra:BRADO6778 [2.1.3.3])        => [2.1.3.2]
(brc:BCCGELA001_21630 [2.1.3.2],brc:BCCGELA001_34135 [2.1.3.3]) => [2.1.3.2]
(brk:CWS35_27085 [2.1.3.2],     brk:CWS35_10260 [2.1.3.3])      => [2.1.3.2]
(bro:BRAD285_4271 [2.1.3.2],    bro:BRAD285_6924 [2.1.3.3])     => [2.1.3.2]
(brs:S23_31190 [2.1.3.2],       brs:S23_67200 [2.1.3.3])        => [2.1.3.2]
(bvr:BVIR_1655 [2.1.3.2],       bvr:BVIR_3201 [2.1.3.3])        => [2.1.3.2]
(bvv:BHK69_17075 [2.6.1.1],     bvv:BHK69_11845 [4.4.1.8])      => [2.1.3.2]
(bvv:BHK69_17405 [2.6.1.1],     bvv:BHK69_10215 [2.6.1.9])      => [2.1.3.2]
(bvv:BHK69_17960 [2.1.3.2],     bvv:BHK69_05425 [2.1.3.3])      => [2.1.3.2]
(bvv:BHK69_21550 [2.6.1.1],     bvv:BHK69_11845 [4.4.1.8])      => [2.1.3.2]
(cdq:BOQ54_10620 [2.1.3.2],     cdq:BOQ54_02410 [2.1.3.3])      => [2.1.3.2]
(cmag:CBW24_15855 [2.6.1.1],    cmag:CBW24_15140 [4.4.1.8])     => [2.1.3.2]
(cmag:CBW24_15855 [2.6.1.1],    cmag:CBW24_17710 [2.6.1.9])     => [2.1.3.2]
(cmb:CSW64_09750 [2.1.3.2],     cmb:CSW64_16805 [2.1.3.3])      => [2.1.3.2]
(deq:XM25_09185 [2.1.3.2],      deq:XM25_22360 [2.1.3.3])       => [2.1.3.2]
(egn:BMF35_a0322 [2.1.3.2],     egn:BMF35_a0814 [2.1.3.3])      => [2.1.3.2]
(esj:SJ05684_c09700 [2.1.3.2],  esj:SJ05684_c01260 [2.1.3.3])   => [2.1.3.2]
(fil:BN1229_v1_0353 [2.1.3.2],  fil:BN1229_v1_1325 [2.1.3.3])   => [2.1.3.2]
(gal:A0U94_13890 [2.1.3.2],     gal:A0U94_13735 [2.1.3.3])      => [2.1.3.2]
(gbe:GbCGDNIH1_0809 [2.1.3.2],  gbe:GbCGDNIH1_2273 [2.1.3.3])   => [2.1.3.2]
(gdi:GDI0049 [2.1.3.2],         gdi:GDI1463 [2.1.3.3])          => [2.1.3.2]
(gox:GOX1267 [2.1.3.2],         gox:GOX1236 [2.1.3.3])          => [2.1.3.2]
(gxl:H845_2485 [2.1.3.2],       gxl:H845_2511 [2.1.3.3])        => [2.1.3.2]
(gxy:GLX_12460 [2.1.3.2],       gxy:GLX_12730 [2.1.3.3])        => [2.1.3.2]
(hat:RC74_07005 [2.6.1.1],      hat:RC74_08240 [4.4.1.8])       => [2.1.3.2]
(hbc:AEM38_09630 [2.1.3.2],     hbc:AEM38_02735 [2.1.3.3])      => [2.1.3.2]
(hdi:HDIA_2920 [2.1.3.2],       hdi:HDIA_0565 [2.1.3.3])        => [2.1.3.2]
(hdi:HDIA_3464 [2.6.1.1],       hdi:HDIA_4357 [2.6.1.9])        => [2.1.3.2]
(hdn:Hden_0636 [2.1.3.2],       hdn:Hden_0020 [2.1.3.3])        => [2.1.3.2]
(hne:HNE_2302 [2.1.3.2],        hne:HNE_0592 [2.1.3.3])         => [2.1.3.2]
(hne:HNE_2968 [2.6.1.1],        hne:HNE_1125 [2.6.1.9])         => [2.1.3.2]
(hoe:IMCC20628_02307 [2.1.3.2], hoe:IMCC20628_03650 [2.1.3.3])  => [2.1.3.2]
(kba:A0U89_11590 [2.1.3.2],     kba:A0U89_11740 [2.1.3.3])      => [2.1.3.2]
(keu:S101446_01792 [2.1.3.2],   keu:S101446_01820 [2.1.3.3])    => [2.1.3.2]
(kna:B0W47_06650 [2.1.3.2],     kna:B0W47_06785 [2.1.3.3])      => [2.1.3.2]
(kro:BVG79_00956 [2.6.1.1],     kro:BVG79_00430 [4.4.1.8])      => [2.1.3.2]
(kvu:EIO_1890 [2.6.1.1],        kvu:EIO_1794 [4.4.1.8])         => [2.1.3.2]
(lar:lam_382 [2.1.3.2],         lar:lam_062 [2.1.3.3])          => [2.1.3.2]
(lcc:B488_09550 [2.1.3.2],      lcc:B488_01490 [2.1.3.3])       => [2.1.3.2]
(magn:WV31_17010 [2.1.3.2],     magn:WV31_14345 [2.1.3.3])      => [2.1.3.2]
(magq:MGMAQ_0620 [2.1.3.2],     magq:MGMAQ_3518 [2.1.3.3])      => [2.1.3.2]
(magq:MGMAQ_3208 [2.6.1.1],     magq:MGMAQ_2975 [2.6.1.9])      => [2.1.3.2]
(magx:XM1_1851 [2.1.3.2],       magx:XM1_1245 [2.1.3.3])        => [2.1.3.2]
(mam:Mesau_03989 [2.1.3.2],     mam:Mesau_06027 [2.1.3.3])      => [2.1.3.2]
(mamo:A6B35_18600 [2.1.3.2],    mamo:A6B35_07965 [2.1.3.3])     => [2.1.3.2]
(mcg:GL4_2216 [2.1.3.2],        mcg:GL4_0837 [2.1.3.3])         => [2.1.3.2]
(mci:Mesci_4015 [2.1.3.2],      mci:Mesci_5986 [2.1.3.3])       => [2.1.3.2]
(mes:Meso_2107 [2.6.1.1],       mes:Meso_3736 [4.4.1.8])        => [2.1.3.2]
(mes:Meso_3626 [2.6.1.1],       mes:Meso_3736 [4.4.1.8])        => [2.1.3.2]
(meso:BSQ44_13150 [2.1.3.2],    meso:BSQ44_20220 [2.1.3.3])     => [2.1.3.2]
(mesw:A9K65_022370 [2.1.3.2],   mesw:A9K65_032115 [2.1.3.3])    => [2.1.3.2]
(met:M446_4349 [2.1.3.2],       met:M446_6535 [2.1.3.3])        => [2.1.3.2]
(meta:Y590_16200 [2.1.3.2],     meta:Y590_20310 [2.1.3.3])      => [2.1.3.2]
(mex:Mext_3312 [2.1.3.2],       mex:Mext_4076 [2.1.3.3])        => [2.1.3.2]
(mgy:MGMSRv2__0292 [2.1.3.2],   mgy:MGMSRv2__2971 [2.1.3.3])    => [2.1.3.2]
(mln:A9174_22265 [2.1.3.2],     mln:A9174_33375 [2.1.3.3])      => [2.1.3.2]
(mlo:mlr0686 [2.1.3.2],         mlo:mlr5647 [2.1.3.3])          => [2.1.3.2]
(mno:Mnod_3310 [2.1.3.2],       mno:Mnod_7456 [2.1.3.3])        => [2.1.3.2]
(mop:Mesop_4222 [2.1.3.2],      mop:Mesop_6633 [2.1.3.3])       => [2.1.3.2]
(mor:MOC_1226 [2.1.3.2],        mor:MOC_2743 [2.1.3.3])         => [2.1.3.2]
(mphy:MCBMB27_00603 [2.1.3.2],  mphy:MCBMB27_01933 [2.1.3.3])   => [2.1.3.2]
(mpo:Mpop_3512 [2.1.3.2],       mpo:Mpop_4557 [2.1.3.3])        => [2.1.3.2]
(mrd:Mrad2831_1010 [2.1.3.2],   mrd:Mrad2831_2317 [2.1.3.3])    => [2.1.3.2]
(mtw:CQW49_10330 [2.1.3.2],     mtw:CQW49_13055 [2.1.3.3])      => [2.1.3.2]
(mza:B2G69_24115 [2.1.3.2],     mza:B2G69_02290 [2.1.3.3])      => [2.1.3.2]
(nao:Y958_18085 [2.1.3.2],      nao:Y958_12640 [2.1.3.3])       => [2.1.3.2]
(nar:Saro_3061 [2.1.3.2],       nar:Saro_3140 [2.1.3.3])        => [2.1.3.2]
(nch:A0U93_01120 [2.1.3.2],     nch:A0U93_08020 [2.1.3.3])      => [2.1.3.2]
(ngl:RG1141_CH12190 [2.1.3.2],  ngl:RG1141_CH01240 [2.1.3.3])   => [2.1.3.2]
(nha:Nham_2282 [2.1.3.2],       nha:Nham_0643 [2.1.3.3])        => [2.1.3.2]
(nwi:Nwi_2007 [2.1.3.2],        nwi:Nwi_0514 [2.1.3.3])         => [2.1.3.2]
(oca:OCAR_5788 [2.1.3.2],       oca:OCAR_4655 [2.1.3.3])        => [2.1.3.2]
(paru:CYR75_02630 [2.6.1.1],    paru:CYR75_03070 [2.6.1.9])     => [2.1.3.2]
(pgd:Gal_01277 [2.6.1.1],       pgd:Gal_00220 [4.4.1.8])        => [2.1.3.2]
(pgv:SL003B_1850 [2.1.3.2],     pgv:SL003B_3272 [2.1.3.3])      => [2.1.3.2]
(pla:Plav_2836 [2.1.3.2],       pla:Plav_0403 [2.1.3.3])        => [2.1.3.2]
(ppic:PhaeoP14_01936 [2.6.1.1], ppic:PhaeoP14_02967 [4.4.1.8])  => [2.1.3.2]
(psf:PSE_3779 [2.1.3.2],        psf:PSE_1697 [2.1.3.3])         => [2.1.3.2]
(pub:SAR11_0080 [2.6.1.1],      pub:SAR11_0216 [2.6.1.9])       => [2.1.3.2]
(pzh:CX676_01205 [2.6.1.1],     pzh:CX676_11515 [4.4.1.8])      => [2.1.3.2]
(rdi:CMV14_11955 [2.1.3.2],     rdi:CMV14_07710 [2.1.3.3])      => [2.1.3.2]
(red:roselon_00687 [2.1.3.2],   red:roselon_01922 [2.1.3.3])    => [2.1.3.2]
(rga:RGR602_CH01510 [2.1.3.2],  rga:RGR602_CH00549 [2.1.3.3])   => [2.1.3.2]
(rgi:RGI145_07825 [2.1.3.2],    rgi:RGI145_04760 [2.1.3.3])     => [2.1.3.2]
(rgi:RGI145_22060 [2.6.1.1],    rgi:RGI145_01290 [2.6.1.9])     => [2.1.3.2]
(rhl:LPU83_1698 [2.1.3.2],      rhl:LPU83_0649 [2.1.3.3])       => [2.1.3.2]
(rht:NT26_1305 [2.1.3.2],       rht:NT26_0083 [2.1.3.3])        => [2.1.3.2]
(rhz:RHPLAN_40050 [2.1.3.2],    rhz:RHPLAN_64680 [2.1.3.3])     => [2.1.3.2]
(rir:BN877_I1288 [2.1.3.2],     rir:BN877_I0433 [2.1.3.3])      => [2.1.3.2]
(ros:CTJ15_09505 [2.1.3.2],     ros:CTJ15_12635 [2.1.3.3])      => [2.1.3.2]
(rpm:RSPPHO_02455 [2.1.3.2],    rpm:RSPPHO_03098 [2.1.3.3])     => [2.1.3.2]
(rru:Rru_A3190 [2.1.3.2],       rru:Rru_A3276 [2.1.3.3])        => [2.1.3.2]
(sagu:CDO87_07195 [2.6.1.1],    sagu:CDO87_06360 [4.4.1.8])     => [2.1.3.2]
(sal:Sala_0924 [2.1.3.2],       sal:Sala_1358 [2.1.3.3])        => [2.1.3.2]
(same:SAMCFNEI73_pC0840 [2.6.1.1],      same:SAMCFNEI73_Ch2931 [4.4.1.8])       => [2.1.3.2]
(sch:Sphch_2981 [2.1.3.2],      sch:Sphch_2663 [2.1.3.3])       => [2.1.3.2]
(sclo:SCLO_1029760 [2.1.3.2],   sclo:SCLO_1016020 [2.1.3.3])    => [2.1.3.2]
(sgi:SGRAN_2628 [2.1.3.2],      sgi:SGRAN_2116 [2.1.3.3])       => [2.1.3.2]
(shyd:CJD35_10725 [2.1.3.2],    shyd:CJD35_03045 [2.1.3.3])     => [2.1.3.2]
(sil:SPO0584 [2.6.1.1],         sil:SPO1468 [2.6.1.9])          => [2.1.3.2]
(sil:SPO0584 [2.6.1.1],         sil:SPO3177 [2.6.1.9])          => [2.1.3.2]
(sil:SPO0584 [2.6.1.1],         sil:SPO3220 [4.4.1.8])          => [2.1.3.2]
(sinb:SIDU_01275 [2.1.3.2],     sinb:SIDU_12520 [2.1.3.3])      => [2.1.3.2]
(six:BSY16_1510 [2.1.3.2],      six:BSY16_2700 [2.1.3.3])       => [2.1.3.2]
(sjp:SJA_C1-27100 [2.1.3.2],    sjp:SJA_C1-30650 [2.1.3.3])     => [2.1.3.2]
(sme:SMc01360 [2.1.3.2],        sme:SMc02137 [2.1.3.3])         => [2.1.3.2]
(sno:Snov_1518 [2.1.3.2],       sno:Snov_4491 [2.1.3.3])        => [2.1.3.2]
(sphb:EP837_02230 [2.1.3.2],    sphb:EP837_02025 [2.1.3.3])     => [2.1.3.2]
(sphd:HY78_23655 [2.1.3.2],     sphd:HY78_19530 [2.1.3.3])      => [2.1.3.2]
(sphj:BSL82_03985 [2.1.3.2],    sphj:BSL82_03265 [2.1.3.3])     => [2.1.3.2]
(sphk:SKP52_12045 [2.1.3.2],    sphk:SKP52_07715 [2.1.3.3])     => [2.1.3.2]
(sphm:G432_00710 [2.1.3.2],     sphm:G432_02100 [2.1.3.3])      => [2.1.3.2]
(sphr:BSY17_2353 [2.1.3.2],     sphr:BSY17_821 [2.1.3.3])       => [2.1.3.2]
(spht:K426_16330 [2.1.3.2],     spht:K426_05450 [2.1.3.3])      => [2.1.3.2]
(spkc:KC8_01860 [2.1.3.2],      spkc:KC8_07830 [2.1.3.3])       => [2.1.3.2]
(splk:AV944_14140 [2.1.3.2],    splk:AV944_15640 [2.1.3.3])     => [2.1.3.2]
(splm:BXU08_01330 [2.1.3.2],    splm:BXU08_09540 [2.1.3.3])     => [2.1.3.2]
(ssan:NX02_05020 [2.1.3.2],     ssan:NX02_16150 [2.1.3.3])      => [2.1.3.2]
(ssy:SLG_20620 [2.1.3.2],       ssy:SLG_34380 [2.1.3.3])        => [2.1.3.2]
(stax:MC45_08595 [2.1.3.2],     stax:MC45_09110 [2.1.3.3])      => [2.1.3.2]
(ster:AOA14_16510 [2.1.3.2],    ster:AOA14_17110 [2.1.3.3])     => [2.1.3.2]
(suam:BOO69_18100 [2.6.1.1],    suam:BOO69_01585 [4.4.1.8])     => [2.1.3.2]
(swi:Swit_0602 [2.1.3.2],       swi:Swit_1408 [2.1.3.3])        => [2.1.3.2]
(sya:A6768_14705 [2.1.3.2],     sya:A6768_16035 [2.1.3.3])      => [2.1.3.2]
(syb:TZ53_14000 [2.1.3.2],      syb:TZ53_02415 [2.1.3.3])       => [2.1.3.2]
(thac:CSC3H3_08600 [2.1.3.2],   thac:CSC3H3_00195 [2.1.3.3])    => [2.1.3.2]
(thal:A1OE_1459 [2.1.3.2],      thal:A1OE_555 [2.1.3.3])        => [2.1.3.2]
(thd:BHV28_06860 [2.1.3.2],     thd:BHV28_11810 [2.1.3.3])      => [2.1.3.2]
(txi:TH3_08955 [2.1.3.2],       txi:TH3_00210 [2.1.3.3])        => [2.1.3.2]
(txi:TH3_16445 [2.6.1.1],       txi:TH3_17770 [2.6.1.9])        => [2.1.3.2]
(zmo:ZMO0791 [2.1.3.2],         zmo:ZMO0409 [2.1.3.3])          => [2.1.3.2]
(aace:A0U92_13605 [4.1.3.-],    aace:A0U92_13610 [5.3.1.16])    => [2.4.2.-]
(aay:WYH_03064 [4.1.3.-],       aay:WYH_03062 [5.3.1.16])       => [2.4.2.-]
(abg:Asbog_01382 [4.1.3.-],     abg:Asbog_01381 [5.3.1.16])     => [2.4.2.-]
(abs:AZOBR_10373 [4.1.3.-],     abs:AZOBR_10372 [5.3.1.16])     => [2.4.2.-]
(acr:Acry_1417 [4.1.3.-],       acr:Acry_1416 [5.3.1.16])       => [2.4.2.-]
(aht:ANTHELSMS3_04067 [4.1.3.-],aht:ANTHELSMS3_04065 [5.3.1.16])=> [2.4.2.-]
(ahu:A6A40_12250 [4.1.3.-],     ahu:A6A40_12245 [5.3.1.16])     => [2.4.2.-]
(amv:ACMV_14640 [4.1.3.-],      amv:ACMV_14630 [5.3.1.16])      => [2.4.2.-]
(apm:HIMB5_00013870 [4.1.3.-],  apm:HIMB5_00013860 [5.3.1.16])  => [2.4.2.-]
(apom:CPF11_07530 [4.1.3.-],    apom:CPF11_07535 [5.3.1.16])    => [2.4.2.-]
(apt:APA01_26550 [4.1.3.-],     apt:APA01_26540 [5.3.1.16])     => [2.4.2.-]
(asv:WG31_13100 [4.1.3.-],      asv:WG31_13095 [5.3.1.16])      => [2.4.2.-]
(asz:ASN_1651 [4.1.3.-],        asz:ASN_1652 [5.3.1.16])        => [2.4.2.-]
(ati:AL072_04630 [4.1.3.-],     ati:AL072_04625 [5.3.1.16])     => [2.4.2.-]
(ato:CIW82_03890 [4.1.3.-],     ato:CIW82_03885 [5.3.1.16])     => [2.4.2.-]
(atu:Atu0039 [4.1.3.-],         atu:Atu0040 [5.3.1.16])         => [2.4.2.-]
(aua:M673_01985 [4.1.3.-],      aua:M673_01975 [5.3.1.16])      => [2.4.2.-]
(avi:Avi_0037 [4.1.3.-],        avi:Avi_0036 [5.3.1.16])        => [2.4.2.-]
(azc:AZC_4498 [4.1.3.-],        azc:AZC_4499 [5.3.1.16])        => [2.4.2.-]
(azl:AZL_028780 [4.1.3.-],      azl:AZL_028790 [5.3.1.16])      => [2.4.2.-]
(bapi:BBC0122_000960 [4.1.3.-], bapi:BBC0122_000970 [5.3.1.16]) => [2.4.2.-]
(bcet:V910_102056 [4.1.3.-],    bcet:V910_102057 [5.3.1.16])    => [2.4.2.-]
(bcs:BCAN_A2131 [4.1.3.-],      bcs:BCAN_A2130 [5.3.1.16])      => [2.4.2.-]
(bic:LMTR13_00085 [4.1.3.-],    bic:LMTR13_00080 [5.3.1.16])    => [2.4.2.-]
(bid:Bind_0243 [4.1.3.-],       bid:Bind_0246 [5.3.1.16])       => [2.4.2.-]
(bja:blr0654 [4.1.3.-],         bja:blr0653 [5.3.1.16])         => [2.4.2.-]
(bme:BMEI2041 [4.1.3.-],        bme:BMEI2042 [5.3.1.16])        => [2.4.2.-]
(bmf:BAB1_2086 [4.1.3.-],       bmf:BAB1_2085 [5.3.1.16])       => [2.4.2.-]
(bmr:BMI_I2107 [4.1.3.-],       bmr:BMI_I2106 [5.3.1.16])       => [2.4.2.-]
(bms:BR2085 [4.1.3.-],          bms:BR2084 [5.3.1.16])          => [2.4.2.-]
(bov:BOV_2005 [4.1.3.-],        bov:BOV_2004 [5.3.1.16])        => [2.4.2.-]
(bpp:BPI_I2143 [4.1.3.-],       bpp:BPI_I2142 [5.3.1.16])       => [2.4.2.-]
(brad:BF49_0189 [4.1.3.-],      brad:BF49_0190 [5.3.1.16])      => [2.4.2.-]
(bvl:BF3285c1_0776 [4.1.3.-],   bvl:BF3285c1_0775 [5.3.1.16])   => [2.4.2.-]
(ccr:CC_3737 [4.1.3.-],         ccr:CC_3736 [5.3.1.16])         => [2.4.2.-]
(chq:AQ619_17935 [4.1.3.-],     chq:AQ619_17940 [5.3.1.16])     => [2.4.2.-]
(cid:P73_3233 [4.1.3.-],        cid:P73_3232 [5.3.1.16])        => [2.4.2.-]
(cmag:CBW24_03755 [4.1.3.-],    cmag:CBW24_04905 [5.3.1.16])    => [2.4.2.-]
(cmb:CSW64_20760 [4.1.3.-],     cmb:CSW64_20765 [5.3.1.16])     => [2.4.2.-]
(con:TQ29_05850 [4.1.3.-],      con:TQ29_05855 [5.3.1.16])      => [2.4.2.-]
(deq:XM25_17710 [4.1.3.-],      deq:XM25_17700 [5.3.1.16])      => [2.4.2.-]
(don:BSK21_03860 [4.1.3.-],     don:BSK21_04160 [5.3.1.16])     => [2.4.2.-]
(dsh:Dshi_2576 [4.1.3.-],       dsh:Dshi_2578 [5.3.1.16])       => [2.4.2.-]
(efv:CHH26_03115 [4.1.3.-],     efv:CHH26_03110 [5.3.1.16])     => [2.4.2.-]
(esj:SJ05684_c34190 [4.1.3.-],  esj:SJ05684_c34200 [5.3.1.16])  => [2.4.2.-]
(gal:A0U94_09400 [4.1.3.-],     gal:A0U94_09395 [5.3.1.16])     => [2.4.2.-]
(gbe:GbCGDNIH1_2230 [4.1.3.-],  gbe:GbCGDNIH1_2231 [5.3.1.16])  => [2.4.2.-]
(gdi:GDI0069 [4.1.3.-],         gdi:GDI0070 [5.3.1.16])         => [2.4.2.-]
(gox:GOX0483 [4.1.3.-],         gox:GOX0482 [5.3.1.16])         => [2.4.2.-]
(gxl:H845_2478 [4.1.3.-],       gxl:H845_2477 [5.3.1.16])       => [2.4.2.-]
(gxy:GLX_12390 [4.1.3.-],       gxy:GLX_12380 [5.3.1.16])       => [2.4.2.-]
(hba:Hbal_3138 [4.1.3.-],       hba:Hbal_3135 [5.3.1.16])       => [2.4.2.-]
(hbc:AEM38_15740 [4.1.3.-],     hbc:AEM38_15735 [5.3.1.16])     => [2.4.2.-]
(hdn:Hden_3358 [4.1.3.-],       hdn:Hden_3354 [5.3.1.16])       => [2.4.2.-]
(hne:HNE_0066 [4.1.3.-],        hne:HNE_0070 [5.3.1.16])        => [2.4.2.-]
(hni:W911_00785 [4.1.3.-],      hni:W911_00790 [5.3.1.16])      => [2.4.2.-]
(jan:Jann_2795 [4.1.3.-],       jan:Jann_2792 [5.3.1.16])       => [2.4.2.-]
(kba:A0U89_05695 [4.1.3.-],     kba:A0U89_05700 [5.3.1.16])     => [2.4.2.-]
(keu:S101446_01785 [4.1.3.-],   keu:S101446_01784 [5.3.1.16])   => [2.4.2.-]
(kna:B0W47_06610 [4.1.3.-],     kna:B0W47_06605 [5.3.1.16])     => [2.4.2.-]
(kro:BVG79_02005 [4.1.3.-],     kro:BVG79_02004 [5.3.1.16])     => [2.4.2.-]
(kvu:EIO_2330 [4.1.3.-],        kvu:EIO_2329 [5.3.1.16])        => [2.4.2.-]
(labr:CHH27_19765 [4.1.3.-],    labr:CHH27_19760 [5.3.1.16])    => [2.4.2.-]
(lagg:B0E33_12120 [4.1.3.-],    lagg:B0E33_12125 [5.3.1.16])    => [2.4.2.-]
(lap:ACP90_00620 [4.1.3.-],     lap:ACP90_00625 [5.3.1.16])     => [2.4.2.-]
(lcc:B488_13520 [4.1.3.-],      lcc:B488_13510 [5.3.1.16])      => [2.4.2.-]
(lvs:LOKVESSMR4R_00974 [4.1.3.-],       lvs:LOKVESSMR4R_00975 [5.3.1.16])       => [2.4.2.-]
(mag:amb4531 [4.1.3.-],         mag:amb4532 [5.3.1.16])         => [2.4.2.-]
(magn:WV31_12385 [4.1.3.-],     magn:WV31_12390 [5.3.1.16])     => [2.4.2.-]
(magq:MGMAQ_3837 [4.1.3.-],     magq:MGMAQ_3836 [5.3.1.16])     => [2.4.2.-]
(magx:XM1_0814 [4.1.3.-],       magx:XM1_0815 [5.3.1.16])       => [2.4.2.-]
(malg:MALG_00137 [4.1.3.-],     malg:MALG_00138 [5.3.1.16])     => [2.4.2.-]
(mam:Mesau_00627 [4.1.3.-],     mam:Mesau_00625 [5.3.1.16])     => [2.4.2.-]
(maqu:Maq22A_1p33375 [4.1.3.-], maqu:Maq22A_1p33365 [5.3.1.16]) => [2.4.2.-]
(mcg:GL4_0299 [4.1.3.-],        mcg:GL4_0301 [5.3.1.16])        => [2.4.2.-]
(mci:Mesci_0476 [4.1.3.-],      mci:Mesci_0478 [5.3.1.16])      => [2.4.2.-]
(meso:BSQ44_02025 [4.1.3.-],    meso:BSQ44_02015 [5.3.1.16])    => [2.4.2.-]
(mesw:A9K65_002385 [4.1.3.-],   mesw:A9K65_002395 [5.3.1.16])   => [2.4.2.-]
(met:M446_6790 [4.1.3.-],       met:M446_6791 [5.3.1.16])       => [2.4.2.-]
(mgm:Mmc1_3156 [4.1.3.-],       mgm:Mmc1_3155 [5.3.1.16])       => [2.4.2.-]
(mgy:MGMSRv2__3491 [4.1.3.-],   mgy:MGMSRv2__3492 [5.3.1.16])   => [2.4.2.-]
(mln:A9174_02290 [4.1.3.-],     mln:A9174_02300 [5.3.1.16])     => [2.4.2.-]
(mlo:mlr5016 [4.1.3.-],         mlo:mlr5014 [5.3.1.16])         => [2.4.2.-]
(mno:Mnod_7529 [4.1.3.-],       mno:Mnod_7530 [5.3.1.16])       => [2.4.2.-]
(mphy:MCBMB27_05651 [4.1.3.-],  mphy:MCBMB27_05650 [5.3.1.16])  => [2.4.2.-]
(mpo:Mpop_2483 [4.1.3.-],       mpo:Mpop_2481 [5.3.1.16])       => [2.4.2.-]
(msc:BN69_0826 [4.1.3.-],       msc:BN69_0827 [5.3.1.16])       => [2.4.2.-]
(nao:Y958_00600 [4.1.3.-],      nao:Y958_00605 [5.3.1.16])      => [2.4.2.-]
(nch:A0U93_01905 [4.1.3.-],     nch:A0U93_01910 [5.3.1.16])     => [2.4.2.-]
(nha:Nham_0126 [4.1.3.-],       nha:Nham_0125 [5.3.1.16])       => [2.4.2.-]
(nre:BES08_17140 [4.1.3.-],     nre:BES08_17130 [5.3.1.16])     => [2.4.2.-]
(nwi:Nwi_0122 [4.1.3.-],        nwi:Nwi_0123 [5.3.1.16])        => [2.4.2.-]
(oan:Oant_0834 [4.1.3.-],       oan:Oant_0835 [5.3.1.16])       => [2.4.2.-]
(oca:OCAR_4399 [4.1.3.-],       oca:OCAR_4398 [5.3.1.16])       => [2.4.2.-]
(och:CES85_2607 [4.1.3.-],      och:CES85_2606 [5.3.1.16])      => [2.4.2.-]
(ops:A8A54_17550 [4.1.3.-],     ops:A8A54_17545 [5.3.1.16])     => [2.4.2.-]
(paby:Ga0080574_TMP1305 [4.1.3.-],      paby:Ga0080574_TMP1334 [5.3.1.16])      => [2.4.2.-]
(pami:JCM7686_0889 [4.1.3.-],   pami:JCM7686_0891 [5.3.1.16])   => [2.4.2.-]
(paro:CUV01_15625 [4.1.3.-],    paro:CUV01_15640 [5.3.1.16])    => [2.4.2.-]
(paru:CYR75_00985 [4.1.3.-],    paru:CYR75_00995 [5.3.1.16])    => [2.4.2.-]
(pcon:B0A89_00105 [4.1.3.-],    pcon:B0A89_13745 [5.3.1.16])    => [2.4.2.-]
(pde:Pden_1887 [4.1.3.-],       pde:Pden_1886 [5.3.1.16])       => [2.4.2.-]
(pel:SAR11G3_00409 [4.1.3.-],   pel:SAR11G3_00408 [5.3.1.16])   => [2.4.2.-]
(pga:PGA1_c09240 [4.1.3.-],     pga:PGA1_c09270 [5.3.1.16])     => [2.4.2.-]
(pgd:Gal_02567 [4.1.3.-],       pgd:Gal_02564 [5.3.1.16])       => [2.4.2.-]
(pgv:SL003B_0013 [4.1.3.-],     pgv:SL003B_0012 [5.3.1.16])     => [2.4.2.-]
(php:PhaeoP97_00889 [4.1.3.-],  php:PhaeoP97_00893 [5.3.1.16])  => [2.4.2.-]
(pht:BLM14_18785 [4.1.3.-],     pht:BLM14_18790 [5.3.1.16])     => [2.4.2.-]
(pla:Plav_1233 [4.1.3.-],       pla:Plav_1234 [5.3.1.16])       => [2.4.2.-]
(pphr:APZ00_04685 [4.1.3.-],    pphr:APZ00_04690 [5.3.1.16])    => [2.4.2.-]
(ppic:PhaeoP14_00844 [4.1.3.-], ppic:PhaeoP14_00847 [5.3.1.16]) => [2.4.2.-]
(psf:PSE_0556 [4.1.3.-],        psf:PSE_0557 [5.3.1.16])        => [2.4.2.-]
(psin:CAK95_07965 [4.1.3.-],    psin:CAK95_07970 [5.3.1.16])    => [2.4.2.-]
(pub:SAR11_0329 [4.1.3.-],      pub:SAR11_0330 [5.3.1.16])      => [2.4.2.-]
(pye:A6J80_06335 [4.1.3.-],     pye:A6J80_06330 [5.3.1.16])     => [2.4.2.-]
(pzh:CX676_03395 [4.1.3.-],     pzh:CX676_03405 [5.3.1.16])     => [2.4.2.-]
(pzu:PHZ_c0043 [4.1.3.-],       pzu:PHZ_c0042 [5.3.1.16])       => [2.4.2.-]
(rbg:BG454_15835 [4.1.3.-],     rbg:BG454_13580 [5.3.1.16])     => [2.4.2.-]
(rbm:TEF_21450 [4.1.3.-],       rbm:TEF_21445 [5.3.1.16])       => [2.4.2.-]
(rce:RC1_3299 [4.1.3.-],        rce:RC1_3298 [5.3.1.16])        => [2.4.2.-]
(rcp:RCAP_rcc01153 [4.1.3.-],   rcp:RCAP_rcc01154 [5.3.1.16])   => [2.4.2.-]
(rde:RD1_3561 [4.1.3.-],        rde:RD1_3560 [5.3.1.16])        => [2.4.2.-]
(rdi:CMV14_01430 [4.1.3.-],     rdi:CMV14_01425 [5.3.1.16])     => [2.4.2.-]
(rhc:RGUI_3765 [4.1.3.-],       rhc:RGUI_3766 [5.3.1.16])       => [2.4.2.-]
(rhm:B5V46_12225 [4.1.3.-],     rhm:B5V46_12230 [5.3.1.16])     => [2.4.2.-]
(rhn:AMJ98_CH00042 [4.1.3.-],   rhn:AMJ98_CH00043 [5.3.1.16])   => [2.4.2.-]
(rhp:LPB142_13045 [4.1.3.-],    rhp:LPB142_13040 [5.3.1.16])    => [2.4.2.-]
(rht:NT26_3871 [4.1.3.-],       rht:NT26_3872 [5.3.1.16])       => [2.4.2.-]
(rhx:AMK02_CH00042 [4.1.3.-],   rhx:AMK02_CH00043 [5.3.1.16])   => [2.4.2.-]
(rle:RL0042 [4.1.3.-],          rle:RL0043 [5.3.1.16])          => [2.4.2.-]
(rli:RLO149_c026220 [4.1.3.-],  rli:RLO149_c026210 [5.3.1.16])  => [2.4.2.-]
(rmb:K529_003635 [4.1.3.-],     rmb:K529_003650 [5.3.1.16])     => [2.4.2.-]
(rmm:ROSMUCSMR3_00832 [4.1.3.-],rmm:ROSMUCSMR3_00834 [5.3.1.16])=> [2.4.2.-]
(rpha:AMC79_CH00044 [4.1.3.-],  rpha:AMC79_CH00045 [5.3.1.16])  => [2.4.2.-]
(rsp:RSP_2242 [4.1.3.-],        rsp:RSP_2243 [5.3.1.16])        => [2.4.2.-]
(rsu:NHU_01297 [4.1.3.-],       rsu:NHU_01296 [5.3.1.16])       => [2.4.2.-]
(rva:Rvan_2397 [4.1.3.-],       rva:Rvan_2017 [5.3.1.16])       => [2.4.2.-]
(sagu:CDO87_01905 [4.1.3.-],    sagu:CDO87_01890 [5.3.1.16])    => [2.4.2.-]
(same:SAMCFNEI73_Ch0051 [4.1.3.-],      same:SAMCFNEI73_Ch0052 [5.3.1.16])      => [2.4.2.-]
(sil:SPO1156 [4.1.3.-],         sil:SPO1158 [5.3.1.16])         => [2.4.2.-]
(sit:TM1040_2041 [4.1.3.-],     sit:TM1040_2039 [5.3.1.16])     => [2.4.2.-]
(smd:Smed_3259 [4.1.3.-],       smd:Smed_3260 [5.3.1.16])       => [2.4.2.-]
(sme:SMc02569 [4.1.3.-],        sme:SMc02570 [5.3.1.16])        => [2.4.2.-]
(sno:Snov_3830 [4.1.3.-],       sno:Snov_3829 [5.3.1.16])       => [2.4.2.-]
(sphd:HY78_11910 [4.1.3.-],     sphd:HY78_11915 [5.3.1.16])     => [2.4.2.-]
(sphj:BSL82_06980 [4.1.3.-],    sphj:BSL82_06975 [5.3.1.16])    => [2.4.2.-]
(sphm:G432_10435 [4.1.3.-],     sphm:G432_10430 [5.3.1.16])     => [2.4.2.-]
(sphq:BWQ93_14380 [4.1.3.-],    sphq:BWQ93_14375 [5.3.1.16])    => [2.4.2.-]
(sphy:CHN51_10005 [4.1.3.-],    sphy:CHN51_10000 [5.3.1.16])    => [2.4.2.-]
(spkc:KC8_14260 [4.1.3.-],      spkc:KC8_14255 [5.3.1.16])      => [2.4.2.-]
(splm:BXU08_11030 [4.1.3.-],    splm:BXU08_11025 [5.3.1.16])    => [2.4.2.-]
(spse:SULPSESMR1_01976 [4.1.3.-],       spse:SULPSESMR1_01975 [5.3.1.16])       => [2.4.2.-]
(suam:BOO69_12025 [4.1.3.-],    suam:BOO69_12020 [5.3.1.16])    => [2.4.2.-]
(swi:Swit_2720 [4.1.3.-],       swi:Swit_2719 [5.3.1.16])       => [2.4.2.-]
(thw:BMG03_06920 [4.1.3.-],     thw:BMG03_06985 [5.3.1.16])     => [2.4.2.-]
(tom:BWR18_09370 [4.1.3.-],     tom:BWR18_09385 [5.3.1.16])     => [2.4.2.-]
(tpro:Ga0080559_TMP2944 [4.1.3.-],      tpro:Ga0080559_TMP693 [5.3.1.16])       => [2.4.2.-]
(txi:TH3_20220 [4.1.3.-],       txi:TH3_20225 [5.3.1.16])       => [2.4.2.-]
(yan:AYJ57_10320 [4.1.3.-],     yan:AYJ57_10360 [5.3.1.16])     => [2.4.2.-]
(zmo:ZMO1500 [4.1.3.-],         zmo:ZMO1501 [5.3.1.16])         => [2.4.2.-]
(aak:AA2016_6521 [2.2.1.1],     aak:AA2016_4845 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(abs:AZOBR_p310084 [2.2.1.1],   abs:AZOBR_p1140022 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(abs:AZOBR_p310084 [2.2.1.1],   abs:AZOBR_p140100 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(acr:Acry_0718 [2.2.1.1],       acr:Acry_1833 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(agc:BSY240_2264 [2.2.1.1],     agc:BSY240_1694 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(agc:BSY240_2264 [2.2.1.1],     agc:BSY240_3636 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(agr:AGROH133_14223 [2.2.1.1],  agr:AGROH133_04351 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(agr:AGROH133_15069 [2.2.1.1],  agr:AGROH133_04351 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(aht:ANTHELSMS3_02354 [2.2.1.1],aht:ANTHELSMS3_02093 [2.2.1.7]) => [5.1.3.1, 5.3.1.6]
(amv:ACMV_11540 [2.2.1.1],      amv:ACMV_20740 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(aol:S58_25160 [2.2.1.1],       aol:S58_53660 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(apc:HIMB59_00006560 [2.2.1.1], apc:HIMB59_00009760 [2.2.1.7])  => [5.1.3.1, 5.3.1.6]
(ara:Arad_8184 [2.2.1.1],       ara:Arad_1198 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(aro:B0909_03510 [2.2.1.1],     aro:B0909_09755 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(ati:AL072_26050 [2.2.1.1],     ati:AL072_16870 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(atu:Atu1902 [2.2.1.1],         atu:Atu0745 [2.2.1.7])          => [5.1.3.1, 5.3.1.6]
(azl:AZL_a04640 [2.2.1.1],      azl:AZL_c00990 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(bbt:BBta_3269 [2.2.1.1],       bbt:BBta_2479 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(bbt:BBta_5637 [2.2.1.1],       bbt:BBta_2479 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(bic:LMTR13_32315 [2.2.1.1],    bic:LMTR13_30360 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(bja:blr2169 [2.2.1.1],         bja:bll2651 [2.2.1.7])          => [5.1.3.1, 5.3.1.6]
(bja:blr5427 [2.2.1.1],         bja:bll2651 [2.2.1.7])          => [5.1.3.1, 5.3.1.6]
(bju:BJ6T_76830 [2.2.1.1],      bju:BJ6T_71490 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(bos:BSY19_638 [2.2.1.1],       bos:BSY19_1705 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(bos:BSY19_638 [2.2.1.1],       bos:BSY19_4068 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(bos:BSY19_984 [2.2.1.1],       bos:BSY19_1705 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(bos:BSY19_984 [2.2.1.1],       bos:BSY19_4068 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(bra:BRADO4763 [2.2.1.1],       bra:BRADO2161 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(bra:BRADO5170 [2.2.1.1],       bra:BRADO2161 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(brad:BF49_6202 [2.2.1.1],      brad:BF49_2076 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(brc:BCCGELA001_13895 [2.2.1.1],brc:BCCGELA001_11565 [2.2.1.7]) => [5.1.3.1, 5.3.1.6]
(brc:BCCGELA001_22815 [2.2.1.1],brc:BCCGELA001_11565 [2.2.1.7]) => [5.1.3.1, 5.3.1.6]
(bro:BRAD285_2061 [2.2.1.1],    bro:BRAD285_5093 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(brs:S23_22520 [2.2.1.1],       brs:S23_53210 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(bvr:BVIR_1972 [2.2.1.1],       bvr:BVIR_1955 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(bvv:BHK69_01915 [2.2.1.1],     bvv:BHK69_11885 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(bvv:BHK69_07175 [2.2.1.1],     bvv:BHK69_11885 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(bvv:BHK69_30485 [2.2.1.1],     bvv:BHK69_11885 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(cbot:ATE48_13255 [2.2.1.1],    cbot:ATE48_03035 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(cmar:IMCC12053_2208 [2.2.1.1], cmar:IMCC12053_1854 [2.2.1.7])  => [5.1.3.1, 5.3.1.6]
(cmar:IMCC12053_755 [2.2.1.1],  cmar:IMCC12053_1854 [2.2.1.7])  => [5.1.3.1, 5.3.1.6]
(cmb:CSW64_01295 [2.2.1.1],     cmb:CSW64_15595 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(don:BSK21_15615 [2.2.1.1],     don:BSK21_13645 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(ead:OV14_a1402 [2.2.1.1],      ead:OV14_1817 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(ead:OV14_b1225 [2.2.1.1],      ead:OV14_1817 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(esj:SJ05684_b54200 [2.2.1.1],  esj:SJ05684_c04820 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(gdi:GDI0241 [2.2.1.1],         gdi:GDI1860 [2.2.1.7])          => [5.1.3.1, 5.3.1.6]
(gdi:GDI3010 [2.2.1.1],         gdi:GDI1860 [2.2.1.7])          => [5.1.3.1, 5.3.1.6]
(hdi:HDIA_0855 [2.2.1.1],       hdi:HDIA_1210 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(hdi:HDIA_P0045 [2.2.1.1],      hdi:HDIA_1210 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(hoe:IMCC20628_02265 [2.2.1.1], hoe:IMCC20628_02813 [2.2.1.7])  => [5.1.3.1, 5.3.1.6]
(maad:AZF01_17905 [2.2.1.1],    maad:AZF01_04975 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(mag:amb0067 [2.2.1.1],         mag:amb2904 [2.2.1.7])          => [5.1.3.1, 5.3.1.6]
(magn:WV31_12985 [2.2.1.1],     magn:WV31_19785 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(magq:MGMAQ_0173 [2.2.1.1],     magq:MGMAQ_2260 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(magx:XM1_0928 [2.2.1.1],       magx:XM1_2756 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(malg:MALG_04575 [2.2.1.1],     malg:MALG_03335 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(maqu:Maq22A_c16690 [2.2.1.1],  maqu:Maq22A_c16825 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(maqu:Maq22A_c16690 [2.2.1.1],  maqu:Maq22A_c25230 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(mbry:B1812_21440 [2.2.1.1],    mbry:B1812_01145 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(mes:Meso_3618 [2.2.1.1],       mes:Meso_0735 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(met:M446_2744 [2.2.1.1],       met:M446_6352 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(met:M446_2744 [2.2.1.1],       met:M446_6391 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(meta:Y590_09995 [2.2.1.1],     meta:Y590_09015 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(meta:Y590_09995 [2.2.1.1],     meta:Y590_21535 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(mex:Mext_2092 [2.2.1.1],       mex:Mext_1939 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mex:Mext_2092 [2.2.1.1],       mex:Mext_4309 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mgm:Mmc1_1058 [2.2.1.1],       mgm:Mmc1_1048 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mln:A9174_02530 [2.2.1.1],     mln:A9174_28510 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(mlo:mll5764 [2.2.1.1],         mlo:mlr7474 [2.2.1.7])          => [5.1.3.1, 5.3.1.6]
(mmed:Mame_00457 [2.2.1.1],     mmed:Mame_03800 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(mmed:Mame_01571 [2.2.1.1],     mmed:Mame_03800 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(mno:Mnod_4383 [2.2.1.1],       mno:Mnod_6796 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mno:Mnod_4383 [2.2.1.1],       mno:Mnod_7141 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mno:Mnod_4387 [2.2.1.1],       mno:Mnod_6796 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mno:Mnod_4387 [2.2.1.1],       mno:Mnod_7141 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mno:Mnod_5659 [2.2.1.1],       mno:Mnod_6796 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mno:Mnod_5659 [2.2.1.1],       mno:Mnod_7141 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(moc:BB934_30545 [2.2.1.1],     moc:BB934_05670 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(mop:Mesop_0510 [2.2.1.1],      mop:Mesop_5623 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(mor:MOC_3368 [2.2.1.1],        mor:MOC_4561 [2.2.1.7])         => [5.1.3.1, 5.3.1.6]
(mphy:MCBMB27_02435 [2.2.1.1],  mphy:MCBMB27_02946 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(mphy:MCBMB27_02435 [2.2.1.1],  mphy:MCBMB27_03478 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(mpo:Mpop_0261 [2.2.1.1],       mpo:Mpop_1830 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mpo:Mpop_0261 [2.2.1.1],       mpo:Mpop_4826 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mrd:Mrad2831_3003 [2.2.1.1],   mrd:Mrad2831_3459 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(mrd:Mrad2831_3003 [2.2.1.1],   mrd:Mrad2831_3992 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(msc:BN69_2088 [2.2.1.1],       msc:BN69_2310 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(mza:B2G69_17915 [2.2.1.1],     mza:B2G69_03480 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(mza:B2G69_17915 [2.2.1.1],     mza:B2G69_17155 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(nre:BES08_14725 [2.2.1.1],     nre:BES08_12705 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(oan:Oant_4834 [2.2.1.1],       oan:Oant_0547 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(oat:OAN307_c00600 [2.2.1.1],   oat:OAN307_c45760 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(paby:Ga0080574_TMP4465 [2.2.1.1],      paby:Ga0080574_TMP3111 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(paro:CUV01_01450 [2.2.1.1],    paro:CUV01_10455 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(paro:CUV01_06065 [2.2.1.1],    paro:CUV01_10455 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(paro:CUV01_13155 [2.2.1.1],    paro:CUV01_10455 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(pgv:SL003B_2451 [2.2.1.1],     pgv:SL003B_3299 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(php:PhaeoP97_03855 [2.2.1.1],  php:PhaeoP97_03318 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(pht:BLM14_25240 [2.2.1.1],     pht:BLM14_13200 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(ptp:RCA23_c02710 [2.2.1.1],    ptp:RCA23_c04430 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(ptp:RCA23_c02710 [2.2.1.1],    ptp:RCA23_c29710 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(pub:SAR11_0536 [2.2.1.1],      pub:SAR11_0611 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(pzh:CX676_18995 [2.2.1.1],     pzh:CX676_10325 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(rce:RC1_3769 [2.2.1.1],        rce:RC1_0565 [2.2.1.7])         => [5.1.3.1, 5.3.1.6]
(rcp:RCAP_rcc01832 [2.2.1.1],   rcp:RCAP_rcc00696 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(rcp:RCAP_rcc02654 [2.2.1.1],   rcp:RCAP_rcc00696 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(rcp:RCAP_rcc02654 [2.2.1.1],   rcp:RCAP_rcc03462 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(ret:RHE_CH02397 [2.2.1.1],     ret:RHE_CH00913 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(rga:RGR602_PC00231 [2.2.1.1],  rga:RGR602_CH00973 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(rga:RGR602_PC01824 [2.2.1.1],  rga:RGR602_CH00973 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(rgi:RGI145_22310 [2.2.1.1],    rgi:RGI145_07290 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(rhc:RGUI_3957 [2.2.1.1],       rhc:RGUI_1953 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(rhc:RGUI_3957 [2.2.1.1],       rhc:RGUI_2678 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(rhi:NGR_a02450 [2.2.1.1],      rhi:NGR_c04950 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(rhl:LPU83_pLPU83c0740 [2.2.1.1],       rhl:LPU83_1026 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(rhn:AMJ98_CH02452 [2.2.1.1],   rhn:AMJ98_CH00931 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(rhx:AMK02_CH02467 [2.2.1.1],   rhx:AMK02_CH00955 [2.2.1.7])    => [5.1.3.1, 5.3.1.6]
(rir:BN877_p0594 [2.2.1.1],     rir:BN877_I0720 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(rle:RL2718 [2.2.1.1],          rle:RL0973 [2.2.1.7])           => [5.1.3.1, 5.3.1.6]
(rmb:K529_016635 [2.2.1.1],     rmb:K529_014870 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(rpha:AMC79_CH02524 [2.2.1.1],  rpha:AMC79_CH00941 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(rpha:AMC79_PD00768 [2.2.1.1],  rpha:AMC79_CH00941 [2.2.1.7])   => [5.1.3.1, 5.3.1.6]
(rsp:RSP_3268 [2.2.1.1],        rsp:RSP_0254 [2.2.1.7])         => [5.1.3.1, 5.3.1.6]
(rsp:RSP_3268 [2.2.1.1],        rsp:RSP_1134 [2.2.1.7])         => [5.1.3.1, 5.3.1.6]
(rtr:RTCIAT899_PC06425 [2.2.1.1],       rtr:RTCIAT899_CH04415 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(sagu:CDO87_02170 [2.2.1.1],    sagu:CDO87_04610 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(same:SAMCFNEI73_pA0163 [2.2.1.1],      same:SAMCFNEI73_Ch0928 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(same:SAMCFNEI73_pC1939 [2.2.1.1],      same:SAMCFNEI73_Ch0928 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(sgi:SGRAN_1185 [2.2.1.1],      sgi:SGRAN_3913 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(shz:shn_03050 [2.2.1.1],       shz:shn_04070 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(shz:shn_26175 [2.2.1.1],       shz:shn_04070 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(shz:shn_27070 [2.2.1.1],       shz:shn_04070 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(sino:SS05631_a42480 [2.2.1.1], sino:SS05631_c05900 [2.2.1.7])  => [5.1.3.1, 5.3.1.6]
(sino:SS05631_a48150 [2.2.1.1], sino:SS05631_c05900 [2.2.1.7])  => [5.1.3.1, 5.3.1.6]
(sino:SS05631_b52020 [2.2.1.1], sino:SS05631_c05900 [2.2.1.7])  => [5.1.3.1, 5.3.1.6]
(six:BSY16_4811 [2.2.1.1],      six:BSY16_2102 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(skr:BRX40_01570 [2.2.1.1],     skr:BRX40_07400 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(smd:Smed_3129 [2.2.1.1],       smd:Smed_0492 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(sme:SMc00269 [2.2.1.1],        sme:SMc00972 [2.2.1.7])         => [5.1.3.1, 5.3.1.6]
(span:AWL63_00225 [2.2.1.1],    span:AWL63_08815 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(sphc:CVN68_12600 [2.2.1.1],    sphc:CVN68_09985 [2.2.1.7])     => [5.1.3.1, 5.3.1.6]
(sphi:TS85_09655 [2.2.1.1],     sphi:TS85_12485 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(spse:SULPSESMR1_00542 [2.2.1.1],       spse:SULPSESMR1_03031 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(ssan:NX02_20250 [2.2.1.1],     ssan:NX02_14100 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(sya:A6768_20295 [2.2.1.1],     sya:A6768_06065 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(thw:BMG03_00060 [2.2.1.1],     thw:BMG03_00810 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(thw:BMG03_00155 [2.2.1.1],     thw:BMG03_00810 [2.2.1.7])      => [5.1.3.1, 5.3.1.6]
(tpro:Ga0080559_TMP322 [2.2.1.1],       tpro:Ga0080559_TMP1172 [2.2.1.7])       => [5.1.3.1, 5.3.1.6]
(xau:Xaut_1539 [2.2.1.1],       xau:Xaut_4733 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(xau:Xaut_1713 [2.2.1.1],       xau:Xaut_4733 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]
(xau:Xaut_2041 [2.2.1.1],       xau:Xaut_4733 [2.2.1.7])        => [5.1.3.1, 5.3.1.6]




Betaproteobacteria:

core metabolism ECs: 298

"neofunctionalised" ECs: 70 (23%)
1.1.1.100
1.1.1.35
1.1.1.36
1.1.1.42
1.1.1.85
1.2.4.1
1.2.4.2
1.8.1.4
2.1.2.2
2.1.3.2
2.1.3.3
2.2.1.1
2.2.1.7
2.3.1.-
2.3.1.1
2.3.1.12
2.3.1.129
2.3.1.16
2.3.1.179
2.3.1.180
2.3.1.191
2.3.1.61
2.3.1.9
2.4.2.-
2.4.2.14
2.5.1.49
2.5.1.54
2.5.1.55
2.6.1.16
2.6.1.17
2.6.1.62
2.7.2.8
2.7.7.24
2.7.7.38
2.7.7.6
2.7.7.7
2.7.7.9
3.1.3.105
3.1.3.18
3.1.3.45
3.5.1.10
4.1.3.-
4.1.3.27
4.1.99.17
4.2.1.46
4.4.1.8
5.1.1.7
5.1.3.2
5.3.1.16
5.4.3.8
6.1.1.1
6.1.1.10
6.1.1.12
6.1.1.14
6.1.1.15
6.1.1.17
6.1.1.18
6.1.1.20
6.1.1.3
6.1.1.4
6.1.1.5
6.1.1.6
6.1.1.9
6.2.1.1
6.2.1.3
6.3.2.10
6.3.2.13
6.3.2.8
6.3.2.9
6.3.4.18

"neofunctionalised" ECs contributing to redundancy: 7 ( 2%)
2.1.3.3 => [2.1.3.2]
2.2.1.1 => [2.2.1.2, 5.1.3.1, 5.3.1.6]
2.2.1.7 => [1.2.1.12, 2.7.9.2]
2.4.2.- => [4.1.3.-]
2.7.7.6 => [6.3.4.2]
4.1.3.- => [2.4.2.-]
6.2.1.3 => [3.1.2.-]

Neofunctionalisations contributing to redundancy: 1760 (21%)
(achr:C2U31_27345 [2.2.1.1],    achr:C2U31_14670 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(adn:Alide_2368 [2.2.1.1],      adn:Alide_1116 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(adt:APT56_19615 [2.2.1.1],     adt:APT56_08065 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(ais:BUW96_13275 [2.2.1.1],     ais:BUW96_17225 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(asw:CVS48_14175 [2.2.1.1],     asw:CVS48_27015 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(axy:AXYL_04857 [2.2.1.1],      axy:AXYL_01834 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(aza:AZKH_p0609 [2.2.1.1],      aza:AZKH_1187 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bam:Bamb_4411 [2.2.1.1],       bam:Bamb_3250 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bav:BAV1248 [2.2.1.1],         bav:BAV2177 [2.2.1.7])          => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bbro:BAU06_15455 [2.2.1.1],    bbro:BAU06_17255 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bbro:BAU06_24825 [2.2.1.1],    bbro:BAU06_17255 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bcai:K788_0002125 [2.2.1.1],   bcai:K788_0000378 [2.2.1.7])    => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bcai:K788_0002125 [2.2.1.1],   bcai:K788_0006001 [2.2.1.7])    => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bcn:Bcen_6422 [2.2.1.1],       bcn:Bcen_4486 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bdl:AK34_4869 [2.2.1.1],       bdl:AK34_4540 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(beb:AEM42_00205 [2.2.1.1],     beb:AEM42_15395 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bfn:OI25_5833 [2.2.1.1],       bfn:OI25_5238 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bfn:OI25_6025 [2.2.1.1],       bfn:OI25_5238 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bfz:BAU07_10955 [2.2.1.1],     bfz:BAU07_08915 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bge:BC1002_6125 [2.2.1.1],     bge:BC1002_5272 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bgf:BC1003_3395 [2.2.1.1],     bgf:BC1003_4540 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bgf:BC1003_4378 [2.2.1.1],     bgf:BC1003_4540 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bhz:ACR54_02536 [2.2.1.1],     bhz:ACR54_02932 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(blat:WK25_27220 [2.2.1.1],     blat:WK25_22030 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bmec:WJ16_20295 [2.2.1.1],     bmec:WJ16_23515 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bmu:Bmul_4991 [2.2.1.1],       bmu:Bmul_4820 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bph:Bphy_5878 [2.2.1.1],       bph:Bphy_3948 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bpsl:WS57_17195 [2.2.1.1],     bpsl:WS57_09505 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bpsl:WS57_18925 [2.2.1.1],     bpsl:WS57_09505 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bpx:BUPH_05969 [2.2.1.1],      bpx:BUPH_01519 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bpx:BUPH_08115 [2.2.1.1],      bpx:BUPH_01519 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bpy:Bphyt_6139 [2.2.1.1],      bpy:Bphyt_6781 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bpy:Bphyt_6143 [2.2.1.1],      bpy:Bphyt_6781 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bpyr:ABD05_24875 [2.2.1.1],    bpyr:ABD05_17250 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bue:BRPE67_CCDS04770 [2.2.1.1],bue:BRPE67_BCDS14920 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bue:BRPE67_DCDS09370 [2.2.1.1],bue:BRPE67_BCDS14920 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bug:BC1001_3437 [2.2.1.1],     bug:BC1001_4954 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bug:BC1001_5109 [2.2.1.1],     bug:BC1001_4954 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(buo:BRPE64_CCDS04460 [2.2.1.1],buo:BRPE64_BCDS12130 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(buo:BRPE64_DCDS04540 [2.2.1.1],buo:BRPE64_BCDS12130 [2.2.1.7]) => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(buq:AC233_24585 [2.2.1.1],     buq:AC233_25165 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(buq:AC233_25595 [2.2.1.1],     buq:AC233_25165 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(buz:AYM40_04760 [2.2.1.1],     buz:AYM40_22455 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(buz:AYM40_34265 [2.2.1.1],     buz:AYM40_22455 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(bxe:Bxe_B2699 [2.2.1.1],       bxe:Bxe_B2827 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(byi:BYI23_C006650 [2.2.1.1],   byi:BYI23_B011150 [2.2.1.7])    => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(byi:BYI23_D007460 [2.2.1.1],   byi:BYI23_B011150 [2.2.1.7])    => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(cbw:RR42_s2709 [2.2.1.1],      cbw:RR42_m3051 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(dac:Daci_0727 [2.2.1.1],       dac:Daci_2242 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(del:DelCs14_5810 [2.2.1.1],    del:DelCs14_4446 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(dhk:BO996_03675 [2.2.1.1],     dhk:BO996_10460 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(dts:BI380_21095 [2.2.1.1],     dts:BI380_13020 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(gca:Galf_1087 [2.2.1.1],       gca:Galf_2269 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(hee:hmeg3_21570 [2.2.1.1],     hee:hmeg3_04815 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(hht:F506_00970 [2.2.1.1],      hht:F506_02305 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(hrb:Hrubri_4314 [2.2.1.1],     hrb:Hrubri_3794 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(hse:Hsero_1105 [2.2.1.1],      hse:Hsero_3831 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(hyr:BSY239_3381 [2.2.1.1],     hyr:BSY239_895 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(jab:VN23_20255 [2.2.1.1],      jab:VN23_00950 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(kki:KKKWG1_1933 [2.2.1.1],     kki:KKKWG1_2212 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(lch:Lcho_4275 [2.2.1.1],       lch:Lcho_3373 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(lim:L103DPR2_00946 [2.2.1.1],  lim:L103DPR2_01015 [2.2.1.7])   => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(lim:L103DPR2_00946 [2.2.1.1],  lim:L103DPR2_01240 [2.2.1.7])   => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(masw:AM586_20940 [2.2.1.1],    masw:AM586_05270 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(nla:NLA_8710 [2.2.1.1],        nla:NLA_18120 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(odi:ODI_R2986 [2.2.1.1],       odi:ODI_R1586 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(parb:CJU94_30940 [2.2.1.1],    parb:CJU94_29535 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(parb:CJU94_31845 [2.2.1.1],    parb:CJU94_29535 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(phs:C2L64_13915 [2.2.1.1],     phs:C2L64_31595 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(phs:C2L64_13915 [2.2.1.1],     phs:C2L64_34025 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(phs:C2L64_42960 [2.2.1.1],     phs:C2L64_31595 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(phs:C2L64_42960 [2.2.1.1],     phs:C2L64_34025 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(pol:Bpro_1462 [2.2.1.1],       pol:Bpro_1747 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(pse:NH8B_2710 [2.2.1.1],       pse:NH8B_2773 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(pspw:BJG93_28290 [2.2.1.1],    pspw:BJG93_20705 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(pter:C2L65_33870 [2.2.1.1],    pter:C2L65_28330 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(pter:C2L65_33870 [2.2.1.1],    pter:C2L65_30475 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(pter:C2L65_40145 [2.2.1.1],    pter:C2L65_28330 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(pter:C2L65_40145 [2.2.1.1],    pter:C2L65_30475 [2.2.1.7])     => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(ptx:ABW99_11865 [2.2.1.1],     ptx:ABW99_10555 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(put:PT7_3273 [2.2.1.1],        put:PT7_0463 [2.2.1.7])         => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(rbu:PG1C_08950 [2.2.1.1],      rbu:PG1C_03825 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(reu:Reut_B4778 [2.2.1.1],      reu:Reut_A0882 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(rsb:RS694_02935 [2.2.1.1],     rsb:RS694_06610 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(rta:Rta_31430 [2.2.1.1],       rta:Rta_13100 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(vap:Vapar_3312 [2.2.1.1],      vap:Vapar_1571 [2.2.1.7])       => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(vbo:CKY39_03890 [2.2.1.1],     vbo:CKY39_09810 [2.2.1.7])      => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(vei:Veis_0901 [2.2.1.1],       vei:Veis_3283 [2.2.1.7])        => [1.2.1.12, 2.2.1.2, 2.7.9.2, 5.1.3.1, 5.3.1.6]
(lhk:LHK_02270 [1.2.4.1],       lhk:LHK_02324 [2.2.1.7])        => [1.2.1.12, 2.7.9.2]
(aaa:Acav_1329 [2.1.3.2],       aaa:Acav_1176 [2.1.3.3])        => [2.1.3.2]
(aaa:Acav_3861 [2.1.3.2],       aaa:Acav_1176 [2.1.3.3])        => [2.1.3.2]
(achr:C2U31_14810 [2.1.3.2],    achr:C2U31_15535 [2.1.3.3])     => [2.1.3.2]
(afa:UZ73_01350 [2.1.3.2],      afa:UZ73_16545 [2.1.3.3])       => [2.1.3.2]
(aql:BXU06_15315 [2.1.3.2],     aql:BXU06_05320 [2.1.3.3])      => [2.1.3.2]
(bbro:BAU06_09015 [2.1.3.2],    bbro:BAU06_16455 [2.1.3.3])     => [2.1.3.2]
(boh:AKI39_08835 [2.1.3.2],     boh:AKI39_15735 [2.1.3.3])      => [2.1.3.2]
(bpdz:BBN53_13075 [2.1.3.2],    bpdz:BBN53_07765 [2.1.3.3])     => [2.1.3.2]
(bpe:BP0321 [2.1.3.2],          bpe:BP3538 [2.1.3.3])           => [2.1.3.2]
(bprc:D521_0249 [2.1.3.2],      bprc:D521_1736 [2.1.3.3])       => [2.1.3.2]
(chro:CXB49_21590 [2.1.3.2],    chro:CXB49_12380 [2.1.3.3])     => [2.1.3.2]
(cuh:BJN34_15590 [2.1.3.2],     cuh:BJN34_16365 [2.1.3.3])      => [2.1.3.2]
(cvc:BKX93_13600 [2.1.3.2],     cvc:BKX93_00195 [2.1.3.3])      => [2.1.3.2]
(cvi:CV_0369 [2.1.3.2],         cvi:CV_1993 [2.1.3.3])          => [2.1.3.2]
(jab:VN23_11375 [2.1.3.2],      jab:VN23_09715 [2.1.3.3])       => [2.1.3.2]
(kci:CKCE_0422 [2.1.3.2],       kci:CKCE_0268 [2.1.3.3])        => [2.1.3.2]
(kde:CDSE_0440 [2.1.3.2],       kde:CDSE_0612 [2.1.3.3])        => [2.1.3.2]
(kki:KKKWG1_1109 [2.1.3.2],     kki:KKKWG1_0605 [2.1.3.3])      => [2.1.3.2]
(lim:L103DPR2_02555 [2.1.3.2],  lim:L103DPR2_02391 [2.1.3.3])   => [2.1.3.2]
(pne:Pnec_0267 [2.1.3.2],       pne:Pnec_1469 [2.1.3.3])        => [2.1.3.2]
(pse:NH8B_4063 [2.1.3.2],       pse:NH8B_2585 [2.1.3.3])        => [2.1.3.2]
(salv:SALWKB2_2106 [2.1.3.2],   salv:SALWKB2_1795 [2.1.3.3])    => [2.1.3.2]
(tbd:Tbd_2582 [2.1.3.2],        tbd:Tbd_1850 [2.1.3.3])         => [2.1.3.2]
(aav:Aave_1047 [4.1.3.-],       aav:Aave_1034 [5.3.1.16])       => [2.4.2.-]
(achr:C2U31_05885 [4.1.3.-],    achr:C2U31_05890 [5.3.1.16])    => [2.4.2.-]
(acid:CBP33_15190 [4.1.3.-],    acid:CBP33_15225 [5.3.1.16])    => [2.4.2.-]
(acin:CBP34_15995 [4.1.3.-],    acin:CBP34_16035 [5.3.1.16])    => [2.4.2.-]
(adn:Alide_0890 [4.1.3.-],      adn:Alide_0880 [5.3.1.16])      => [2.4.2.-]
(adt:APT56_01200 [4.1.3.-],     adt:APT56_01205 [5.3.1.16])     => [2.4.2.-]
(afa:UZ73_12110 [4.1.3.-],      afa:UZ73_12115 [5.3.1.16])      => [2.4.2.-]
(ais:BUW96_26685 [4.1.3.-],     ais:BUW96_26690 [5.3.1.16])     => [2.4.2.-]
(amim:MIM_c04890 [4.1.3.-],     amim:MIM_c04880 [5.3.1.16])     => [2.4.2.-]
(aoa:dqs_3481 [4.1.3.-],        aoa:dqs_3482 [5.3.1.16])        => [2.4.2.-]
(app:CAP2UW1_4038 [4.1.3.-],    app:CAP2UW1_4037 [5.3.1.16])    => [2.4.2.-]
(aql:BXU06_13320 [4.1.3.-],     aql:BXU06_13325 [5.3.1.16])     => [2.4.2.-]
(asw:CVS48_05125 [4.1.3.-],     asw:CVS48_05120 [5.3.1.16])     => [2.4.2.-]
(atw:C0099_06035 [4.1.3.-],     atw:C0099_06030 [5.3.1.16])     => [2.4.2.-]
(axy:AXYL_00185 [4.1.3.-],      axy:AXYL_00186 [5.3.1.16])      => [2.4.2.-]
(aza:AZKH_0760 [4.1.3.-],       aza:AZKH_0759 [5.3.1.16])       => [2.4.2.-]
(azi:AzCIB_0661 [4.1.3.-],      azi:AzCIB_0660 [5.3.1.16])      => [2.4.2.-]
(azo:azo3344 [4.1.3.-],         azo:azo3345 [5.3.1.16])         => [2.4.2.-]
(bam:Bamb_0349 [4.1.3.-],       bam:Bamb_0348 [5.3.1.16])       => [2.4.2.-]
(bav:BAV3319 [4.1.3.-],         bav:BAV3318 [5.3.1.16])         => [2.4.2.-]
(bbag:E1O_23320 [4.1.3.-],      bbag:E1O_23330 [5.3.1.16])      => [2.4.2.-]
(bbay:A4V04_12520 [4.1.3.-],    bbay:A4V04_12525 [5.3.1.16])    => [2.4.2.-]
(bbr:BB4859 [4.1.3.-],          bbr:BB4858 [5.3.1.16])          => [2.4.2.-]
(bbro:BAU06_00830 [4.1.3.-],    bbro:BAU06_00835 [5.3.1.16])    => [2.4.2.-]
(bcai:K788_00013550 [4.1.3.-],  bcai:K788_0002608 [5.3.1.16])   => [2.4.2.-]
(bcn:Bcen_2676 [4.1.3.-],       bcn:Bcen_2677 [5.3.1.16])       => [2.4.2.-]
(bcon:NL30_19965 [4.1.3.-],     bcon:NL30_19960 [5.3.1.16])     => [2.4.2.-]
(bct:GEM_3091 [4.1.3.-],        bct:GEM_3092 [5.3.1.16])        => [2.4.2.-]
(bdf:WI26_01760 [4.1.3.-],      bdf:WI26_01755 [5.3.1.16])      => [2.4.2.-]
(bdl:AK34_2715 [4.1.3.-],       bdl:AK34_2716 [5.3.1.16])       => [2.4.2.-]
(beba:BWI17_08645 [4.1.3.-],    beba:BWI17_08640 [5.3.1.16])    => [2.4.2.-]
(bfn:OI25_1854 [4.1.3.-],       bfn:OI25_1853 [5.3.1.16])       => [2.4.2.-]
(bfz:BAU07_00675 [4.1.3.-],     bfz:BAU07_00680 [5.3.1.16])     => [2.4.2.-]
(bgd:bgla_1g03820 [4.1.3.-],    bgd:bgla_1g03810 [5.3.1.16])    => [2.4.2.-]
(bge:BC1002_2813 [4.1.3.-],     bge:BC1002_2814 [5.3.1.16])     => [2.4.2.-]
(bgf:BC1003_3154 [4.1.3.-],     bgf:BC1003_3155 [5.3.1.16])     => [2.4.2.-]
(bgl:bglu_1g03370 [4.1.3.-],    bgl:bglu_1g03360 [5.3.1.16])    => [2.4.2.-]
(bho:D560_1570 [4.1.3.-],       bho:D560_1571 [5.3.1.16])       => [2.4.2.-]
(bhz:ACR54_04497 [4.1.3.-],     bhz:ACR54_04496 [5.3.1.16])     => [2.4.2.-]
(blat:WK25_00550 [4.1.3.-],     blat:WK25_00555 [5.3.1.16])     => [2.4.2.-]
(bma:BMA2708 [4.1.3.-],         bma:BMA2709 [5.3.1.16])         => [2.4.2.-]
(bmec:WJ16_01790 [4.1.3.-],     bmec:WJ16_01785 [5.3.1.16])     => [2.4.2.-]
(bmu:Bmul_0334 [4.1.3.-],       bmu:Bmul_0333 [5.3.1.16])       => [2.4.2.-]
(boh:AKI39_00595 [4.1.3.-],     boh:AKI39_00590 [5.3.1.16])     => [2.4.2.-]
(bok:DM82_2832 [4.1.3.-],       bok:DM82_2833 [5.3.1.16])       => [2.4.2.-]
(bpa:BPP4272 [4.1.3.-],         bpa:BPP4271 [5.3.1.16])         => [2.4.2.-]
(bpdz:BBN53_00655 [4.1.3.-],    bpdz:BBN53_00660 [5.3.1.16])    => [2.4.2.-]
(bpe:BP3773 [4.1.3.-],          bpe:BP3772 [5.3.1.16])          => [2.4.2.-]
(bpla:bpln_1g03260 [4.1.3.-],   bpla:bpln_1g03250 [5.3.1.16])   => [2.4.2.-]
(bprc:D521_0111 [4.1.3.-],      bprc:D521_0110 [5.3.1.16])      => [2.4.2.-]
(bps:BPSL3133 [4.1.3.-],        bps:BPSL3134 [5.3.1.16])        => [2.4.2.-]
(bpsi:IX83_08400 [4.1.3.-],     bpsi:IX83_08405 [5.3.1.16])     => [2.4.2.-]
(bpsl:WS57_19655 [4.1.3.-],     bpsl:WS57_19650 [5.3.1.16])     => [2.4.2.-]
(bpx:BUPH_06283 [4.1.3.-],      bpx:BUPH_06284 [5.3.1.16])      => [2.4.2.-]
(bpy:Bphyt_3554 [4.1.3.-],      bpy:Bphyt_3555 [5.3.1.16])      => [2.4.2.-]
(bpyr:ABD05_07815 [4.1.3.-],    bpyr:ABD05_07810 [5.3.1.16])    => [2.4.2.-]
(brh:RBRH_02287 [4.1.3.-],      brh:RBRH_02288 [5.3.1.16])      => [2.4.2.-]
(bsem:WJ12_01840 [4.1.3.-],     bsem:WJ12_01835 [5.3.1.16])     => [2.4.2.-]
(bstg:WT74_02130 [4.1.3.-],     bstg:WT74_02125 [5.3.1.16])     => [2.4.2.-]
(bstl:BBJ41_11885 [4.1.3.-],    bstl:BBJ41_11880 [5.3.1.16])    => [2.4.2.-]
(bte:BTH_I2987 [4.1.3.-],       bte:BTH_I2988 [5.3.1.16])       => [2.4.2.-]
(btei:WS51_12580 [4.1.3.-],     btei:WS51_12575 [5.3.1.16])     => [2.4.2.-]
(btrm:SAMEA390648701079 [4.1.3.-],      btrm:SAMEA390648701078 [5.3.1.16])      => [2.4.2.-]
(bub:BW23_1321 [4.1.3.-],       bub:BW23_1322 [5.3.1.16])       => [2.4.2.-]
(bud:AQ610_01970 [4.1.3.-],     bud:AQ610_01965 [5.3.1.16])     => [2.4.2.-]
(bue:BRPE67_ACDS24470 [4.1.3.-],bue:BRPE67_ACDS24480 [5.3.1.16])=> [2.4.2.-]
(bug:BC1001_3193 [4.1.3.-],     bug:BC1001_3194 [5.3.1.16])     => [2.4.2.-]
(bul:BW21_514 [4.1.3.-],        bul:BW21_513 [5.3.1.16])        => [2.4.2.-]
(buo:BRPE64_ACDS25010 [4.1.3.-],buo:BRPE64_ACDS25020 [5.3.1.16])=> [2.4.2.-]
(buq:AC233_16230 [4.1.3.-],     buq:AC233_16235 [5.3.1.16])     => [2.4.2.-]
(bur:Bcep18194_A3529 [4.1.3.-], bur:Bcep18194_A3528 [5.3.1.16]) => [2.4.2.-]
(buz:AYM40_18560 [4.1.3.-],     buz:AYM40_18565 [5.3.1.16])     => [2.4.2.-]
(bvi:Bcep1808_0410 [4.1.3.-],   bvi:Bcep1808_0409 [5.3.1.16])   => [2.4.2.-]
(bxe:Bxe_A0404 [4.1.3.-],       bxe:Bxe_A0403 [5.3.1.16])       => [2.4.2.-]
(byi:BYI23_A023660 [4.1.3.-],   byi:BYI23_A023670 [5.3.1.16])   => [2.4.2.-]
(care:LT85_0577 [4.1.3.-],      care:LT85_0576 [5.3.1.16])      => [2.4.2.-]
(cbw:RR42_m3835 [4.1.3.-],      cbw:RR42_m3836 [5.3.1.16])      => [2.4.2.-]
(cbx:Cenrod_0738 [4.1.3.-],     cbx:Cenrod_0737 [5.3.1.16])     => [2.4.2.-]
(ccup:BKK81_00100 [4.1.3.-],    ccup:BKK81_00105 [5.3.1.16])    => [2.4.2.-]
(cdn:BN940_00391 [4.1.3.-],     cdn:BN940_00386 [5.3.1.16])     => [2.4.2.-]
(cfu:CFU_0520 [4.1.3.-],        cfu:CFU_0519 [5.3.1.16])        => [2.4.2.-]
(cgd:CR3_2520 [4.1.3.-],        cgd:CR3_2521 [5.3.1.16])        => [2.4.2.-]
(chro:CXB49_22815 [4.1.3.-],    chro:CXB49_22810 [5.3.1.16])    => [2.4.2.-]
(cke:B5M06_07895 [4.1.3.-],     cke:B5M06_07885 [5.3.1.16])     => [2.4.2.-]
(cpra:CPter91_0601 [4.1.3.-],   cpra:CPter91_0600 [5.3.1.16])   => [2.4.2.-]
(cser:CCO03_05155 [4.1.3.-],    cser:CCO03_14580 [5.3.1.16])    => [2.4.2.-]
(cti:RALTA_A2869 [4.1.3.-],     cti:RALTA_A2870 [5.3.1.16])     => [2.4.2.-]
(cuh:BJN34_18275 [4.1.3.-],     cuh:BJN34_18280 [5.3.1.16])     => [2.4.2.-]
(cup:BKK80_19355 [4.1.3.-],     cup:BKK80_19360 [5.3.1.16])     => [2.4.2.-]
(cuu:BKK79_12720 [4.1.3.-],     cuu:BKK79_12715 [5.3.1.16])     => [2.4.2.-]
(cvc:BKX93_12265 [4.1.3.-],     cvc:BKX93_12270 [5.3.1.16])     => [2.4.2.-]
(cvi:CV_0618 [4.1.3.-],         cvi:CV_0617 [5.3.1.16])         => [2.4.2.-]
(dac:Daci_5548 [4.1.3.-],       dac:Daci_5518 [5.3.1.16])       => [2.4.2.-]
(del:DelCs14_1066 [4.1.3.-],    del:DelCs14_1096 [5.3.1.16])    => [2.4.2.-]
(dhk:BO996_25830 [4.1.3.-],     dhk:BO996_25680 [5.3.1.16])     => [2.4.2.-]
(dia:Dtpsy_0738 [4.1.3.-],      dia:Dtpsy_0732 [5.3.1.16])      => [2.4.2.-]
(dpy:BA022_11040 [4.1.3.-],     dpy:BA022_11070 [5.3.1.16])     => [2.4.2.-]
(dsu:Dsui_1418 [4.1.3.-],       dsu:Dsui_1417 [5.3.1.16])       => [2.4.2.-]
(dts:BI380_27375 [4.1.3.-],     dts:BI380_27520 [5.3.1.16])     => [2.4.2.-]
(eba:ebA1291 [4.1.3.-],         eba:ebA1293 [5.3.1.16])         => [2.4.2.-]
(har:HEAR3064 [4.1.3.-],        har:HEAR3065 [5.3.1.16])        => [2.4.2.-]
(hee:hmeg3_03510 [4.1.3.-],     hee:hmeg3_03505 [5.3.1.16])     => [2.4.2.-]
(hht:F506_03585 [4.1.3.-],      hht:F506_03580 [5.3.1.16])      => [2.4.2.-]
(hrb:Hrubri_4021 [4.1.3.-],     hrb:Hrubri_4022 [5.3.1.16])     => [2.4.2.-]
(hse:Hsero_4063 [4.1.3.-],      hse:Hsero_4064 [5.3.1.16])      => [2.4.2.-]
(hyb:Q5W_02305 [4.1.3.-],       hyb:Q5W_02300 [5.3.1.16])       => [2.4.2.-]
(hyl:LPB072_04835 [4.1.3.-],    hyl:LPB072_04830 [5.3.1.16])    => [2.4.2.-]
(hyr:BSY239_3079 [4.1.3.-],     hyr:BSY239_3080 [5.3.1.16])     => [2.4.2.-]
(jab:VN23_18290 [4.1.3.-],      jab:VN23_18300 [5.3.1.16])      => [2.4.2.-]
(jag:GJA_76 [4.1.3.-],          jag:GJA_75 [5.3.1.16])          => [2.4.2.-]
(jal:BZG29_00540 [4.1.3.-],     jal:BZG29_00545 [5.3.1.16])     => [2.4.2.-]
(jaz:YQ44_27465 [4.1.3.-],      jaz:YQ44_27460 [5.3.1.16])      => [2.4.2.-]
(jsv:CNX70_00570 [4.1.3.-],     jsv:CNX70_00575 [5.3.1.16])     => [2.4.2.-]
(kbl:CKBE_00184 [4.1.3.-],      kbl:CKBE_00185 [5.3.1.16])      => [2.4.2.-]
(kci:CKCE_0628 [4.1.3.-],       kci:CKCE_0629 [5.3.1.16])       => [2.4.2.-]
(kde:CDSE_0225 [4.1.3.-],       kde:CDSE_0226 [5.3.1.16])       => [2.4.2.-]
(kga:ST1E_0246 [4.1.3.-],       kga:ST1E_0248 [5.3.1.16])       => [2.4.2.-]
(kon:CONE_0222 [4.1.3.-],       kon:CONE_0223 [5.3.1.16])       => [2.4.2.-]
(lch:Lcho_1592 [4.1.3.-],       lch:Lcho_1591 [5.3.1.16])       => [2.4.2.-]
(lhk:LHK_00190 [4.1.3.-],       lhk:LHK_00188 [5.3.1.16])       => [2.4.2.-]
(lih:L63ED372_02586 [4.1.3.-],  lih:L63ED372_02588 [5.3.1.16])  => [2.4.2.-]
(lim:L103DPR2_00741 [4.1.3.-],  lim:L103DPR2_00739 [5.3.1.16])  => [2.4.2.-]
(mbac:BN1209_0206 [4.1.3.-],    mbac:BN1209_0205 [5.3.1.16])    => [2.4.2.-]
(mbat:BN1208_0185 [4.1.3.-],    mbat:BN1208_0184 [5.3.1.16])    => [2.4.2.-]
(meh:M301_0308 [4.1.3.-],       meh:M301_0307 [5.3.1.16])       => [2.4.2.-]
(mei:Msip34_0272 [4.1.3.-],     mei:Msip34_0271 [5.3.1.16])     => [2.4.2.-]
(mep:MPQ_0285 [4.1.3.-],        mep:MPQ_0284 [5.3.1.16])        => [2.4.2.-]
(metr:BSY238_2540 [4.1.3.-],    metr:BSY238_2539 [5.3.1.16])    => [2.4.2.-]
(meu:ACJ67_02440 [4.1.3.-],     meu:ACJ67_02435 [5.3.1.16])     => [2.4.2.-]
(mfa:Mfla_0254 [4.1.3.-],       mfa:Mfla_0253 [5.3.1.16])       => [2.4.2.-]
(mmb:Mmol_0317 [4.1.3.-],       mmb:Mmol_0316 [5.3.1.16])       => [2.4.2.-]
(mms:mma_3283 [4.1.3.-],        mms:mma_3284 [5.3.1.16])        => [2.4.2.-]
(mnr:ACZ75_19875 [4.1.3.-],     mnr:ACZ75_19870 [5.3.1.16])     => [2.4.2.-]
(mpt:Mpe_A0836 [4.1.3.-],       mpt:Mpe_A0835 [5.3.1.16])       => [2.4.2.-]
(nco:AAW31_17410 [4.1.3.-],     nco:AAW31_17415 [5.3.1.16])     => [2.4.2.-]
(nel:NELON_04670 [4.1.3.-],     nel:NELON_04660 [5.3.1.16])     => [2.4.2.-]
(net:Neut_1909 [4.1.3.-],       net:Neut_1908 [5.3.1.16])       => [2.4.2.-]
(neu:NE0643 [4.1.3.-],          neu:NE0644 [5.3.1.16])          => [2.4.2.-]
(ngo:NGO0211 [4.1.3.-],         ngo:NGO0212 [5.3.1.16])         => [2.4.2.-]
(nii:Nit79A3_1044 [4.1.3.-],    nii:Nit79A3_1045 [5.3.1.16])    => [2.4.2.-]
(nla:NLA_16030 [4.1.3.-],       nla:NLA_16020 [5.3.1.16])       => [2.4.2.-]
(nlc:EBAPG3_006305 [4.1.3.-],   nlc:EBAPG3_006310 [5.3.1.16])   => [2.4.2.-]
(nma:NMA0838 [4.1.3.-],         nma:NMA0839 [5.3.1.16])         => [2.4.2.-]
(nmu:Nmul_A0814 [4.1.3.-],      nmu:Nmul_A0815 [5.3.1.16])      => [2.4.2.-]
(nsi:A6J88_13230 [4.1.3.-],     nsi:A6J88_13240 [5.3.1.16])     => [2.4.2.-]
(nwe:SAMEA3174300_0041 [4.1.3.-],       nwe:SAMEA3174300_0039 [5.3.1.16])       => [2.4.2.-]
(odi:ODI_R0270 [4.1.3.-],       odi:ODI_R0271 [5.3.1.16])       => [2.4.2.-]
(ofo:BRW83_0194 [4.1.3.-],      ofo:BRW83_0193 [5.3.1.16])      => [2.4.2.-]
(oto:ADJ79_05965 [4.1.3.-],     oto:ADJ79_02380 [5.3.1.16])     => [2.4.2.-]
(papi:SG18_06885 [4.1.3.-],     papi:SG18_06890 [5.3.1.16])     => [2.4.2.-]
(para:BTO02_18755 [4.1.3.-],    para:BTO02_18760 [5.3.1.16])    => [2.4.2.-]
(parb:CJU94_07155 [4.1.3.-],    parb:CJU94_07150 [5.3.1.16])    => [2.4.2.-]
(pbh:AAW51_4651 [4.1.3.-],      pbh:AAW51_4652 [5.3.1.16])      => [2.4.2.-]
(pdq:CL55_00001100 [4.1.3.-],   pdq:CL55_00001090 [5.3.1.16])   => [2.4.2.-]
(pfg:AB870_09440 [4.1.3.-],     pfg:AB870_09445 [5.3.1.16])     => [2.4.2.-]
(phn:PAEH1_08825 [4.1.3.-],     phn:PAEH1_08830 [5.3.1.16])     => [2.4.2.-]
(phs:C2L64_16400 [4.1.3.-],     phs:C2L64_16405 [5.3.1.16])     => [2.4.2.-]
(pkt:AT984_01545 [4.1.3.-],     pkt:AT984_01540 [5.3.1.16])     => [2.4.2.-]
(pne:Pnec_0111 [4.1.3.-],       pne:Pnec_0110 [5.3.1.16])       => [2.4.2.-]
(pnr:AT302_06085 [4.1.3.-],     pnr:AT302_06090 [5.3.1.16])     => [2.4.2.-]
(pnu:Pnuc_0112 [4.1.3.-],       pnu:Pnuc_0111 [5.3.1.16])       => [2.4.2.-]
(pox:MB84_02490 [4.1.3.-],      pox:MB84_02495 [5.3.1.16])      => [2.4.2.-]
(ppk:U875_00645 [4.1.3.-],      ppk:U875_00640 [5.3.1.16])      => [2.4.2.-]
(ppul:RO07_06495 [4.1.3.-],     ppul:RO07_06500 [5.3.1.16])     => [2.4.2.-]
(pse:NH8B_3828 [4.1.3.-],       pse:NH8B_3829 [5.3.1.16])       => [2.4.2.-]
(pspu:NA29_02365 [4.1.3.-],     pspu:NA29_02370 [5.3.1.16])     => [2.4.2.-]
(pspw:BJG93_14435 [4.1.3.-],    pspw:BJG93_14430 [5.3.1.16])    => [2.4.2.-]
(pter:C2L65_14240 [4.1.3.-],    pter:C2L65_14245 [5.3.1.16])    => [2.4.2.-]
(ptx:ABW99_18420 [4.1.3.-],     ptx:ABW99_18415 [5.3.1.16])     => [2.4.2.-]
(put:PT7_3117 [4.1.3.-],        put:PT7_3118 [5.3.1.16])        => [2.4.2.-]
(pve:UC34_22565 [4.1.3.-],      pve:UC34_22570 [5.3.1.16])      => [2.4.2.-]
(rbn:RBXJA2T_15493 [4.1.3.-],   rbn:RBXJA2T_15488 [5.3.1.16])   => [2.4.2.-]
(rbu:PG1C_10135 [4.1.3.-],      rbu:PG1C_10140 [5.3.1.16])      => [2.4.2.-]
(rdp:RD2015_4184 [4.1.3.-],     rdp:RD2015_4185 [5.3.1.16])     => [2.4.2.-]
(reh:H16_A3410 [4.1.3.-],       reh:H16_A3411 [5.3.1.16])       => [2.4.2.-]
(reu:Reut_A3105 [4.1.3.-],      reu:Reut_A3106 [5.3.1.16])      => [2.4.2.-]
(rge:RGE_08640 [4.1.3.-],       rge:RGE_08630 [5.3.1.16])       => [2.4.2.-]
(rgu:A4W93_04900 [4.1.3.-],     rgu:A4W93_04895 [5.3.1.16])     => [2.4.2.-]
(rin:ACS15_3305 [4.1.3.-],      rin:ACS15_3306 [5.3.1.16])      => [2.4.2.-]
(rme:Rmet_3242 [4.1.3.-],       rme:Rmet_3243 [5.3.1.16])       => [2.4.2.-]
(rmn:TK49_00365 [4.1.3.-],      rmn:TK49_00370 [5.3.1.16])      => [2.4.2.-]
(rpi:Rpic_3223 [4.1.3.-],       rpi:Rpic_3224 [5.3.1.16])       => [2.4.2.-]
(rsb:RS694_16185 [4.1.3.-],     rsb:RS694_16190 [5.3.1.16])     => [2.4.2.-]
(rso:RSc2946 [4.1.3.-],         rso:RSc2947 [5.3.1.16])         => [2.4.2.-]
(salv:SALWKB2_1725 [4.1.3.-],   salv:SALWKB2_1727 [5.3.1.16])   => [2.4.2.-]
(sdr:SCD_n00591 [4.1.3.-],      sdr:SCD_n00590 [5.3.1.16])      => [2.4.2.-]
(shd:SUTH_02839 [4.1.3.-],      shd:SUTH_02840 [5.3.1.16])      => [2.4.2.-]
(sulf:CAP31_05295 [4.1.3.-],    sulf:CAP31_05300 [5.3.1.16])    => [2.4.2.-]
(tbd:Tbd_1708 [4.1.3.-],        tbd:Tbd_1709 [5.3.1.16])        => [2.4.2.-]
(tcl:Tchl_0637 [4.1.3.-],       tcl:Tchl_0636 [5.3.1.16])       => [2.4.2.-]
(thi:THI_1118 [4.1.3.-],        thi:THI_1117 [5.3.1.16])        => [2.4.2.-]
(thk:CCZ27_00850 [4.1.3.-],     thk:CCZ27_00845 [5.3.1.16])     => [2.4.2.-]
(thu:AC731_018095 [4.1.3.-],    thu:AC731_018090 [5.3.1.16])    => [2.4.2.-]
(tin:Tint_0867 [4.1.3.-],       tin:Tint_0866 [5.3.1.16])       => [2.4.2.-]
(vbo:CKY39_05960 [4.1.3.-],     vbo:CKY39_05935 [5.3.1.16])     => [2.4.2.-]
(vff:VITFI_CDS2687 [4.1.3.-],   vff:VITFI_CDS2688 [5.3.1.16])   => [2.4.2.-]
(zin:ZICARI_180 [4.1.3.-],      zin:ZICARI_181 [5.3.1.16])      => [2.4.2.-]
(aaa:Acav_1539 [6.2.1.1],       aaa:Acav_2415 [6.2.1.3])        => [3.1.2.-]
(aaa:Acav_1539 [6.2.1.1],       aaa:Acav_4494 [6.2.1.3])        => [3.1.2.-]
(aaa:Acav_2427 [6.2.1.1],       aaa:Acav_2415 [6.2.1.3])        => [3.1.2.-]
(aaa:Acav_2427 [6.2.1.1],       aaa:Acav_4494 [6.2.1.3])        => [3.1.2.-]
(aav:Aave_1499 [6.2.1.1],       aav:Aave_4574 [6.2.1.3])        => [3.1.2.-]
(achr:C2U31_13190 [6.2.1.1],    achr:C2U31_08890 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_13190 [6.2.1.1],    achr:C2U31_22425 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_13190 [6.2.1.1],    achr:C2U31_26190 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_13350 [6.2.1.1],    achr:C2U31_03265 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_13350 [6.2.1.1],    achr:C2U31_08890 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_13350 [6.2.1.1],    achr:C2U31_22425 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_13350 [6.2.1.1],    achr:C2U31_26190 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_21745 [6.2.1.1],    achr:C2U31_08890 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_21745 [6.2.1.1],    achr:C2U31_22425 [6.2.1.3])     => [3.1.2.-]
(achr:C2U31_21745 [6.2.1.1],    achr:C2U31_26190 [6.2.1.3])     => [3.1.2.-]
(acid:CBP33_07535 [6.2.1.1],    acid:CBP33_17730 [6.2.1.3])     => [3.1.2.-]
(acid:CBP33_08165 [6.2.1.1],    acid:CBP33_17730 [6.2.1.3])     => [3.1.2.-]
(acin:CBP34_07435 [6.2.1.1],    acin:CBP34_18350 [6.2.1.3])     => [3.1.2.-]
(acip:CBP36_08105 [6.2.1.1],    acip:CBP36_18010 [6.2.1.3])     => [3.1.2.-]
(ack:C380_15660 [6.2.1.1],      ack:C380_00030 [6.2.1.3])       => [3.1.2.-]
(ack:C380_15660 [6.2.1.1],      ack:C380_02255 [6.2.1.3])       => [3.1.2.-]
(ack:C380_15660 [6.2.1.1],      ack:C380_22580 [6.2.1.3])       => [3.1.2.-]
(acra:BSY15_48 [6.2.1.1],       acra:BSY15_1176 [6.2.1.3])      => [3.1.2.-]
(acra:BSY15_48 [6.2.1.1],       acra:BSY15_1452 [6.2.1.3])      => [3.1.2.-]
(acra:BSY15_48 [6.2.1.1],       acra:BSY15_5 [6.2.1.3])         => [3.1.2.-]
(adn:Alide_1147 [6.2.1.1],      adn:Alide_4154 [6.2.1.3])       => [3.1.2.-]
(adn:Alide_2935 [6.2.1.1],      adn:Alide_4154 [6.2.1.3])       => [3.1.2.-]
(adn:Alide_4206 [6.2.1.1],      adn:Alide_4154 [6.2.1.3])       => [3.1.2.-]
(adn:Alide_4322 [6.2.1.1],      adn:Alide_4154 [6.2.1.3])       => [3.1.2.-]
(adt:APT56_06955 [6.2.1.1],     adt:APT56_04460 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_06955 [6.2.1.1],     adt:APT56_20045 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_07095 [6.2.1.1],     adt:APT56_04460 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_07095 [6.2.1.1],     adt:APT56_20045 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_07095 [6.2.1.1],     adt:APT56_26880 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_10850 [6.2.1.1],     adt:APT56_04460 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_10850 [6.2.1.1],     adt:APT56_17615 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_10850 [6.2.1.1],     adt:APT56_20045 [6.2.1.3])      => [3.1.2.-]
(adt:APT56_10850 [6.2.1.1],     adt:APT56_26880 [6.2.1.3])      => [3.1.2.-]
(afa:UZ73_03200 [6.2.1.1],      afa:UZ73_06630 [6.2.1.3])       => [3.1.2.-]
(afa:UZ73_03200 [6.2.1.1],      afa:UZ73_11085 [6.2.1.3])       => [3.1.2.-]
(afa:UZ73_06130 [6.2.1.1],      afa:UZ73_06630 [6.2.1.3])       => [3.1.2.-]
(afa:UZ73_06130 [6.2.1.1],      afa:UZ73_09570 [6.2.1.3])       => [3.1.2.-]
(afa:UZ73_06130 [6.2.1.1],      afa:UZ73_11085 [6.2.1.3])       => [3.1.2.-]
(ais:BUW96_02335 [6.2.1.1],     ais:BUW96_03095 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_02335 [6.2.1.1],     ais:BUW96_11380 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_02335 [6.2.1.1],     ais:BUW96_11745 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_02335 [6.2.1.1],     ais:BUW96_21525 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_02335 [6.2.1.1],     ais:BUW96_24205 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18325 [6.2.1.1],     ais:BUW96_03095 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18325 [6.2.1.1],     ais:BUW96_11380 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18325 [6.2.1.1],     ais:BUW96_11745 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18325 [6.2.1.1],     ais:BUW96_21525 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18325 [6.2.1.1],     ais:BUW96_24205 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18505 [6.2.1.1],     ais:BUW96_03095 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18505 [6.2.1.1],     ais:BUW96_11380 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18505 [6.2.1.1],     ais:BUW96_11745 [6.2.1.3])      => [3.1.2.-]
(ais:BUW96_18505 [6.2.1.1],     ais:BUW96_21525 [6.2.1.3])      => [3.1.2.-]
(ajs:Ajs_1067 [6.2.1.1],        ajs:Ajs_3950 [6.2.1.3])         => [3.1.2.-]
(aka:TKWG_10060 [6.2.1.1],      aka:TKWG_23800 [6.2.1.3])       => [3.1.2.-]
(amim:MIM_c23610 [6.2.1.1],     amim:MIM_c01110 [6.2.1.3])      => [3.1.2.-]
(amim:MIM_c23610 [6.2.1.1],     amim:MIM_c23700 [6.2.1.3])      => [3.1.2.-]
(amim:MIM_c38630 [6.2.1.1],     amim:MIM_c01110 [6.2.1.3])      => [3.1.2.-]
(amim:MIM_c38630 [6.2.1.1],     amim:MIM_c07010 [6.2.1.3])      => [3.1.2.-]
(amim:MIM_c38630 [6.2.1.1],     amim:MIM_c23700 [6.2.1.3])      => [3.1.2.-]
(aoa:dqs_2558 [6.2.1.1],        aoa:dqs_1141 [6.2.1.3])         => [3.1.2.-]
(app:CAP2UW1_2247 [6.2.1.1],    app:CAP2UW1_1889 [6.2.1.3])     => [3.1.2.-]
(app:CAP2UW1_2247 [6.2.1.1],    app:CAP2UW1_3331 [6.2.1.3])     => [3.1.2.-]
(app:CAP2UW1_3755 [6.2.1.1],    app:CAP2UW1_1889 [6.2.1.3])     => [3.1.2.-]
(app:CAP2UW1_3755 [6.2.1.1],    app:CAP2UW1_3331 [6.2.1.3])     => [3.1.2.-]
(aql:BXU06_06255 [6.2.1.1],     aql:BXU06_05445 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_10110 [6.2.1.1],     asw:CVS48_02350 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_10110 [6.2.1.1],     asw:CVS48_23515 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_10110 [6.2.1.1],     asw:CVS48_23880 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_13690 [6.2.1.1],     asw:CVS48_02350 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_13690 [6.2.1.1],     asw:CVS48_23515 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_13690 [6.2.1.1],     asw:CVS48_23880 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_15660 [6.2.1.1],     asw:CVS48_02350 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_15660 [6.2.1.1],     asw:CVS48_07560 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_15660 [6.2.1.1],     asw:CVS48_23515 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_15660 [6.2.1.1],     asw:CVS48_23880 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_28150 [6.2.1.1],     asw:CVS48_02350 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_28150 [6.2.1.1],     asw:CVS48_23515 [6.2.1.3])      => [3.1.2.-]
(asw:CVS48_28150 [6.2.1.1],     asw:CVS48_23880 [6.2.1.3])      => [3.1.2.-]
(axy:AXYL_01580 [6.2.1.1],      axy:AXYL_00813 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01580 [6.2.1.1],      axy:AXYL_02583 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01580 [6.2.1.1],      axy:AXYL_04432 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01580 [6.2.1.1],      axy:AXYL_04504 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01616 [6.2.1.1],      axy:AXYL_00813 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01616 [6.2.1.1],      axy:AXYL_02583 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01616 [6.2.1.1],      axy:AXYL_04432 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01616 [6.2.1.1],      axy:AXYL_04504 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_01616 [6.2.1.1],      axy:AXYL_06189 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_02409 [6.2.1.1],      axy:AXYL_00813 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_02409 [6.2.1.1],      axy:AXYL_02583 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_02409 [6.2.1.1],      axy:AXYL_04432 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_02409 [6.2.1.1],      axy:AXYL_04504 [6.2.1.3])       => [3.1.2.-]
(axy:AXYL_02409 [6.2.1.1],      axy:AXYL_06189 [6.2.1.3])       => [3.1.2.-]
(aza:AZKH_0568 [6.2.1.1],       aza:AZKH_2502 [6.2.1.3])        => [3.1.2.-]
(aza:AZKH_0568 [6.2.1.1],       aza:AZKH_3122 [6.2.1.3])        => [3.1.2.-]
(aza:AZKH_0851 [6.2.1.1],       aza:AZKH_2502 [6.2.1.3])        => [3.1.2.-]
(aza:AZKH_0851 [6.2.1.1],       aza:AZKH_3122 [6.2.1.3])        => [3.1.2.-]
(aza:AZKH_1504 [6.2.1.1],       aza:AZKH_2502 [6.2.1.3])        => [3.1.2.-]
(aza:AZKH_1504 [6.2.1.1],       aza:AZKH_3122 [6.2.1.3])        => [3.1.2.-]
(aza:AZKH_1719 [6.2.1.1],       aza:AZKH_2502 [6.2.1.3])        => [3.1.2.-]
(aza:AZKH_1719 [6.2.1.1],       aza:AZKH_3122 [6.2.1.3])        => [3.1.2.-]
(azi:AzCIB_0750 [6.2.1.1],      azi:AzCIB_3050 [6.2.1.3])       => [3.1.2.-]
(azi:AzCIB_1014 [6.2.1.1],      azi:AzCIB_3050 [6.2.1.3])       => [3.1.2.-]
(azi:AzCIB_1325 [6.2.1.1],      azi:AzCIB_3050 [6.2.1.3])       => [3.1.2.-]
(azi:AzCIB_3999 [6.2.1.1],      azi:AzCIB_3050 [6.2.1.3])       => [3.1.2.-]
(azo:azo2414 [6.2.1.1],         azo:azo1033 [6.2.1.3])          => [3.1.2.-]
(bam:Bamb_1201 [6.2.1.1],       bam:Bamb_0451 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_1201 [6.2.1.1],       bam:Bamb_1416 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_1201 [6.2.1.1],       bam:Bamb_5782 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_2230 [6.2.1.1],       bam:Bamb_0451 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_2230 [6.2.1.1],       bam:Bamb_1416 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_2230 [6.2.1.1],       bam:Bamb_5782 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_4384 [6.2.1.1],       bam:Bamb_0451 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_4384 [6.2.1.1],       bam:Bamb_1416 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_4384 [6.2.1.1],       bam:Bamb_5782 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_5971 [6.2.1.1],       bam:Bamb_0451 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_5971 [6.2.1.1],       bam:Bamb_1416 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_5971 [6.2.1.1],       bam:Bamb_5782 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_6158 [6.2.1.1],       bam:Bamb_0451 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_6158 [6.2.1.1],       bam:Bamb_1416 [6.2.1.3])        => [3.1.2.-]
(bam:Bamb_6158 [6.2.1.1],       bam:Bamb_5782 [6.2.1.3])        => [3.1.2.-]
(bav:BAV1149 [6.2.1.1],         bav:BAV2858 [6.2.1.3])          => [3.1.2.-]
(bav:BAV1171 [6.2.1.1],         bav:BAV0187 [6.2.1.3])          => [3.1.2.-]
(bav:BAV1171 [6.2.1.1],         bav:BAV2858 [6.2.1.3])          => [3.1.2.-]
(bbag:E1O_05800 [6.2.1.1],      bbag:E1O_03600 [6.2.1.3])       => [3.1.2.-]
(bbr:BB0615 [6.2.1.1],          bbr:BB1125 [6.2.1.3])           => [3.1.2.-]
(bbr:BB0615 [6.2.1.1],          bbr:BB1789 [6.2.1.3])           => [3.1.2.-]
(bbr:BB0615 [6.2.1.1],          bbr:BB4175 [6.2.1.3])           => [3.1.2.-]
(bbr:BB1153 [6.2.1.1],          bbr:BB1125 [6.2.1.3])           => [3.1.2.-]
(bbr:BB1153 [6.2.1.1],          bbr:BB1789 [6.2.1.3])           => [3.1.2.-]
(bbr:BB1153 [6.2.1.1],          bbr:BB4175 [6.2.1.3])           => [3.1.2.-]
(bbr:BB3695 [6.2.1.1],          bbr:BB0233 [6.2.1.3])           => [3.1.2.-]
(bbr:BB3695 [6.2.1.1],          bbr:BB1125 [6.2.1.3])           => [3.1.2.-]
(bbr:BB3695 [6.2.1.1],          bbr:BB1789 [6.2.1.3])           => [3.1.2.-]
(bbr:BB3695 [6.2.1.1],          bbr:BB4175 [6.2.1.3])           => [3.1.2.-]
(bbr:BB3725 [6.2.1.1],          bbr:BB1125 [6.2.1.3])           => [3.1.2.-]
(bbr:BB3725 [6.2.1.1],          bbr:BB1789 [6.2.1.3])           => [3.1.2.-]
(bbr:BB3725 [6.2.1.1],          bbr:BB4175 [6.2.1.3])           => [3.1.2.-]
(bbro:BAU06_08060 [6.2.1.1],    bbro:BAU06_20275 [6.2.1.3])     => [3.1.2.-]
(bbro:BAU06_08195 [6.2.1.1],    bbro:BAU06_20275 [6.2.1.3])     => [3.1.2.-]
(bbro:BAU06_08195 [6.2.1.1],    bbro:BAU06_24265 [6.2.1.3])     => [3.1.2.-]
(bcai:K788_0002231 [6.2.1.1],   bcai:K788_0001161 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0002231 [6.2.1.1],   bcai:K788_0002435 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0002231 [6.2.1.1],   bcai:K788_0006803 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0002254 [6.2.1.1],   bcai:K788_0001161 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0002254 [6.2.1.1],   bcai:K788_0002435 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0002254 [6.2.1.1],   bcai:K788_0006803 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0002254 [6.2.1.1],   bcai:K788_0008577 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0008225 [6.2.1.1],   bcai:K788_0001161 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0008225 [6.2.1.1],   bcai:K788_0002435 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0008225 [6.2.1.1],   bcai:K788_0006803 [6.2.1.3])    => [3.1.2.-]
(bcai:K788_0008225 [6.2.1.1],   bcai:K788_0008577 [6.2.1.3])    => [3.1.2.-]
(bcn:Bcen_0835 [6.2.1.1],       bcn:Bcen_0064 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_0835 [6.2.1.1],       bcn:Bcen_1054 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_0835 [6.2.1.1],       bcn:Bcen_1557 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_1428 [6.2.1.1],       bcn:Bcen_0064 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_1428 [6.2.1.1],       bcn:Bcen_1054 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_1428 [6.2.1.1],       bcn:Bcen_1557 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_1601 [6.2.1.1],       bcn:Bcen_0064 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_1601 [6.2.1.1],       bcn:Bcen_1054 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_1601 [6.2.1.1],       bcn:Bcen_1557 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_3238 [6.2.1.1],       bcn:Bcen_0064 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_3238 [6.2.1.1],       bcn:Bcen_1054 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_3238 [6.2.1.1],       bcn:Bcen_1557 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_3405 [6.2.1.1],       bcn:Bcen_0064 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_3405 [6.2.1.1],       bcn:Bcen_1054 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_3405 [6.2.1.1],       bcn:Bcen_1557 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_5886 [6.2.1.1],       bcn:Bcen_0064 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_5886 [6.2.1.1],       bcn:Bcen_1054 [6.2.1.3])        => [3.1.2.-]
(bcn:Bcen_5886 [6.2.1.1],       bcn:Bcen_1557 [6.2.1.3])        => [3.1.2.-]
(bcon:NL30_00605 [6.2.1.1],     bcon:NL30_15565 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_00605 [6.2.1.1],     bcon:NL30_21345 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_00605 [6.2.1.1],     bcon:NL30_31680 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_00605 [6.2.1.1],     bcon:NL30_31795 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_01435 [6.2.1.1],     bcon:NL30_15565 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_01435 [6.2.1.1],     bcon:NL30_21345 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_01435 [6.2.1.1],     bcon:NL30_31680 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_01435 [6.2.1.1],     bcon:NL30_31795 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_09090 [6.2.1.1],     bcon:NL30_15565 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_09090 [6.2.1.1],     bcon:NL30_21345 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_09090 [6.2.1.1],     bcon:NL30_31680 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_09090 [6.2.1.1],     bcon:NL30_31795 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_25515 [6.2.1.1],     bcon:NL30_15565 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_25515 [6.2.1.1],     bcon:NL30_21345 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_25515 [6.2.1.1],     bcon:NL30_31680 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_25515 [6.2.1.1],     bcon:NL30_31795 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33335 [6.2.1.1],     bcon:NL30_15565 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33335 [6.2.1.1],     bcon:NL30_21345 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33335 [6.2.1.1],     bcon:NL30_31680 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33335 [6.2.1.1],     bcon:NL30_31795 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33430 [6.2.1.1],     bcon:NL30_15565 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33430 [6.2.1.1],     bcon:NL30_21345 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33430 [6.2.1.1],     bcon:NL30_31680 [6.2.1.3])      => [3.1.2.-]
(bcon:NL30_33430 [6.2.1.1],     bcon:NL30_31795 [6.2.1.3])      => [3.1.2.-]
(bct:GEM_1224 [6.2.1.1],        bct:GEM_1899 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_1224 [6.2.1.1],        bct:GEM_2236 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_1224 [6.2.1.1],        bct:GEM_2971 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_2137 [6.2.1.1],        bct:GEM_1899 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_2137 [6.2.1.1],        bct:GEM_2236 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_2137 [6.2.1.1],        bct:GEM_2971 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_3469 [6.2.1.1],        bct:GEM_1899 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_3469 [6.2.1.1],        bct:GEM_2236 [6.2.1.3])         => [3.1.2.-]
(bct:GEM_3469 [6.2.1.1],        bct:GEM_2971 [6.2.1.3])         => [3.1.2.-]
(bdf:WI26_06045 [6.2.1.1],      bdf:WI26_02280 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_06045 [6.2.1.1],      bdf:WI26_06990 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_06045 [6.2.1.1],      bdf:WI26_26935 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_10580 [6.2.1.1],      bdf:WI26_02280 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_10580 [6.2.1.1],      bdf:WI26_06990 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_10580 [6.2.1.1],      bdf:WI26_26935 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_23850 [6.2.1.1],      bdf:WI26_02280 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_23850 [6.2.1.1],      bdf:WI26_06990 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_23850 [6.2.1.1],      bdf:WI26_26935 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_28390 [6.2.1.1],      bdf:WI26_02280 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_28390 [6.2.1.1],      bdf:WI26_06990 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_28390 [6.2.1.1],      bdf:WI26_26935 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_29530 [6.2.1.1],      bdf:WI26_02280 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_29530 [6.2.1.1],      bdf:WI26_06990 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_29530 [6.2.1.1],      bdf:WI26_26935 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_30110 [6.2.1.1],      bdf:WI26_02280 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_30110 [6.2.1.1],      bdf:WI26_06990 [6.2.1.3])       => [3.1.2.-]
(bdf:WI26_30110 [6.2.1.1],      bdf:WI26_26935 [6.2.1.3])       => [3.1.2.-]
(bdl:AK34_1850 [6.2.1.1],       bdl:AK34_1636 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_1850 [6.2.1.1],       bdl:AK34_2595 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_3563 [6.2.1.1],       bdl:AK34_1636 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_3563 [6.2.1.1],       bdl:AK34_2595 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_5313 [6.2.1.1],       bdl:AK34_1636 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_5313 [6.2.1.1],       bdl:AK34_2595 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_5434 [6.2.1.1],       bdl:AK34_1636 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_5434 [6.2.1.1],       bdl:AK34_2595 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_925 [6.2.1.1],        bdl:AK34_1636 [6.2.1.3])        => [3.1.2.-]
(bdl:AK34_925 [6.2.1.1],        bdl:AK34_2595 [6.2.1.3])        => [3.1.2.-]
(beb:AEM42_13155 [6.2.1.1],     beb:AEM42_09160 [6.2.1.3])      => [3.1.2.-]
(beba:BWI17_05810 [6.2.1.1],    beba:BWI17_00995 [6.2.1.3])     => [3.1.2.-]
(beba:BWI17_05810 [6.2.1.1],    beba:BWI17_16015 [6.2.1.3])     => [3.1.2.-]
(beba:BWI17_20430 [6.2.1.1],    beba:BWI17_16015 [6.2.1.3])     => [3.1.2.-]
(bfn:OI25_335 [6.2.1.1],        bfn:OI25_1023 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_335 [6.2.1.1],        bfn:OI25_1934 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_335 [6.2.1.1],        bfn:OI25_3957 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_3495 [6.2.1.1],       bfn:OI25_1023 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_3495 [6.2.1.1],       bfn:OI25_1934 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_3495 [6.2.1.1],       bfn:OI25_3957 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_6882 [6.2.1.1],       bfn:OI25_1023 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_6882 [6.2.1.1],       bfn:OI25_1934 [6.2.1.3])        => [3.1.2.-]
(bfn:OI25_6882 [6.2.1.1],       bfn:OI25_3957 [6.2.1.3])        => [3.1.2.-]
(bfz:BAU07_17935 [6.2.1.1],     bfz:BAU07_06095 [6.2.1.3])      => [3.1.2.-]
(bfz:BAU07_17935 [6.2.1.1],     bfz:BAU07_12970 [6.2.1.3])      => [3.1.2.-]
(bfz:BAU07_17935 [6.2.1.1],     bfz:BAU07_19820 [6.2.1.3])      => [3.1.2.-]
(bfz:BAU07_17935 [6.2.1.1],     bfz:BAU07_24375 [6.2.1.3])      => [3.1.2.-]
(bfz:BAU07_18090 [6.2.1.1],     bfz:BAU07_06095 [6.2.1.3])      => [3.1.2.-]
(bfz:BAU07_18090 [6.2.1.1],     bfz:BAU07_12970 [6.2.1.3])      => [3.1.2.-]
(bfz:BAU07_18090 [6.2.1.1],     bfz:BAU07_19820 [6.2.1.3])      => [3.1.2.-]
(bgd:bgla_1g14050 [6.2.1.1],    bgd:bgla_1g04870 [6.2.1.3])     => [3.1.2.-]
(bgd:bgla_1g14050 [6.2.1.1],    bgd:bgla_1g18310 [6.2.1.3])     => [3.1.2.-]
(bgd:bgla_1g28680 [6.2.1.1],    bgd:bgla_1g04870 [6.2.1.3])     => [3.1.2.-]
(bgd:bgla_1g28680 [6.2.1.1],    bgd:bgla_1g18310 [6.2.1.3])     => [3.1.2.-]
(bgd:bgla_2g08940 [6.2.1.1],    bgd:bgla_1g04870 [6.2.1.3])     => [3.1.2.-]
(bgd:bgla_2g08940 [6.2.1.1],    bgd:bgla_1g18310 [6.2.1.3])     => [3.1.2.-]
(bge:BC1002_1033 [6.2.1.1],     bge:BC1002_1213 [6.2.1.3])      => [3.1.2.-]
(bge:BC1002_1033 [6.2.1.1],     bge:BC1002_2741 [6.2.1.3])      => [3.1.2.-]
(bge:BC1002_1985 [6.2.1.1],     bge:BC1002_1213 [6.2.1.3])      => [3.1.2.-]
(bge:BC1002_1985 [6.2.1.1],     bge:BC1002_2741 [6.2.1.3])      => [3.1.2.-]
(bge:BC1002_4209 [6.2.1.1],     bge:BC1002_1213 [6.2.1.3])      => [3.1.2.-]
(bge:BC1002_4209 [6.2.1.1],     bge:BC1002_2741 [6.2.1.3])      => [3.1.2.-]
(bgf:BC1003_2250 [6.2.1.1],     bgf:BC1003_1957 [6.2.1.3])      => [3.1.2.-]
(bgf:BC1003_2250 [6.2.1.1],     bgf:BC1003_3068 [6.2.1.3])      => [3.1.2.-]
(bgf:BC1003_5574 [6.2.1.1],     bgf:BC1003_1957 [6.2.1.3])      => [3.1.2.-]
(bgf:BC1003_5574 [6.2.1.1],     bgf:BC1003_3068 [6.2.1.3])      => [3.1.2.-]
(bgl:bglu_1g11900 [6.2.1.1],    bgl:bglu_1g04510 [6.2.1.3])     => [3.1.2.-]
(bgl:bglu_1g11900 [6.2.1.1],    bgl:bglu_1g19680 [6.2.1.3])     => [3.1.2.-]
(bgl:bglu_1g25360 [6.2.1.1],    bgl:bglu_1g04510 [6.2.1.3])     => [3.1.2.-]
(bgl:bglu_1g25360 [6.2.1.1],    bgl:bglu_1g19680 [6.2.1.3])     => [3.1.2.-]
(bgl:bglu_2g06270 [6.2.1.1],    bgl:bglu_1g04510 [6.2.1.3])     => [3.1.2.-]
(bgl:bglu_2g06270 [6.2.1.1],    bgl:bglu_1g19680 [6.2.1.3])     => [3.1.2.-]
(bho:D560_2346 [6.2.1.1],       bho:D560_0669 [6.2.1.3])        => [3.1.2.-]
(bho:D560_2346 [6.2.1.1],       bho:D560_2804 [6.2.1.3])        => [3.1.2.-]
(bho:D560_2371 [6.2.1.1],       bho:D560_0669 [6.2.1.3])        => [3.1.2.-]
(bho:D560_2371 [6.2.1.1],       bho:D560_2804 [6.2.1.3])        => [3.1.2.-]
(bhz:ACR54_02516 [6.2.1.1],     bhz:ACR54_01248 [6.2.1.3])      => [3.1.2.-]
(bhz:ACR54_02516 [6.2.1.1],     bhz:ACR54_03918 [6.2.1.3])      => [3.1.2.-]
(bhz:ACR54_03249 [6.2.1.1],     bhz:ACR54_00227 [6.2.1.3])      => [3.1.2.-]
(bhz:ACR54_03249 [6.2.1.1],     bhz:ACR54_01248 [6.2.1.3])      => [3.1.2.-]
(bhz:ACR54_03249 [6.2.1.1],     bhz:ACR54_03918 [6.2.1.3])      => [3.1.2.-]
(bhz:ACR54_03273 [6.2.1.1],     bhz:ACR54_01248 [6.2.1.3])      => [3.1.2.-]
(bhz:ACR54_03273 [6.2.1.1],     bhz:ACR54_03918 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_06590 [6.2.1.1],     blat:WK25_02625 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_06590 [6.2.1.1],     blat:WK25_07575 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_10660 [6.2.1.1],     blat:WK25_02625 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_10660 [6.2.1.1],     blat:WK25_07575 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_17835 [6.2.1.1],     blat:WK25_02625 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_17835 [6.2.1.1],     blat:WK25_07575 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_18560 [6.2.1.1],     blat:WK25_02625 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_18560 [6.2.1.1],     blat:WK25_07575 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_27095 [6.2.1.1],     blat:WK25_02625 [6.2.1.3])      => [3.1.2.-]
(blat:WK25_27095 [6.2.1.1],     blat:WK25_07575 [6.2.1.3])      => [3.1.2.-]
(bma:BMA0802 [6.2.1.1],         bma:BMA1134 [6.2.1.3])          => [3.1.2.-]
(bma:BMA0802 [6.2.1.1],         bma:BMA1276 [6.2.1.3])          => [3.1.2.-]
(bma:BMAA1794 [6.2.1.1],        bma:BMA1134 [6.2.1.3])          => [3.1.2.-]
(bma:BMAA1794 [6.2.1.1],        bma:BMA1276 [6.2.1.3])          => [3.1.2.-]
(bmec:WJ16_06275 [6.2.1.1],     bmec:WJ16_02355 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_06275 [6.2.1.1],     bmec:WJ16_07420 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_06275 [6.2.1.1],     bmec:WJ16_17220 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_11385 [6.2.1.1],     bmec:WJ16_02355 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_11385 [6.2.1.1],     bmec:WJ16_07420 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_11385 [6.2.1.1],     bmec:WJ16_17220 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_16590 [6.2.1.1],     bmec:WJ16_02355 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_16590 [6.2.1.1],     bmec:WJ16_07420 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_16590 [6.2.1.1],     bmec:WJ16_17220 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_29435 [6.2.1.1],     bmec:WJ16_02355 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_29435 [6.2.1.1],     bmec:WJ16_07420 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_29435 [6.2.1.1],     bmec:WJ16_17220 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_30235 [6.2.1.1],     bmec:WJ16_02355 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_30235 [6.2.1.1],     bmec:WJ16_07420 [6.2.1.3])      => [3.1.2.-]
(bmec:WJ16_30235 [6.2.1.1],     bmec:WJ16_17220 [6.2.1.3])      => [3.1.2.-]
(bmu:Bmul_1085 [6.2.1.1],       bmu:Bmul_1720 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_1085 [6.2.1.1],       bmu:Bmul_2848 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_1085 [6.2.1.1],       bmu:Bmul_5361 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_1992 [6.2.1.1],       bmu:Bmul_1720 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_1992 [6.2.1.1],       bmu:Bmul_2848 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_1992 [6.2.1.1],       bmu:Bmul_5361 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_3657 [6.2.1.1],       bmu:Bmul_1720 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_3657 [6.2.1.1],       bmu:Bmul_2848 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_3657 [6.2.1.1],       bmu:Bmul_5361 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_5345 [6.2.1.1],       bmu:Bmul_1720 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_5345 [6.2.1.1],       bmu:Bmul_2848 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_5345 [6.2.1.1],       bmu:Bmul_5361 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_5976 [6.2.1.1],       bmu:Bmul_1720 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_5976 [6.2.1.1],       bmu:Bmul_2848 [6.2.1.3])        => [3.1.2.-]
(bmu:Bmul_5976 [6.2.1.1],       bmu:Bmul_5361 [6.2.1.3])        => [3.1.2.-]
(boh:AKI39_07875 [6.2.1.1],     boh:AKI39_19520 [6.2.1.3])      => [3.1.2.-]
(boh:AKI39_08010 [6.2.1.1],     boh:AKI39_19520 [6.2.1.3])      => [3.1.2.-]
(boh:AKI39_08010 [6.2.1.1],     boh:AKI39_23190 [6.2.1.3])      => [3.1.2.-]
(boh:AKI39_21535 [6.2.1.1],     boh:AKI39_19520 [6.2.1.3])      => [3.1.2.-]
(bok:DM82_4474 [6.2.1.1],       bok:DM82_1061 [6.2.1.3])        => [3.1.2.-]
(bok:DM82_4474 [6.2.1.1],       bok:DM82_2705 [6.2.1.3])        => [3.1.2.-]
(bok:DM82_4713 [6.2.1.1],       bok:DM82_1061 [6.2.1.3])        => [3.1.2.-]
(bok:DM82_4713 [6.2.1.1],       bok:DM82_2705 [6.2.1.3])        => [3.1.2.-]
(bok:DM82_820 [6.2.1.1],        bok:DM82_1061 [6.2.1.3])        => [3.1.2.-]
(bok:DM82_820 [6.2.1.1],        bok:DM82_2705 [6.2.1.3])        => [3.1.2.-]
(bpa:BPP0609 [6.2.1.1],         bpa:BPP2338 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP0609 [6.2.1.1],         bpa:BPP3729 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP0944 [6.2.1.1],         bpa:BPP0915 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP0944 [6.2.1.1],         bpa:BPP2338 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP0944 [6.2.1.1],         bpa:BPP3729 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP3243 [6.2.1.1],         bpa:BPP0229 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP3243 [6.2.1.1],         bpa:BPP0915 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP3243 [6.2.1.1],         bpa:BPP2338 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP3243 [6.2.1.1],         bpa:BPP3729 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP3274 [6.2.1.1],         bpa:BPP0915 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP3274 [6.2.1.1],         bpa:BPP2338 [6.2.1.3])          => [3.1.2.-]
(bpa:BPP3274 [6.2.1.1],         bpa:BPP3729 [6.2.1.3])          => [3.1.2.-]
(bpdz:BBN53_06085 [6.2.1.1],    bpdz:BBN53_03455 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_06085 [6.2.1.1],    bpdz:BBN53_13595 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_06085 [6.2.1.1],    bpdz:BBN53_15510 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_06210 [6.2.1.1],    bpdz:BBN53_03455 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_06210 [6.2.1.1],    bpdz:BBN53_13595 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_06210 [6.2.1.1],    bpdz:BBN53_15510 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_06210 [6.2.1.1],    bpdz:BBN53_19600 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_09585 [6.2.1.1],    bpdz:BBN53_03455 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_09585 [6.2.1.1],    bpdz:BBN53_13595 [6.2.1.3])     => [3.1.2.-]
(bpdz:BBN53_09585 [6.2.1.1],    bpdz:BBN53_15510 [6.2.1.3])     => [3.1.2.-]
(bpe:BP2377 [6.2.1.1],          bpe:BP0532 [6.2.1.3])           => [3.1.2.-]
(bpe:BP2377 [6.2.1.1],          bpe:BP2811 [6.2.1.3])           => [3.1.2.-]
(bpe:BP2409 [6.2.1.1],          bpe:BP0532 [6.2.1.3])           => [3.1.2.-]
(bpe:BP2409 [6.2.1.1],          bpe:BP2811 [6.2.1.3])           => [3.1.2.-]
(bph:Bphy_1850 [6.2.1.1],       bph:Bphy_1704 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_1850 [6.2.1.1],       bph:Bphy_2685 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_1850 [6.2.1.1],       bph:Bphy_4871 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_1850 [6.2.1.1],       bph:Bphy_5806 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_1938 [6.2.1.1],       bph:Bphy_1704 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_1938 [6.2.1.1],       bph:Bphy_2685 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_1938 [6.2.1.1],       bph:Bphy_4871 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_1938 [6.2.1.1],       bph:Bphy_5806 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_4939 [6.2.1.1],       bph:Bphy_1704 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_4939 [6.2.1.1],       bph:Bphy_2685 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_4939 [6.2.1.1],       bph:Bphy_4871 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_4939 [6.2.1.1],       bph:Bphy_5806 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_5127 [6.2.1.1],       bph:Bphy_1704 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_5127 [6.2.1.1],       bph:Bphy_2685 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_5127 [6.2.1.1],       bph:Bphy_4871 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_5127 [6.2.1.1],       bph:Bphy_5806 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_7028 [6.2.1.1],       bph:Bphy_1704 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_7028 [6.2.1.1],       bph:Bphy_2685 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_7028 [6.2.1.1],       bph:Bphy_4871 [6.2.1.3])        => [3.1.2.-]
(bph:Bphy_7028 [6.2.1.1],       bph:Bphy_5806 [6.2.1.3])        => [3.1.2.-]
(bpla:bpln_1g12960 [6.2.1.1],   bpla:bpln_1g04230 [6.2.1.3])    => [3.1.2.-]
(bpla:bpln_1g12960 [6.2.1.1],   bpla:bpln_1g16140 [6.2.1.3])    => [3.1.2.-]
(bpla:bpln_1g26450 [6.2.1.1],   bpla:bpln_1g04230 [6.2.1.3])    => [3.1.2.-]
(bpla:bpln_1g26450 [6.2.1.1],   bpla:bpln_1g16140 [6.2.1.3])    => [3.1.2.-]
(bpla:bpln_2g08890 [6.2.1.1],   bpla:bpln_1g04230 [6.2.1.3])    => [3.1.2.-]
(bpla:bpln_2g08890 [6.2.1.1],   bpla:bpln_1g16140 [6.2.1.3])    => [3.1.2.-]
(bprc:D521_0689 [6.2.1.1],      bprc:D521_0877 [6.2.1.3])       => [3.1.2.-]
(bps:BPSL1380 [6.2.1.1],        bps:BPSL1734 [6.2.1.3])         => [3.1.2.-]
(bps:BPSL1380 [6.2.1.1],        bps:BPSL1883 [6.2.1.3])         => [3.1.2.-]
(bps:BPSL1380 [6.2.1.1],        bps:BPSL3037 [6.2.1.3])         => [3.1.2.-]
(bps:BPSS0375 [6.2.1.1],        bps:BPSL1734 [6.2.1.3])         => [3.1.2.-]
(bps:BPSS0375 [6.2.1.1],        bps:BPSL1883 [6.2.1.3])         => [3.1.2.-]
(bps:BPSS0375 [6.2.1.1],        bps:BPSL3037 [6.2.1.3])         => [3.1.2.-]
(bps:BPSS0618 [6.2.1.1],        bps:BPSL1734 [6.2.1.3])         => [3.1.2.-]
(bps:BPSS0618 [6.2.1.1],        bps:BPSL1883 [6.2.1.3])         => [3.1.2.-]
(bps:BPSS0618 [6.2.1.1],        bps:BPSL3037 [6.2.1.3])         => [3.1.2.-]
(bpsl:WS57_03130 [6.2.1.1],     bpsl:WS57_03575 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_03130 [6.2.1.1],     bpsl:WS57_14925 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_03130 [6.2.1.1],     bpsl:WS57_20190 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_03130 [6.2.1.1],     bpsl:WS57_26140 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_14235 [6.2.1.1],     bpsl:WS57_03575 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_14235 [6.2.1.1],     bpsl:WS57_14925 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_14235 [6.2.1.1],     bpsl:WS57_20190 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_14235 [6.2.1.1],     bpsl:WS57_26140 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_17070 [6.2.1.1],     bpsl:WS57_03575 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_17070 [6.2.1.1],     bpsl:WS57_14925 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_17070 [6.2.1.1],     bpsl:WS57_20190 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_17070 [6.2.1.1],     bpsl:WS57_26140 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_24300 [6.2.1.1],     bpsl:WS57_03575 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_24300 [6.2.1.1],     bpsl:WS57_14925 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_24300 [6.2.1.1],     bpsl:WS57_20190 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_24300 [6.2.1.1],     bpsl:WS57_26140 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_29735 [6.2.1.1],     bpsl:WS57_03575 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_29735 [6.2.1.1],     bpsl:WS57_14925 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_29735 [6.2.1.1],     bpsl:WS57_20190 [6.2.1.3])      => [3.1.2.-]
(bpsl:WS57_29735 [6.2.1.1],     bpsl:WS57_26140 [6.2.1.3])      => [3.1.2.-]
(bpt:Bpet1782 [6.2.1.1],        bpt:Bpet0716 [6.2.1.3])         => [3.1.2.-]
(bpt:Bpet1782 [6.2.1.1],        bpt:Bpet3416 [6.2.1.3])         => [3.1.2.-]
(bpt:Bpet1807 [6.2.1.1],        bpt:Bpet0716 [6.2.1.3])         => [3.1.2.-]
(bpt:Bpet1807 [6.2.1.1],        bpt:Bpet3416 [6.2.1.3])         => [3.1.2.-]
(bpt:Bpet1807 [6.2.1.1],        bpt:Bpet4743 [6.2.1.3])         => [3.1.2.-]
(bpx:BUPH_00398 [6.2.1.1],      bpx:BUPH_01937 [6.2.1.3])       => [3.1.2.-]
(bpx:BUPH_00398 [6.2.1.1],      bpx:BUPH_03649 [6.2.1.3])       => [3.1.2.-]
(bpx:BUPH_01685 [6.2.1.1],      bpx:BUPH_01937 [6.2.1.3])       => [3.1.2.-]
(bpx:BUPH_01685 [6.2.1.1],      bpx:BUPH_03649 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_1416 [6.2.1.1],      bpy:Bphyt_1672 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_1416 [6.2.1.1],      bpy:Bphyt_3482 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_2727 [6.2.1.1],      bpy:Bphyt_1672 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_2727 [6.2.1.1],      bpy:Bphyt_3482 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_5594 [6.2.1.1],      bpy:Bphyt_1672 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_5594 [6.2.1.1],      bpy:Bphyt_3482 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_5649 [6.2.1.1],      bpy:Bphyt_1672 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_5649 [6.2.1.1],      bpy:Bphyt_3482 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_6450 [6.2.1.1],      bpy:Bphyt_1672 [6.2.1.3])       => [3.1.2.-]
(bpy:Bphyt_6450 [6.2.1.1],      bpy:Bphyt_3482 [6.2.1.3])       => [3.1.2.-]
(bpyr:ABD05_00965 [6.2.1.1],    bpyr:ABD05_08330 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_00965 [6.2.1.1],    bpyr:ABD05_13465 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_00965 [6.2.1.1],    bpyr:ABD05_31075 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_12335 [6.2.1.1],    bpyr:ABD05_08330 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_12335 [6.2.1.1],    bpyr:ABD05_13465 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_12335 [6.2.1.1],    bpyr:ABD05_31075 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_24480 [6.2.1.1],    bpyr:ABD05_08330 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_24480 [6.2.1.1],    bpyr:ABD05_13465 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_24480 [6.2.1.1],    bpyr:ABD05_31075 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_34705 [6.2.1.1],    bpyr:ABD05_08330 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_34705 [6.2.1.1],    bpyr:ABD05_13465 [6.2.1.3])     => [3.1.2.-]
(bpyr:ABD05_34705 [6.2.1.1],    bpyr:ABD05_31075 [6.2.1.3])     => [3.1.2.-]
(brh:RBRH_03924 [6.2.1.1],      brh:RBRH_03271 [6.2.1.3])       => [3.1.2.-]
(bsem:WJ12_06460 [6.2.1.1],     bsem:WJ12_02375 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_06460 [6.2.1.1],     bsem:WJ12_07565 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_06460 [6.2.1.1],     bsem:WJ12_18115 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_11085 [6.2.1.1],     bsem:WJ12_02375 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_11085 [6.2.1.1],     bsem:WJ12_07565 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_11085 [6.2.1.1],     bsem:WJ12_18115 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_18680 [6.2.1.1],     bsem:WJ12_02375 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_18680 [6.2.1.1],     bsem:WJ12_07565 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_18680 [6.2.1.1],     bsem:WJ12_18115 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_30880 [6.2.1.1],     bsem:WJ12_02375 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_30880 [6.2.1.1],     bsem:WJ12_07565 [6.2.1.3])      => [3.1.2.-]
(bsem:WJ12_30880 [6.2.1.1],     bsem:WJ12_18115 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_06860 [6.2.1.1],     bstg:WT74_02680 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_06860 [6.2.1.1],     bstg:WT74_07750 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_06860 [6.2.1.1],     bstg:WT74_08015 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_06860 [6.2.1.1],     bstg:WT74_17055 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_11580 [6.2.1.1],     bstg:WT74_02680 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_11580 [6.2.1.1],     bstg:WT74_07750 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_11580 [6.2.1.1],     bstg:WT74_08015 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_11580 [6.2.1.1],     bstg:WT74_17055 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_16810 [6.2.1.1],     bstg:WT74_02680 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_16810 [6.2.1.1],     bstg:WT74_07750 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_16810 [6.2.1.1],     bstg:WT74_08015 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_16810 [6.2.1.1],     bstg:WT74_17055 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_29950 [6.2.1.1],     bstg:WT74_02680 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_29950 [6.2.1.1],     bstg:WT74_07750 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_29950 [6.2.1.1],     bstg:WT74_08015 [6.2.1.3])      => [3.1.2.-]
(bstg:WT74_29950 [6.2.1.1],     bstg:WT74_17055 [6.2.1.3])      => [3.1.2.-]
(bstl:BBJ41_05525 [6.2.1.1],    bstl:BBJ41_04440 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_05525 [6.2.1.1],    bstl:BBJ41_09605 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_05525 [6.2.1.1],    bstl:BBJ41_22510 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_05525 [6.2.1.1],    bstl:BBJ41_34650 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_05525 [6.2.1.1],    bstl:BBJ41_35480 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_18025 [6.2.1.1],    bstl:BBJ41_04440 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_18025 [6.2.1.1],    bstl:BBJ41_09605 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_18025 [6.2.1.1],    bstl:BBJ41_22510 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_18025 [6.2.1.1],    bstl:BBJ41_34650 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_18025 [6.2.1.1],    bstl:BBJ41_35480 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_24625 [6.2.1.1],    bstl:BBJ41_04440 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_24625 [6.2.1.1],    bstl:BBJ41_09605 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_24625 [6.2.1.1],    bstl:BBJ41_22510 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_24625 [6.2.1.1],    bstl:BBJ41_34650 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_24625 [6.2.1.1],    bstl:BBJ41_35480 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_34800 [6.2.1.1],    bstl:BBJ41_04440 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_34800 [6.2.1.1],    bstl:BBJ41_09605 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_34800 [6.2.1.1],    bstl:BBJ41_22510 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_34800 [6.2.1.1],    bstl:BBJ41_34650 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_34800 [6.2.1.1],    bstl:BBJ41_35480 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_38135 [6.2.1.1],    bstl:BBJ41_04440 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_38135 [6.2.1.1],    bstl:BBJ41_09605 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_38135 [6.2.1.1],    bstl:BBJ41_22510 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_38135 [6.2.1.1],    bstl:BBJ41_34650 [6.2.1.3])     => [3.1.2.-]
(bstl:BBJ41_38135 [6.2.1.1],    bstl:BBJ41_35480 [6.2.1.3])     => [3.1.2.-]
(bte:BTH_I2753 [6.2.1.1],       bte:BTH_I1106 [6.2.1.3])        => [3.1.2.-]
(bte:BTH_I2753 [6.2.1.1],       bte:BTH_I2529 [6.2.1.3])        => [3.1.2.-]
(bte:BTH_II0927 [6.2.1.1],      bte:BTH_I1106 [6.2.1.3])        => [3.1.2.-]
(bte:BTH_II0927 [6.2.1.1],      bte:BTH_I2529 [6.2.1.3])        => [3.1.2.-]
(bte:BTH_II1802 [6.2.1.1],      bte:BTH_I1106 [6.2.1.3])        => [3.1.2.-]
(bte:BTH_II1802 [6.2.1.1],      bte:BTH_I2529 [6.2.1.3])        => [3.1.2.-]
(bte:BTH_II2017 [6.2.1.1],      bte:BTH_I1106 [6.2.1.3])        => [3.1.2.-]
(bte:BTH_II2017 [6.2.1.1],      bte:BTH_I2529 [6.2.1.3])        => [3.1.2.-]
(btei:WS51_08135 [6.2.1.1],     btei:WS51_13100 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_08135 [6.2.1.1],     btei:WS51_17935 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_08135 [6.2.1.1],     btei:WS51_26430 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_16915 [6.2.1.1],     btei:WS51_13100 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_16915 [6.2.1.1],     btei:WS51_17935 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_16915 [6.2.1.1],     btei:WS51_26430 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_21320 [6.2.1.1],     btei:WS51_13100 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_21320 [6.2.1.1],     btei:WS51_17935 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_21320 [6.2.1.1],     btei:WS51_26430 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_27940 [6.2.1.1],     btei:WS51_13100 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_27940 [6.2.1.1],     btei:WS51_17935 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_27940 [6.2.1.1],     btei:WS51_26430 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_29345 [6.2.1.1],     btei:WS51_13100 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_29345 [6.2.1.1],     btei:WS51_17935 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_29345 [6.2.1.1],     btei:WS51_26430 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_29895 [6.2.1.1],     btei:WS51_13100 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_29895 [6.2.1.1],     btei:WS51_17935 [6.2.1.3])      => [3.1.2.-]
(btei:WS51_29895 [6.2.1.1],     btei:WS51_26430 [6.2.1.3])      => [3.1.2.-]
(btrm:SAMEA390648702598 [6.2.1.1],      btrm:SAMEA390648700527 [6.2.1.3])       => [3.1.2.-]
(btrm:SAMEA390648702598 [6.2.1.1],      btrm:SAMEA390648704147 [6.2.1.3])       => [3.1.2.-]
(btrm:SAMEA390648702622 [6.2.1.1],      btrm:SAMEA390648700527 [6.2.1.3])       => [3.1.2.-]
(btrm:SAMEA390648702622 [6.2.1.1],      btrm:SAMEA390648701436 [6.2.1.3])       => [3.1.2.-]
(btrm:SAMEA390648702622 [6.2.1.1],      btrm:SAMEA390648704147 [6.2.1.3])       => [3.1.2.-]
(bub:BW23_2675 [6.2.1.1],       bub:BW23_1198 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_2675 [6.2.1.1],       bub:BW23_181 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_2675 [6.2.1.1],       bub:BW23_214 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_2675 [6.2.1.1],       bub:BW23_6260 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_3395 [6.2.1.1],       bub:BW23_1198 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_3395 [6.2.1.1],       bub:BW23_181 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_3395 [6.2.1.1],       bub:BW23_214 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_3395 [6.2.1.1],       bub:BW23_6260 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_403 [6.2.1.1],        bub:BW23_1198 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_403 [6.2.1.1],        bub:BW23_181 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_403 [6.2.1.1],        bub:BW23_214 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_403 [6.2.1.1],        bub:BW23_6260 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_5613 [6.2.1.1],       bub:BW23_1198 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_5613 [6.2.1.1],       bub:BW23_214 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_5613 [6.2.1.1],       bub:BW23_6260 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_6237 [6.2.1.1],       bub:BW23_1198 [6.2.1.3])        => [3.1.2.-]
(bub:BW23_6237 [6.2.1.1],       bub:BW23_181 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_6237 [6.2.1.1],       bub:BW23_214 [6.2.1.3])         => [3.1.2.-]
(bub:BW23_6237 [6.2.1.1],       bub:BW23_6260 [6.2.1.3])        => [3.1.2.-]
(bud:AQ610_11680 [6.2.1.1],     bud:AQ610_02580 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_11680 [6.2.1.1],     bud:AQ610_10595 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_11680 [6.2.1.1],     bud:AQ610_12700 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_21505 [6.2.1.1],     bud:AQ610_02580 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_21505 [6.2.1.1],     bud:AQ610_10595 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_21505 [6.2.1.1],     bud:AQ610_12700 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_27650 [6.2.1.1],     bud:AQ610_02580 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_27650 [6.2.1.1],     bud:AQ610_10595 [6.2.1.3])      => [3.1.2.-]
(bud:AQ610_27650 [6.2.1.1],     bud:AQ610_12700 [6.2.1.3])      => [3.1.2.-]
(bue:BRPE67_ACDS09430 [6.2.1.1],bue:BRPE67_ACDS16560 [6.2.1.3]) => [3.1.2.-]
(bue:BRPE67_ACDS09430 [6.2.1.1],bue:BRPE67_ACDS23770 [6.2.1.3]) => [3.1.2.-]
(bue:BRPE67_BCDS14320 [6.2.1.1],bue:BRPE67_ACDS16560 [6.2.1.3]) => [3.1.2.-]
(bue:BRPE67_BCDS14320 [6.2.1.1],bue:BRPE67_ACDS23770 [6.2.1.3]) => [3.1.2.-]
(bue:BRPE67_DCDS01770 [6.2.1.1],bue:BRPE67_ACDS16560 [6.2.1.3]) => [3.1.2.-]
(bue:BRPE67_DCDS01770 [6.2.1.1],bue:BRPE67_ACDS23770 [6.2.1.3]) => [3.1.2.-]
(bue:BRPE67_DCDS07580 [6.2.1.1],bue:BRPE67_ACDS16560 [6.2.1.3]) => [3.1.2.-]
(bue:BRPE67_DCDS07580 [6.2.1.1],bue:BRPE67_ACDS23770 [6.2.1.3]) => [3.1.2.-]
(bug:BC1001_1157 [6.2.1.1],     bug:BC1001_1422 [6.2.1.3])      => [3.1.2.-]
(bug:BC1001_1157 [6.2.1.1],     bug:BC1001_3121 [6.2.1.3])      => [3.1.2.-]
(bug:BC1001_3824 [6.2.1.1],     bug:BC1001_1422 [6.2.1.3])      => [3.1.2.-]
(bug:BC1001_3824 [6.2.1.1],     bug:BC1001_3121 [6.2.1.3])      => [3.1.2.-]
(buk:MYA_1983 [6.2.1.1],        buk:MYA_0459 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_1983 [6.2.1.1],        buk:MYA_1375 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_1983 [6.2.1.1],        buk:MYA_5190 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_2950 [6.2.1.1],        buk:MYA_0459 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_2950 [6.2.1.1],        buk:MYA_1375 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_2950 [6.2.1.1],        buk:MYA_5190 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_5107 [6.2.1.1],        buk:MYA_0459 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_5107 [6.2.1.1],        buk:MYA_1375 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_5107 [6.2.1.1],        buk:MYA_5190 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_5963 [6.2.1.1],        buk:MYA_0459 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_5963 [6.2.1.1],        buk:MYA_1375 [6.2.1.3])         => [3.1.2.-]
(buk:MYA_5963 [6.2.1.1],        buk:MYA_5190 [6.2.1.3])         => [3.1.2.-]
(bul:BW21_2470 [6.2.1.1],       bul:BW21_2247 [6.2.1.3])        => [3.1.2.-]
(bul:BW21_2470 [6.2.1.1],       bul:BW21_2684 [6.2.1.3])        => [3.1.2.-]
(bul:BW21_2470 [6.2.1.1],       bul:BW21_637 [6.2.1.3])         => [3.1.2.-]
(bul:BW21_3880 [6.2.1.1],       bul:BW21_2247 [6.2.1.3])        => [3.1.2.-]
(bul:BW21_3880 [6.2.1.1],       bul:BW21_2684 [6.2.1.3])        => [3.1.2.-]
(bul:BW21_3880 [6.2.1.1],       bul:BW21_637 [6.2.1.3])         => [3.1.2.-]
(bul:BW21_5112 [6.2.1.1],       bul:BW21_2247 [6.2.1.3])        => [3.1.2.-]
(bul:BW21_5112 [6.2.1.1],       bul:BW21_2684 [6.2.1.3])        => [3.1.2.-]
(bul:BW21_5112 [6.2.1.1],       bul:BW21_637 [6.2.1.3])         => [3.1.2.-]
(buo:BRPE64_ACDS10530 [6.2.1.1],buo:BRPE64_ACDS16570 [6.2.1.3]) => [3.1.2.-]
(buo:BRPE64_ACDS10530 [6.2.1.1],buo:BRPE64_ACDS24290 [6.2.1.3]) => [3.1.2.-]
(buo:BRPE64_BCDS02730 [6.2.1.1],buo:BRPE64_ACDS16570 [6.2.1.3]) => [3.1.2.-]
(buo:BRPE64_BCDS02730 [6.2.1.1],buo:BRPE64_ACDS24290 [6.2.1.3]) => [3.1.2.-]
(buo:BRPE64_DCDS01300 [6.2.1.1],buo:BRPE64_ACDS16570 [6.2.1.3]) => [3.1.2.-]
(buo:BRPE64_DCDS01300 [6.2.1.1],buo:BRPE64_ACDS24290 [6.2.1.3]) => [3.1.2.-]
(buq:AC233_05760 [6.2.1.1],     buq:AC233_09270 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_05760 [6.2.1.1],     buq:AC233_15850 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_09565 [6.2.1.1],     buq:AC233_09270 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_09565 [6.2.1.1],     buq:AC233_15850 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_09565 [6.2.1.1],     buq:AC233_29570 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_21460 [6.2.1.1],     buq:AC233_09270 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_21460 [6.2.1.1],     buq:AC233_15850 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_21460 [6.2.1.1],     buq:AC233_29570 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_31115 [6.2.1.1],     buq:AC233_09270 [6.2.1.3])      => [3.1.2.-]
(buq:AC233_31115 [6.2.1.1],     buq:AC233_15850 [6.2.1.3])      => [3.1.2.-]
(bur:Bcep18194_A4459 [6.2.1.1], bur:Bcep18194_A3633 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A4459 [6.2.1.1], bur:Bcep18194_A4674 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A4459 [6.2.1.1], bur:Bcep18194_C6739 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A4459 [6.2.1.1], bur:Bcep18194_C6801 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A4459 [6.2.1.1], bur:Bcep18194_C6813 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A5520 [6.2.1.1], bur:Bcep18194_A3633 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A5520 [6.2.1.1], bur:Bcep18194_A4674 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A5520 [6.2.1.1], bur:Bcep18194_C6739 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A5520 [6.2.1.1], bur:Bcep18194_C6801 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_A5520 [6.2.1.1], bur:Bcep18194_C6813 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_B0715 [6.2.1.1], bur:Bcep18194_A3633 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_B0715 [6.2.1.1], bur:Bcep18194_A4674 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_B0715 [6.2.1.1], bur:Bcep18194_C6739 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_B0715 [6.2.1.1], bur:Bcep18194_C6801 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_B0715 [6.2.1.1], bur:Bcep18194_C6813 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C6650 [6.2.1.1], bur:Bcep18194_A3633 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C6650 [6.2.1.1], bur:Bcep18194_A4674 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C6650 [6.2.1.1], bur:Bcep18194_C6739 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C6650 [6.2.1.1], bur:Bcep18194_C6801 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C6650 [6.2.1.1], bur:Bcep18194_C6813 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7155 [6.2.1.1], bur:Bcep18194_A3633 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7155 [6.2.1.1], bur:Bcep18194_A4674 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7155 [6.2.1.1], bur:Bcep18194_C6739 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7155 [6.2.1.1], bur:Bcep18194_C6801 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7155 [6.2.1.1], bur:Bcep18194_C6813 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7333 [6.2.1.1], bur:Bcep18194_A3633 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7333 [6.2.1.1], bur:Bcep18194_A4674 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7333 [6.2.1.1], bur:Bcep18194_C6739 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7333 [6.2.1.1], bur:Bcep18194_C6801 [6.2.1.3])  => [3.1.2.-]
(bur:Bcep18194_C7333 [6.2.1.1], bur:Bcep18194_C6813 [6.2.1.3])  => [3.1.2.-]
(buz:AYM40_05675 [6.2.1.1],     buz:AYM40_08245 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_05675 [6.2.1.1],     buz:AYM40_18185 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_05675 [6.2.1.1],     buz:AYM40_27575 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_10310 [6.2.1.1],     buz:AYM40_08245 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_10310 [6.2.1.1],     buz:AYM40_18185 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_10310 [6.2.1.1],     buz:AYM40_27575 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_27855 [6.2.1.1],     buz:AYM40_08245 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_27855 [6.2.1.1],     buz:AYM40_18185 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_27855 [6.2.1.1],     buz:AYM40_27575 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_28435 [6.2.1.1],     buz:AYM40_08245 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_28435 [6.2.1.1],     buz:AYM40_18185 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_28435 [6.2.1.1],     buz:AYM40_27575 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_32775 [6.2.1.1],     buz:AYM40_08245 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_32775 [6.2.1.1],     buz:AYM40_18185 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_32775 [6.2.1.1],     buz:AYM40_27575 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_36710 [6.2.1.1],     buz:AYM40_08245 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_36710 [6.2.1.1],     buz:AYM40_18185 [6.2.1.3])      => [3.1.2.-]
(buz:AYM40_36710 [6.2.1.1],     buz:AYM40_27575 [6.2.1.3])      => [3.1.2.-]
(bvi:Bcep1808_2277 [6.2.1.1],   bvi:Bcep1808_0523 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_2277 [6.2.1.1],   bvi:Bcep1808_1500 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_2277 [6.2.1.1],   bvi:Bcep1808_5638 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_3336 [6.2.1.1],   bvi:Bcep1808_0523 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_3336 [6.2.1.1],   bvi:Bcep1808_1500 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_3336 [6.2.1.1],   bvi:Bcep1808_5638 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_5505 [6.2.1.1],   bvi:Bcep1808_0523 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_5505 [6.2.1.1],   bvi:Bcep1808_1500 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_5505 [6.2.1.1],   bvi:Bcep1808_5638 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_6566 [6.2.1.1],   bvi:Bcep1808_0523 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_6566 [6.2.1.1],   bvi:Bcep1808_1500 [6.2.1.3])    => [3.1.2.-]
(bvi:Bcep1808_6566 [6.2.1.1],   bvi:Bcep1808_5638 [6.2.1.3])    => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_A0474 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_A2746 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_A2778 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_B0702 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_B2539 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_C0318 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_C0707 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1395 [6.2.1.1],       bxe:Bxe_C0867 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1862 [6.2.1.1],       bxe:Bxe_A0474 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1862 [6.2.1.1],       bxe:Bxe_A2746 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1862 [6.2.1.1],       bxe:Bxe_A2778 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1862 [6.2.1.1],       bxe:Bxe_B0702 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1862 [6.2.1.1],       bxe:Bxe_C0318 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A1862 [6.2.1.1],       bxe:Bxe_C0867 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A2769 [6.2.1.1],       bxe:Bxe_A0474 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A2769 [6.2.1.1],       bxe:Bxe_A2778 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A2769 [6.2.1.1],       bxe:Bxe_C0867 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3113 [6.2.1.1],       bxe:Bxe_A0474 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3113 [6.2.1.1],       bxe:Bxe_A2746 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3113 [6.2.1.1],       bxe:Bxe_A2778 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3113 [6.2.1.1],       bxe:Bxe_B0702 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3113 [6.2.1.1],       bxe:Bxe_B2539 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3113 [6.2.1.1],       bxe:Bxe_C0867 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_A0474 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_A2746 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_A2778 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_B0702 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_B2539 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_C0318 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_C0707 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_A3573 [6.2.1.1],       bxe:Bxe_C0867 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_B1085 [6.2.1.1],       bxe:Bxe_A0474 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_B1085 [6.2.1.1],       bxe:Bxe_A2746 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_B1085 [6.2.1.1],       bxe:Bxe_A2778 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_B1085 [6.2.1.1],       bxe:Bxe_B2539 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_B1085 [6.2.1.1],       bxe:Bxe_C0318 [6.2.1.3])        => [3.1.2.-]
(bxe:Bxe_B1085 [6.2.1.1],       bxe:Bxe_C0867 [6.2.1.3])        => [3.1.2.-]
(byi:BYI23_A009340 [6.2.1.1],   byi:BYI23_A016100 [6.2.1.3])    => [3.1.2.-]
(byi:BYI23_A009340 [6.2.1.1],   byi:BYI23_A023010 [6.2.1.3])    => [3.1.2.-]
(byi:BYI23_B010190 [6.2.1.1],   byi:BYI23_A016100 [6.2.1.3])    => [3.1.2.-]
(byi:BYI23_B010190 [6.2.1.1],   byi:BYI23_A023010 [6.2.1.3])    => [3.1.2.-]
(byi:BYI23_D005770 [6.2.1.1],   byi:BYI23_A023010 [6.2.1.3])    => [3.1.2.-]
(byi:BYI23_D013080 [6.2.1.1],   byi:BYI23_A016100 [6.2.1.3])    => [3.1.2.-]
(byi:BYI23_D013080 [6.2.1.1],   byi:BYI23_A023010 [6.2.1.3])    => [3.1.2.-]
(care:LT85_1494 [6.2.1.1],      care:LT85_4543 [6.2.1.3])       => [3.1.2.-]
(care:LT85_1494 [6.2.1.1],      care:LT85_4544 [6.2.1.3])       => [3.1.2.-]
(care:LT85_3863 [6.2.1.1],      care:LT85_4543 [6.2.1.3])       => [3.1.2.-]
(care:LT85_3863 [6.2.1.1],      care:LT85_4544 [6.2.1.3])       => [3.1.2.-]
(cbaa:SRAA_1154 [6.2.1.1],      cbaa:SRAA_1887 [6.2.1.3])       => [3.1.2.-]
(cbaa:SRAA_1154 [6.2.1.1],      cbaa:SRAA_2285 [6.2.1.3])       => [3.1.2.-]
(cbaa:SRAA_1169 [6.2.1.1],      cbaa:SRAA_1887 [6.2.1.3])       => [3.1.2.-]
(cbaa:SRAA_1169 [6.2.1.1],      cbaa:SRAA_2285 [6.2.1.3])       => [3.1.2.-]
(cbab:SMCB_1048 [6.2.1.1],      cbab:SMCB_0206 [6.2.1.3])       => [3.1.2.-]
(cbab:SMCB_1048 [6.2.1.1],      cbab:SMCB_2068 [6.2.1.3])       => [3.1.2.-]
(cbab:SMCB_1048 [6.2.1.1],      cbab:SMCB_2310 [6.2.1.3])       => [3.1.2.-]
(cbab:SMCB_1063 [6.2.1.1],      cbab:SMCB_0206 [6.2.1.3])       => [3.1.2.-]
(cbab:SMCB_1063 [6.2.1.1],      cbab:SMCB_2310 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m1282 [6.2.1.1],      cbw:RR42_m1900 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m1282 [6.2.1.1],      cbw:RR42_m3695 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m1282 [6.2.1.1],      cbw:RR42_m3772 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m1282 [6.2.1.1],      cbw:RR42_s0903 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m1282 [6.2.1.1],      cbw:RR42_s1721 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m1282 [6.2.1.1],      cbw:RR42_s1812 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2146 [6.2.1.1],      cbw:RR42_m1900 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2146 [6.2.1.1],      cbw:RR42_m3695 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2146 [6.2.1.1],      cbw:RR42_m3772 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2146 [6.2.1.1],      cbw:RR42_s0903 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2146 [6.2.1.1],      cbw:RR42_s1721 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2146 [6.2.1.1],      cbw:RR42_s1812 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2818 [6.2.1.1],      cbw:RR42_m1900 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2818 [6.2.1.1],      cbw:RR42_m3695 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2818 [6.2.1.1],      cbw:RR42_m3772 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2818 [6.2.1.1],      cbw:RR42_s0903 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_m2818 [6.2.1.1],      cbw:RR42_s1721 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0395 [6.2.1.1],      cbw:RR42_m1900 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0395 [6.2.1.1],      cbw:RR42_m3695 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0395 [6.2.1.1],      cbw:RR42_m3772 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0395 [6.2.1.1],      cbw:RR42_s0903 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0395 [6.2.1.1],      cbw:RR42_s1721 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0838 [6.2.1.1],      cbw:RR42_m1900 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0838 [6.2.1.1],      cbw:RR42_m3695 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0838 [6.2.1.1],      cbw:RR42_m3772 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0838 [6.2.1.1],      cbw:RR42_s0903 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s0838 [6.2.1.1],      cbw:RR42_s1721 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s3042 [1.1.1.35],     cbw:RR42_m1900 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s3042 [1.1.1.35],     cbw:RR42_m3695 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s3042 [1.1.1.35],     cbw:RR42_m3772 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s3042 [1.1.1.35],     cbw:RR42_s0903 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s3042 [1.1.1.35],     cbw:RR42_s1721 [6.2.1.3])       => [3.1.2.-]
(cbw:RR42_s3042 [1.1.1.35],     cbw:RR42_s1812 [6.2.1.3])       => [3.1.2.-]
(ccup:BKK81_08790 [6.2.1.1],    ccup:BKK81_17645 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_08790 [6.2.1.1],    ccup:BKK81_18280 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_08790 [6.2.1.1],    ccup:BKK81_30420 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_08790 [6.2.1.1],    ccup:BKK81_30470 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_08790 [6.2.1.1],    ccup:BKK81_30825 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_08790 [6.2.1.1],    ccup:BKK81_33775 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_14455 [6.2.1.1],    ccup:BKK81_17645 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_14455 [6.2.1.1],    ccup:BKK81_18280 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_14455 [6.2.1.1],    ccup:BKK81_30420 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_14455 [6.2.1.1],    ccup:BKK81_30470 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_14455 [6.2.1.1],    ccup:BKK81_30825 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_19195 [6.2.1.1],    ccup:BKK81_17645 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_19195 [6.2.1.1],    ccup:BKK81_18280 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_19195 [6.2.1.1],    ccup:BKK81_30420 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_19195 [6.2.1.1],    ccup:BKK81_30470 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_19195 [6.2.1.1],    ccup:BKK81_30825 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_19195 [6.2.1.1],    ccup:BKK81_33775 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_31020 [6.2.1.1],    ccup:BKK81_17645 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_31020 [6.2.1.1],    ccup:BKK81_18280 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_31020 [6.2.1.1],    ccup:BKK81_30420 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_31020 [6.2.1.1],    ccup:BKK81_30470 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_31020 [6.2.1.1],    ccup:BKK81_30825 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_31020 [6.2.1.1],    ccup:BKK81_33775 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_33765 [6.2.1.1],    ccup:BKK81_08345 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_33765 [6.2.1.1],    ccup:BKK81_17645 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_33765 [6.2.1.1],    ccup:BKK81_18280 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_33765 [6.2.1.1],    ccup:BKK81_30420 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_33765 [6.2.1.1],    ccup:BKK81_30470 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_33765 [6.2.1.1],    ccup:BKK81_30825 [6.2.1.3])     => [3.1.2.-]
(ccup:BKK81_33765 [6.2.1.1],    ccup:BKK81_33775 [6.2.1.3])     => [3.1.2.-]
(cdn:BN940_04501 [6.2.1.1],     cdn:BN940_00571 [6.2.1.3])      => [3.1.2.-]
(cdn:BN940_04501 [6.2.1.1],     cdn:BN940_03141 [6.2.1.3])      => [3.1.2.-]
(cdn:BN940_04501 [6.2.1.1],     cdn:BN940_05616 [6.2.1.3])      => [3.1.2.-]
(cdn:BN940_05571 [6.2.1.1],     cdn:BN940_00571 [6.2.1.3])      => [3.1.2.-]
(cfu:CFU_3071 [6.2.1.1],        cfu:CFU_3992 [6.2.1.3])         => [3.1.2.-]
(cfu:CFU_3350 [6.2.1.1],        cfu:CFU_3992 [6.2.1.3])         => [3.1.2.-]
(cfu:CFU_3350 [6.2.1.1],        cfu:CFU_3993 [6.2.1.3])         => [3.1.2.-]
(cgd:CR3_1824 [6.2.1.1],        cgd:CR3_0016 [6.2.1.3])         => [3.1.2.-]
(cgd:CR3_1824 [6.2.1.1],        cgd:CR3_2422 [6.2.1.3])         => [3.1.2.-]
(cgd:CR3_1824 [6.2.1.1],        cgd:CR3_2491 [6.2.1.3])         => [3.1.2.-]
(chro:CXB49_05110 [6.2.1.1],    chro:CXB49_20175 [6.2.1.3])     => [3.1.2.-]
(cke:B5M06_16310 [6.2.1.1],     cke:B5M06_05915 [6.2.1.3])      => [3.1.2.-]
(cpra:CPter91_1450 [6.2.1.1],   cpra:CPter91_4969 [6.2.1.3])    => [3.1.2.-]
(cpra:CPter91_1450 [6.2.1.1],   cpra:CPter91_4970 [6.2.1.3])    => [3.1.2.-]
(cpra:CPter91_4119 [6.2.1.1],   cpra:CPter91_4969 [6.2.1.3])    => [3.1.2.-]
(cpra:CPter91_4119 [6.2.1.1],   cpra:CPter91_4970 [6.2.1.3])    => [3.1.2.-]
(cser:CCO03_12400 [6.2.1.1],    cser:CCO03_06145 [6.2.1.3])     => [3.1.2.-]
(cser:CCO03_15840 [6.2.1.1],    cser:CCO03_06145 [6.2.1.3])     => [3.1.2.-]
(cti:RALTA_A1174 [6.2.1.1],     cti:RALTA_A0225 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A1174 [6.2.1.1],     cti:RALTA_A2744 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A1174 [6.2.1.1],     cti:RALTA_A2808 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A1174 [6.2.1.1],     cti:RALTA_A2852 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A1174 [6.2.1.1],     cti:RALTA_B1144 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A2028 [6.2.1.1],     cti:RALTA_A2744 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A2028 [6.2.1.1],     cti:RALTA_A2808 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A2028 [6.2.1.1],     cti:RALTA_A2852 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_A2028 [6.2.1.1],     cti:RALTA_B1144 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_B0925 [6.2.1.1],     cti:RALTA_A2744 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_B0925 [6.2.1.1],     cti:RALTA_A2808 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_B0925 [6.2.1.1],     cti:RALTA_A2852 [6.2.1.3])      => [3.1.2.-]
(cti:RALTA_B0925 [6.2.1.1],     cti:RALTA_B1144 [6.2.1.3])      => [3.1.2.-]
(ctt:CtCNB1_1397 [6.2.1.1],     ctt:CtCNB1_4404 [6.2.1.3])      => [3.1.2.-]
(ctt:CtCNB1_1397 [6.2.1.1],     ctt:CtCNB1_4619 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_06290 [6.2.1.1],     cuh:BJN34_15765 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_06290 [6.2.1.1],     cuh:BJN34_17615 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_06290 [6.2.1.1],     cuh:BJN34_17950 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_06290 [6.2.1.1],     cuh:BJN34_25525 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_06290 [6.2.1.1],     cuh:BJN34_26490 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_06290 [6.2.1.1],     cuh:BJN34_27820 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_09830 [6.2.1.1],     cuh:BJN34_15765 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_09830 [6.2.1.1],     cuh:BJN34_17615 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_09830 [6.2.1.1],     cuh:BJN34_26490 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_09830 [6.2.1.1],     cuh:BJN34_27820 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_13560 [6.2.1.1],     cuh:BJN34_15765 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_13560 [6.2.1.1],     cuh:BJN34_17615 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_13560 [6.2.1.1],     cuh:BJN34_17950 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_13560 [6.2.1.1],     cuh:BJN34_25525 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_13560 [6.2.1.1],     cuh:BJN34_26490 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_13560 [6.2.1.1],     cuh:BJN34_27820 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_22305 [6.2.1.1],     cuh:BJN34_15765 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_22305 [6.2.1.1],     cuh:BJN34_17615 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_22305 [6.2.1.1],     cuh:BJN34_17950 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_22305 [6.2.1.1],     cuh:BJN34_25525 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_22305 [6.2.1.1],     cuh:BJN34_26490 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_22305 [6.2.1.1],     cuh:BJN34_27820 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_27195 [6.2.1.1],     cuh:BJN34_15765 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_27195 [6.2.1.1],     cuh:BJN34_17615 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_27195 [6.2.1.1],     cuh:BJN34_17950 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_27195 [6.2.1.1],     cuh:BJN34_25525 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_27195 [6.2.1.1],     cuh:BJN34_26490 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_27195 [6.2.1.1],     cuh:BJN34_27820 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_31265 [6.2.1.1],     cuh:BJN34_17615 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_31265 [6.2.1.1],     cuh:BJN34_17950 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_31265 [6.2.1.1],     cuh:BJN34_25525 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_31265 [6.2.1.1],     cuh:BJN34_26490 [6.2.1.3])      => [3.1.2.-]
(cuh:BJN34_31265 [6.2.1.1],     cuh:BJN34_27820 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_08100 [6.2.1.1],     cup:BKK80_18655 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_08100 [6.2.1.1],     cup:BKK80_19135 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_08100 [6.2.1.1],     cup:BKK80_23215 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_08100 [6.2.1.1],     cup:BKK80_25530 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_08100 [6.2.1.1],     cup:BKK80_25885 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_08100 [6.2.1.1],     cup:BKK80_25935 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_15405 [6.2.1.1],     cup:BKK80_18655 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_15405 [6.2.1.1],     cup:BKK80_19135 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_15405 [6.2.1.1],     cup:BKK80_23215 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_15405 [6.2.1.1],     cup:BKK80_25530 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_15405 [6.2.1.1],     cup:BKK80_25885 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_15405 [6.2.1.1],     cup:BKK80_25935 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_22745 [6.2.1.1],     cup:BKK80_18655 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_22745 [6.2.1.1],     cup:BKK80_19135 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_22745 [6.2.1.1],     cup:BKK80_23215 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_22745 [6.2.1.1],     cup:BKK80_25530 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_22745 [6.2.1.1],     cup:BKK80_25885 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_22745 [6.2.1.1],     cup:BKK80_25935 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_25330 [6.2.1.1],     cup:BKK80_18655 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_25330 [6.2.1.1],     cup:BKK80_19135 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_25330 [6.2.1.1],     cup:BKK80_23215 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_25330 [6.2.1.1],     cup:BKK80_25530 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_25330 [6.2.1.1],     cup:BKK80_25885 [6.2.1.3])      => [3.1.2.-]
(cup:BKK80_25330 [6.2.1.1],     cup:BKK80_25935 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_04040 [6.2.1.1],     cuu:BKK79_12910 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_04040 [6.2.1.1],     cuu:BKK79_13395 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_04040 [6.2.1.1],     cuu:BKK79_28520 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_04040 [6.2.1.1],     cuu:BKK79_31405 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_04040 [6.2.1.1],     cuu:BKK79_31760 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_04040 [6.2.1.1],     cuu:BKK79_31810 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_17545 [6.2.1.1],     cuu:BKK79_12910 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_17545 [6.2.1.1],     cuu:BKK79_13395 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_17545 [6.2.1.1],     cuu:BKK79_28520 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_17545 [6.2.1.1],     cuu:BKK79_31405 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_17545 [6.2.1.1],     cuu:BKK79_31760 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_17545 [6.2.1.1],     cuu:BKK79_31810 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_28020 [6.2.1.1],     cuu:BKK79_12910 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_28020 [6.2.1.1],     cuu:BKK79_13395 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_28020 [6.2.1.1],     cuu:BKK79_28520 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_28020 [6.2.1.1],     cuu:BKK79_31405 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_28020 [6.2.1.1],     cuu:BKK79_31760 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_28020 [6.2.1.1],     cuu:BKK79_31810 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_31040 [6.2.1.1],     cuu:BKK79_12910 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_31040 [6.2.1.1],     cuu:BKK79_13395 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_31040 [6.2.1.1],     cuu:BKK79_28520 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_31040 [6.2.1.1],     cuu:BKK79_31405 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_31040 [6.2.1.1],     cuu:BKK79_31760 [6.2.1.3])      => [3.1.2.-]
(cuu:BKK79_31040 [6.2.1.1],     cuu:BKK79_31810 [6.2.1.3])      => [3.1.2.-]
(cvc:BKX93_07155 [6.2.1.1],     cvc:BKX93_14975 [6.2.1.3])      => [3.1.2.-]
(cvc:BKX93_07155 [6.2.1.1],     cvc:BKX93_20305 [6.2.1.3])      => [3.1.2.-]
(cvi:CV_3282 [6.2.1.1],         cvi:CV_0093 [6.2.1.3])          => [3.1.2.-]
(cvi:CV_3282 [6.2.1.1],         cvi:CV_1459 [6.2.1.3])          => [3.1.2.-]
(dac:Daci_1761 [6.2.1.1],       dac:Daci_0928 [6.2.1.3])        => [3.1.2.-]
(dac:Daci_1761 [6.2.1.1],       dac:Daci_0946 [6.2.1.3])        => [3.1.2.-]
(dac:Daci_1761 [6.2.1.1],       dac:Daci_1072 [6.2.1.3])        => [3.1.2.-]
(dac:Daci_1761 [6.2.1.1],       dac:Daci_3166 [6.2.1.3])        => [3.1.2.-]
(dac:Daci_2747 [6.2.1.1],       dac:Daci_0928 [6.2.1.3])        => [3.1.2.-]
(dac:Daci_2747 [6.2.1.1],       dac:Daci_0946 [6.2.1.3])        => [3.1.2.-]
(dac:Daci_2747 [6.2.1.1],       dac:Daci_1072 [6.2.1.3])        => [3.1.2.-]
(dac:Daci_2747 [6.2.1.1],       dac:Daci_3166 [6.2.1.3])        => [3.1.2.-]
(dar:Daro_1629 [6.2.1.1],       dar:Daro_1553 [6.2.1.3])        => [3.1.2.-]
(dar:Daro_2708 [6.2.1.1],       dar:Daro_1553 [6.2.1.3])        => [3.1.2.-]
(del:DelCs14_4005 [6.2.1.1],    del:DelCs14_3549 [6.2.1.3])     => [3.1.2.-]
(del:DelCs14_4005 [6.2.1.1],    del:DelCs14_5449 [6.2.1.3])     => [3.1.2.-]
(del:DelCs14_4005 [6.2.1.1],    del:DelCs14_5581 [6.2.1.3])     => [3.1.2.-]
(del:DelCs14_4005 [6.2.1.1],    del:DelCs14_5598 [6.2.1.3])     => [3.1.2.-]
(del:DelCs14_4879 [6.2.1.1],    del:DelCs14_3549 [6.2.1.3])     => [3.1.2.-]
(del:DelCs14_4879 [6.2.1.1],    del:DelCs14_5449 [6.2.1.3])     => [3.1.2.-]
(del:DelCs14_4879 [6.2.1.1],    del:DelCs14_5581 [6.2.1.3])     => [3.1.2.-]
(del:DelCs14_4879 [6.2.1.1],    del:DelCs14_5598 [6.2.1.3])     => [3.1.2.-]
(dhk:BO996_08310 [6.2.1.1],     dhk:BO996_04700 [6.2.1.3])      => [3.1.2.-]
(dhk:BO996_08310 [6.2.1.1],     dhk:BO996_04790 [6.2.1.3])      => [3.1.2.-]
(dhk:BO996_08310 [6.2.1.1],     dhk:BO996_05445 [6.2.1.3])      => [3.1.2.-]
(dhk:BO996_08310 [6.2.1.1],     dhk:BO996_14635 [6.2.1.3])      => [3.1.2.-]
(dhk:BO996_12685 [6.2.1.1],     dhk:BO996_04700 [6.2.1.3])      => [3.1.2.-]
(dhk:BO996_12685 [6.2.1.1],     dhk:BO996_04790 [6.2.1.3])      => [3.1.2.-]
(dhk:BO996_12685 [6.2.1.1],     dhk:BO996_05445 [6.2.1.3])      => [3.1.2.-]
(dhk:BO996_12685 [6.2.1.1],     dhk:BO996_14635 [6.2.1.3])      => [3.1.2.-]
(dia:Dtpsy_0983 [6.2.1.1],      dia:Dtpsy_3299 [6.2.1.3])       => [3.1.2.-]
(dpy:BA022_09880 [6.2.1.1],     dpy:BA022_16095 [6.2.1.3])      => [3.1.2.-]
(dsu:Dsui_2003 [6.2.1.1],       dsu:Dsui_3212 [6.2.1.3])        => [3.1.2.-]
(dsu:Dsui_2187 [6.2.1.1],       dsu:Dsui_3212 [6.2.1.3])        => [3.1.2.-]
(dts:BI380_09925 [6.2.1.1],     dts:BI380_01785 [6.2.1.3])      => [3.1.2.-]
(dts:BI380_09925 [6.2.1.1],     dts:BI380_19335 [6.2.1.3])      => [3.1.2.-]
(dts:BI380_09925 [6.2.1.1],     dts:BI380_19980 [6.2.1.3])      => [3.1.2.-]
(eba:ebA1206 [6.2.1.1],         eba:ebA4749 [6.2.1.3])          => [3.1.2.-]
(eba:ebA172 [6.2.1.1],          eba:ebA4749 [6.2.1.3])          => [3.1.2.-]
(eba:ebA4717 [6.2.1.1],         eba:ebA4749 [6.2.1.3])          => [3.1.2.-]
(har:HEAR0921 [6.2.1.1],        har:HEAR0221 [6.2.1.3])         => [3.1.2.-]
(hee:hmeg3_05060 [6.2.1.1],     hee:hmeg3_04630 [6.2.1.3])      => [3.1.2.-]
(hee:hmeg3_15885 [6.2.1.1],     hee:hmeg3_04630 [6.2.1.3])      => [3.1.2.-]
(hht:F506_05995 [6.2.1.1],      hht:F506_02120 [6.2.1.3])       => [3.1.2.-]
(hht:F506_09885 [6.2.1.1],      hht:F506_02120 [6.2.1.3])       => [3.1.2.-]
(hrb:Hrubri_0038 [6.2.1.1],     hrb:Hrubri_3826 [6.2.1.3])      => [3.1.2.-]
(hrb:Hrubri_1391 [6.2.1.1],     hrb:Hrubri_3826 [6.2.1.3])      => [3.1.2.-]
(hrb:Hrubri_2885 [6.2.1.1],     hrb:Hrubri_3826 [6.2.1.3])      => [3.1.2.-]
(hse:Hsero_0019 [6.2.1.1],      hse:Hsero_3863 [6.2.1.3])       => [3.1.2.-]
(hse:Hsero_0924 [6.2.1.1],      hse:Hsero_3863 [6.2.1.3])       => [3.1.2.-]
(hse:Hsero_1545 [6.2.1.1],      hse:Hsero_3863 [6.2.1.3])       => [3.1.2.-]
(hyb:Q5W_03760 [6.2.1.1],       hyb:Q5W_11410 [6.2.1.3])        => [3.1.2.-]
(hyb:Q5W_03760 [6.2.1.1],       hyb:Q5W_24170 [6.2.1.3])        => [3.1.2.-]
(hyb:Q5W_10430 [6.2.1.1],       hyb:Q5W_24170 [6.2.1.3])        => [3.1.2.-]
(hyb:Q5W_13100 [6.2.1.1],       hyb:Q5W_24170 [6.2.1.3])        => [3.1.2.-]
(hyl:LPB072_05340 [6.2.1.1],    hyl:LPB072_02370 [6.2.1.3])     => [3.1.2.-]
(hyl:LPB072_13390 [6.2.1.1],    hyl:LPB072_02370 [6.2.1.3])     => [3.1.2.-]
(hyr:BSY239_1420 [6.2.1.1],     hyr:BSY239_3863 [6.2.1.3])      => [3.1.2.-]
(hyr:BSY239_208 [6.2.1.1],      hyr:BSY239_242 [6.2.1.3])       => [3.1.2.-]
(hyr:BSY239_208 [6.2.1.1],      hyr:BSY239_3863 [6.2.1.3])      => [3.1.2.-]
(hyr:BSY239_2575 [6.2.1.1],     hyr:BSY239_3863 [6.2.1.3])      => [3.1.2.-]
(hyr:BSY239_2806 [6.2.1.1],     hyr:BSY239_3863 [6.2.1.3])      => [3.1.2.-]
(hyr:BSY239_862 [6.2.1.1],      hyr:BSY239_3863 [6.2.1.3])      => [3.1.2.-]
(jab:VN23_20665 [6.2.1.1],      jab:VN23_04400 [6.2.1.3])       => [3.1.2.-]
(jag:GJA_4262 [6.2.1.1],        jag:GJA_267 [6.2.1.3])          => [3.1.2.-]
(jag:GJA_4262 [6.2.1.1],        jag:GJA_268 [6.2.1.3])          => [3.1.2.-]
(jag:GJA_4262 [6.2.1.1],        jag:GJA_4080 [6.2.1.3])         => [3.1.2.-]
(jal:BZG29_06755 [6.2.1.1],     jal:BZG29_06345 [6.2.1.3])      => [3.1.2.-]
(jal:BZG29_06755 [6.2.1.1],     jal:BZG29_27375 [6.2.1.3])      => [3.1.2.-]
(jal:BZG29_06755 [6.2.1.1],     jal:BZG29_27380 [6.2.1.3])      => [3.1.2.-]
(jaz:YQ44_21335 [6.2.1.1],      jaz:YQ44_00265 [6.2.1.3])       => [3.1.2.-]
(jaz:YQ44_21335 [6.2.1.1],      jaz:YQ44_00270 [6.2.1.3])       => [3.1.2.-]
(jeu:BJP62_15215 [6.2.1.1],     jeu:BJP62_03110 [6.2.1.3])      => [3.1.2.-]
(jsv:CNX70_06965 [6.2.1.1],     jsv:CNX70_27655 [6.2.1.3])      => [3.1.2.-]
(jsv:CNX70_06965 [6.2.1.1],     jsv:CNX70_27660 [6.2.1.3])      => [3.1.2.-]
(lch:Lcho_3063 [6.2.1.1],       lch:Lcho_0424 [6.2.1.3])        => [3.1.2.-]
(lhk:LHK_01225 [6.2.1.1],       lhk:LHK_01931 [6.2.1.3])        => [3.1.2.-]
(lih:L63ED372_01051 [6.2.1.1],  lih:L63ED372_00452 [6.2.1.3])   => [3.1.2.-]
(lih:L63ED372_01051 [6.2.1.1],  lih:L63ED372_02281 [6.2.1.3])   => [3.1.2.-]
(lih:L63ED372_01330 [6.2.1.1],  lih:L63ED372_00452 [6.2.1.3])   => [3.1.2.-]
(lih:L63ED372_01330 [6.2.1.1],  lih:L63ED372_02281 [6.2.1.3])   => [3.1.2.-]
(lih:L63ED372_01862 [6.2.1.1],  lih:L63ED372_00452 [6.2.1.3])   => [3.1.2.-]
(lih:L63ED372_01862 [6.2.1.1],  lih:L63ED372_02281 [6.2.1.3])   => [3.1.2.-]
(lim:L103DPR2_02152 [6.2.1.1],  lim:L103DPR2_00134 [6.2.1.3])   => [3.1.2.-]
(lim:L103DPR2_02348 [6.2.1.1],  lim:L103DPR2_00134 [6.2.1.3])   => [3.1.2.-]
(masw:AM586_07040 [6.2.1.1],    masw:AM586_14865 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_07040 [6.2.1.1],    masw:AM586_26465 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_07040 [6.2.1.1],    masw:AM586_26470 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_18300 [6.2.1.1],    masw:AM586_14865 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_18300 [6.2.1.1],    masw:AM586_26465 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_18300 [6.2.1.1],    masw:AM586_26470 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_20075 [6.2.1.1],    masw:AM586_14865 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_20075 [6.2.1.1],    masw:AM586_26465 [6.2.1.3])     => [3.1.2.-]
(masw:AM586_20075 [6.2.1.1],    masw:AM586_26470 [6.2.1.3])     => [3.1.2.-]
(metr:BSY238_112 [6.2.1.1],     metr:BSY238_2622 [6.2.1.3])     => [3.1.2.-]
(miu:ABE85_02665 [6.2.1.1],     miu:ABE85_24065 [6.2.1.3])      => [3.1.2.-]
(miu:ABE85_26380 [6.2.1.1],     miu:ABE85_24065 [6.2.1.3])      => [3.1.2.-]
(mms:mma_0882 [6.2.1.1],        mms:mma_0275 [6.2.1.3])         => [3.1.2.-]
(mnr:ACZ75_12925 [6.2.1.1],     mnr:ACZ75_20990 [6.2.1.3])      => [3.1.2.-]
(mnr:ACZ75_12925 [6.2.1.1],     mnr:ACZ75_20995 [6.2.1.3])      => [3.1.2.-]
(mpt:Mpe_A0343 [6.2.1.1],       mpt:Mpe_A0353 [6.2.1.3])        => [3.1.2.-]
(mpt:Mpe_A0343 [6.2.1.1],       mpt:Mpe_A2687 [6.2.1.3])        => [3.1.2.-]
(mpt:Mpe_A0343 [6.2.1.1],       mpt:Mpe_A3572 [6.2.1.3])        => [3.1.2.-]
(mpt:Mpe_A1385 [6.2.1.1],       mpt:Mpe_A0353 [6.2.1.3])        => [3.1.2.-]
(mpt:Mpe_A1385 [6.2.1.1],       mpt:Mpe_A2687 [6.2.1.3])        => [3.1.2.-]
(mpt:Mpe_A1385 [6.2.1.1],       mpt:Mpe_A3572 [6.2.1.3])        => [3.1.2.-]
(nlc:EBAPG3_014425 [6.2.1.1],   nlc:EBAPG3_002355 [6.2.1.3])    => [3.1.2.-]
(odi:ODI_R1455 [6.2.1.1],       odi:ODI_R0965 [6.2.1.3])        => [3.1.2.-]
(odi:ODI_R1475 [6.2.1.1],       odi:ODI_R0420 [6.2.1.3])        => [3.1.2.-]
(odi:ODI_R1475 [6.2.1.1],       odi:ODI_R0965 [6.2.1.3])        => [3.1.2.-]
(papi:SG18_13465 [6.2.1.1],     papi:SG18_01660 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_13465 [6.2.1.1],     papi:SG18_21670 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_15225 [6.2.1.1],     papi:SG18_01660 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_15225 [6.2.1.1],     papi:SG18_21670 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_22545 [6.2.1.1],     papi:SG18_01660 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_22545 [6.2.1.1],     papi:SG18_21670 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_23210 [6.2.1.1],     papi:SG18_01660 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_23210 [6.2.1.1],     papi:SG18_21670 [6.2.1.3])      => [3.1.2.-]
(papi:SG18_23210 [6.2.1.1],     papi:SG18_23430 [6.2.1.3])      => [3.1.2.-]
(para:BTO02_14005 [6.2.1.1],    para:BTO02_13220 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_14005 [6.2.1.1],    para:BTO02_18380 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_14005 [6.2.1.1],    para:BTO02_30340 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_19585 [6.2.1.1],    para:BTO02_13220 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_19585 [6.2.1.1],    para:BTO02_18380 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_19585 [6.2.1.1],    para:BTO02_30340 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_31640 [6.2.1.1],    para:BTO02_13220 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_31640 [6.2.1.1],    para:BTO02_18380 [6.2.1.3])     => [3.1.2.-]
(para:BTO02_31640 [6.2.1.1],    para:BTO02_30340 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_11275 [6.2.1.1],    parb:CJU94_07555 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_11275 [6.2.1.1],    parb:CJU94_16760 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_11275 [6.2.1.1],    parb:CJU94_33365 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_13285 [6.2.1.1],    parb:CJU94_07555 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_13285 [6.2.1.1],    parb:CJU94_16760 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_18040 [6.2.1.1],    parb:CJU94_07555 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_18040 [6.2.1.1],    parb:CJU94_16760 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_23590 [6.2.1.1],    parb:CJU94_07555 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_23590 [6.2.1.1],    parb:CJU94_16760 [6.2.1.3])     => [3.1.2.-]
(parb:CJU94_23590 [6.2.1.1],    parb:CJU94_33365 [6.2.1.3])     => [3.1.2.-]
(pbh:AAW51_1716 [6.2.1.1],      pbh:AAW51_0196 [6.2.1.3])       => [3.1.2.-]
(pbh:AAW51_1716 [6.2.1.1],      pbh:AAW51_0774 [6.2.1.3])       => [3.1.2.-]
(pbh:AAW51_1716 [6.2.1.1],      pbh:AAW51_4756 [6.2.1.3])       => [3.1.2.-]
(pfg:AB870_01500 [6.2.1.1],     pfg:AB870_00895 [6.2.1.3])      => [3.1.2.-]
(pfg:AB870_01500 [6.2.1.1],     pfg:AB870_04785 [6.2.1.3])      => [3.1.2.-]
(pfg:AB870_02135 [6.2.1.1],     pfg:AB870_00895 [6.2.1.3])      => [3.1.2.-]
(pfg:AB870_02135 [6.2.1.1],     pfg:AB870_04785 [6.2.1.3])      => [3.1.2.-]
(pfg:AB870_15915 [6.2.1.1],     pfg:AB870_00895 [6.2.1.3])      => [3.1.2.-]
(pfg:AB870_15915 [6.2.1.1],     pfg:AB870_04785 [6.2.1.3])      => [3.1.2.-]
(pfg:AB870_18295 [6.2.1.1],     pfg:AB870_00895 [6.2.1.3])      => [3.1.2.-]
(pfg:AB870_18295 [6.2.1.1],     pfg:AB870_04785 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_10990 [6.2.1.1],     phs:C2L64_09960 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_10990 [6.2.1.1],     phs:C2L64_15970 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_10990 [6.2.1.1],     phs:C2L64_40120 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_10990 [6.2.1.1],     phs:C2L64_42020 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_10990 [6.2.1.1],     phs:C2L64_52585 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_11060 [6.2.1.1],     phs:C2L64_09960 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_11060 [6.2.1.1],     phs:C2L64_15970 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_11060 [6.2.1.1],     phs:C2L64_40120 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_21175 [6.2.1.1],     phs:C2L64_09960 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_21175 [6.2.1.1],     phs:C2L64_15970 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_21175 [6.2.1.1],     phs:C2L64_40120 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_28080 [6.2.1.1],     phs:C2L64_09960 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_28080 [6.2.1.1],     phs:C2L64_15970 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_28080 [6.2.1.1],     phs:C2L64_40120 [6.2.1.3])      => [3.1.2.-]
(phs:C2L64_28080 [6.2.1.1],     phs:C2L64_42020 [6.2.1.3])      => [3.1.2.-]
(pkt:AT984_05505 [6.2.1.1],     pkt:AT984_00025 [6.2.1.3])      => [3.1.2.-]
(pkt:AT984_05505 [6.2.1.1],     pkt:AT984_17090 [6.2.1.3])      => [3.1.2.-]
(pna:Pnap_2880 [6.2.1.1],       pna:Pnap_3797 [6.2.1.3])        => [3.1.2.-]
(pne:Pnec_0756 [6.2.1.1],       pne:Pnec_0959 [6.2.1.3])        => [3.1.2.-]
(pnr:AT302_13210 [6.2.1.1],     pnr:AT302_14335 [6.2.1.3])      => [3.1.2.-]
(pnr:AT302_13210 [6.2.1.1],     pnr:AT302_18235 [6.2.1.3])      => [3.1.2.-]
(pnr:AT302_16795 [6.2.1.1],     pnr:AT302_14335 [6.2.1.3])      => [3.1.2.-]
(pnr:AT302_16795 [6.2.1.1],     pnr:AT302_18235 [6.2.1.3])      => [3.1.2.-]
(pnr:AT302_17500 [6.2.1.1],     pnr:AT302_14335 [6.2.1.3])      => [3.1.2.-]
(pnr:AT302_17500 [6.2.1.1],     pnr:AT302_18235 [6.2.1.3])      => [3.1.2.-]
(pnr:AT302_26415 [6.2.1.1],     pnr:AT302_14335 [6.2.1.3])      => [3.1.2.-]
(pnr:AT302_26415 [6.2.1.1],     pnr:AT302_18235 [6.2.1.3])      => [3.1.2.-]
(pol:Bpro_0761 [6.2.1.1],       pol:Bpro_4543 [6.2.1.3])        => [3.1.2.-]
(pol:Bpro_1590 [6.2.1.1],       pol:Bpro_4543 [6.2.1.3])        => [3.1.2.-]
(pol:Bpro_2049 [6.2.1.1],       pol:Bpro_4543 [6.2.1.3])        => [3.1.2.-]
(pol:Bpro_3358 [6.2.1.1],       pol:Bpro_4543 [6.2.1.3])        => [3.1.2.-]
(pox:MB84_09360 [6.2.1.1],      pox:MB84_18475 [6.2.1.3])       => [3.1.2.-]
(pox:MB84_09360 [6.2.1.1],      pox:MB84_22535 [6.2.1.3])       => [3.1.2.-]
(pox:MB84_11965 [6.2.1.1],      pox:MB84_18475 [6.2.1.3])       => [3.1.2.-]
(pox:MB84_11965 [6.2.1.1],      pox:MB84_22535 [6.2.1.3])       => [3.1.2.-]
(pox:MB84_19035 [6.2.1.1],      pox:MB84_18475 [6.2.1.3])       => [3.1.2.-]
(pox:MB84_19035 [6.2.1.1],      pox:MB84_22535 [6.2.1.3])       => [3.1.2.-]
(pox:MB84_19680 [6.2.1.1],      pox:MB84_18475 [6.2.1.3])       => [3.1.2.-]
(pox:MB84_19680 [6.2.1.1],      pox:MB84_22535 [6.2.1.3])       => [3.1.2.-]
(ppk:U875_08745 [6.2.1.1],      ppk:U875_06300 [6.2.1.3])       => [3.1.2.-]
(ppk:U875_08745 [6.2.1.1],      ppk:U875_08570 [6.2.1.3])       => [3.1.2.-]
(ppk:U875_09770 [6.2.1.1],      ppk:U875_06300 [6.2.1.3])       => [3.1.2.-]
(ppk:U875_16760 [6.2.1.1],      ppk:U875_06300 [6.2.1.3])       => [3.1.2.-]
(ppk:U875_19165 [6.2.1.1],      ppk:U875_06300 [6.2.1.3])       => [3.1.2.-]
(ppul:RO07_13145 [6.2.1.1],     ppul:RO07_01525 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_13145 [6.2.1.1],     ppul:RO07_22430 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_16390 [6.2.1.1],     ppul:RO07_01525 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_16390 [6.2.1.1],     ppul:RO07_22430 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_23175 [6.2.1.1],     ppul:RO07_01525 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_23175 [6.2.1.1],     ppul:RO07_22430 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_23865 [6.2.1.1],     ppul:RO07_01525 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_23865 [6.2.1.1],     ppul:RO07_22430 [6.2.1.3])      => [3.1.2.-]
(ppul:RO07_23865 [6.2.1.1],     ppul:RO07_24030 [6.2.1.3])      => [3.1.2.-]
(pse:NH8B_1762 [6.2.1.1],       pse:NH8B_2855 [6.2.1.3])        => [3.1.2.-]
(pse:NH8B_2199 [6.2.1.1],       pse:NH8B_2855 [6.2.1.3])        => [3.1.2.-]
(pse:NH8B_2257 [6.2.1.1],       pse:NH8B_2855 [6.2.1.3])        => [3.1.2.-]
(pse:NH8B_2997 [6.2.1.1],       pse:NH8B_2855 [6.2.1.3])        => [3.1.2.-]
(pspu:NA29_09215 [6.2.1.1],     pspu:NA29_10135 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_09215 [6.2.1.1],     pspu:NA29_14500 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_13090 [6.2.1.1],     pspu:NA29_10135 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_13090 [6.2.1.1],     pspu:NA29_12860 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_13090 [6.2.1.1],     pspu:NA29_14500 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_13895 [6.2.1.1],     pspu:NA29_10135 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_13895 [6.2.1.1],     pspu:NA29_14500 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_20785 [6.2.1.1],     pspu:NA29_10135 [6.2.1.3])      => [3.1.2.-]
(pspu:NA29_20785 [6.2.1.1],     pspu:NA29_14500 [6.2.1.3])      => [3.1.2.-]
(pspw:BJG93_07510 [6.2.1.1],    pspw:BJG93_06735 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_07510 [6.2.1.1],    pspw:BJG93_14935 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_25740 [6.2.1.1],    pspw:BJG93_06735 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_25740 [6.2.1.1],    pspw:BJG93_14935 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_25740 [6.2.1.1],    pspw:BJG93_34000 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_32490 [6.2.1.1],    pspw:BJG93_06735 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_32490 [6.2.1.1],    pspw:BJG93_14935 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_32490 [6.2.1.1],    pspw:BJG93_34000 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_33350 [6.2.1.1],    pspw:BJG93_06735 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_33350 [6.2.1.1],    pspw:BJG93_14935 [6.2.1.3])     => [3.1.2.-]
(pspw:BJG93_33350 [6.2.1.1],    pspw:BJG93_34000 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10135 [6.2.1.1],    pter:C2L65_09270 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10135 [6.2.1.1],    pter:C2L65_13860 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10135 [6.2.1.1],    pter:C2L65_37360 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10135 [6.2.1.1],    pter:C2L65_39140 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10135 [6.2.1.1],    pter:C2L65_44665 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10220 [6.2.1.1],    pter:C2L65_09270 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10220 [6.2.1.1],    pter:C2L65_13860 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10220 [6.2.1.1],    pter:C2L65_37360 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_10220 [6.2.1.1],    pter:C2L65_44665 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_20430 [6.2.1.1],    pter:C2L65_09270 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_20430 [6.2.1.1],    pter:C2L65_13860 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_20430 [6.2.1.1],    pter:C2L65_37360 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_20430 [6.2.1.1],    pter:C2L65_39140 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_20430 [6.2.1.1],    pter:C2L65_44665 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_42195 [6.2.1.1],    pter:C2L65_09270 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_42195 [6.2.1.1],    pter:C2L65_13860 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_42195 [6.2.1.1],    pter:C2L65_37360 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_42195 [6.2.1.1],    pter:C2L65_44665 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_44135 [6.2.1.1],    pter:C2L65_09270 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_44135 [6.2.1.1],    pter:C2L65_13860 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_44135 [6.2.1.1],    pter:C2L65_37360 [6.2.1.3])     => [3.1.2.-]
(pter:C2L65_44135 [6.2.1.1],    pter:C2L65_44665 [6.2.1.3])     => [3.1.2.-]
(ptx:ABW99_00335 [6.2.1.1],     ptx:ABW99_20595 [6.2.1.3])      => [3.1.2.-]
(ptx:ABW99_07275 [6.2.1.1],     ptx:ABW99_20595 [6.2.1.3])      => [3.1.2.-]
(ptx:ABW99_09370 [6.2.1.1],     ptx:ABW99_20595 [6.2.1.3])      => [3.1.2.-]
(ptx:ABW99_11010 [6.2.1.1],     ptx:ABW99_20595 [6.2.1.3])      => [3.1.2.-]
(ptx:ABW99_13945 [6.2.1.1],     ptx:ABW99_20595 [6.2.1.3])      => [3.1.2.-]
(put:PT7_0129 [6.2.1.1],        put:PT7_2583 [6.2.1.3])         => [3.1.2.-]
(put:PT7_0129 [6.2.1.1],        put:PT7_2885 [6.2.1.3])         => [3.1.2.-]
(put:PT7_1650 [6.2.1.1],        put:PT7_2583 [6.2.1.3])         => [3.1.2.-]
(put:PT7_1665 [6.2.1.1],        put:PT7_2885 [6.2.1.3])         => [3.1.2.-]
(pve:UC34_04915 [6.2.1.1],      pve:UC34_13920 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_04915 [6.2.1.1],      pve:UC34_17755 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_07590 [6.2.1.1],      pve:UC34_13920 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_07590 [6.2.1.1],      pve:UC34_17755 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_14590 [6.2.1.1],      pve:UC34_13920 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_14590 [6.2.1.1],      pve:UC34_17755 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_15325 [6.2.1.1],      pve:UC34_13920 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_15325 [6.2.1.1],      pve:UC34_15475 [6.2.1.3])       => [3.1.2.-]
(pve:UC34_15325 [6.2.1.1],      pve:UC34_17755 [6.2.1.3])       => [3.1.2.-]
(rac:RA876_06960 [6.2.1.1],     rac:RA876_14920 [6.2.1.3])      => [3.1.2.-]
(rac:RA876_06960 [6.2.1.1],     rac:RA876_17480 [6.2.1.3])      => [3.1.2.-]
(rbn:RBXJA2T_05853 [6.2.1.1],   rbn:RBXJA2T_09037 [6.2.1.3])    => [3.1.2.-]
(rbn:RBXJA2T_05853 [6.2.1.1],   rbn:RBXJA2T_13294 [6.2.1.3])    => [3.1.2.-]
(rbn:RBXJA2T_05853 [6.2.1.1],   rbn:RBXJA2T_17162 [6.2.1.3])    => [3.1.2.-]
(rbn:RBXJA2T_05903 [6.2.1.1],   rbn:RBXJA2T_09037 [6.2.1.3])    => [3.1.2.-]
(rbn:RBXJA2T_05903 [6.2.1.1],   rbn:RBXJA2T_13294 [6.2.1.3])    => [3.1.2.-]
(rbu:PG1C_06520 [6.2.1.1],      rbu:PG1C_05420 [6.2.1.3])       => [3.1.2.-]
(rdp:RD2015_1620 [6.2.1.1],     rdp:RD2015_4432 [6.2.1.3])      => [3.1.2.-]
(rdp:RD2015_1620 [6.2.1.1],     rdp:RD2015_4649 [6.2.1.3])      => [3.1.2.-]
(rdp:RD2015_1980 [6.2.1.1],     rdp:RD2015_4432 [6.2.1.3])      => [3.1.2.-]
(rdp:RD2015_1980 [6.2.1.1],     rdp:RD2015_4649 [6.2.1.3])      => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_A1295 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_A2150 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_A2748 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_A2947 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_A3288 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_A3351 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_B0753 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_B1239 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:H16_B1736 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1197 [6.2.1.1],       reh:PHG399 [6.2.1.3])           => [3.1.2.-]
(reh:H16_A1616 [6.2.1.1],       reh:H16_A2748 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1616 [6.2.1.1],       reh:H16_A2947 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1616 [6.2.1.1],       reh:H16_A3288 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A1616 [6.2.1.1],       reh:H16_B1239 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_A1295 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_A2150 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_A2748 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_A2947 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_A3288 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_A3351 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_B0753 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:H16_B1239 [6.2.1.3])        => [3.1.2.-]
(reh:H16_A2525 [6.2.1.1],       reh:PHG399 [6.2.1.3])           => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:H16_A1295 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:H16_A2150 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:H16_A2748 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:H16_A2947 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:H16_A3288 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:H16_A3351 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:H16_B1239 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B0834 [6.2.1.1],       reh:PHG399 [6.2.1.3])           => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_A1295 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_A2150 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_A2748 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_A2947 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_A3288 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_A3351 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_B0753 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_B1239 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:H16_B1736 [6.2.1.3])        => [3.1.2.-]
(reh:H16_B1102 [6.2.1.1],       reh:PHG399 [6.2.1.3])           => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_A2994 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_A3057 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_B3549 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_B3565 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_B3605 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_B4042 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_B4155 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_B4758 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_C6056 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_C6065 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_C6185 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1097 [6.2.1.1],      reu:Reut_D6480 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_A2994 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_A3057 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_B3549 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_B3565 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_B4042 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_B4155 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_B4758 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_C6065 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_C6185 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A1821 [6.2.1.1],      reu:Reut_D6480 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_A2994 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_A3057 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_B3549 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_B3565 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_B4042 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_B4155 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_B4758 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_C6056 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_C6065 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_C6185 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_A2229 [6.2.1.1],      reu:Reut_D6480 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_A2994 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_A3057 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_B3549 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_B3565 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_B3605 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_B4042 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_B4155 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_B4758 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_C6056 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_C6065 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_C6185 [6.2.1.3])       => [3.1.2.-]
(reu:Reut_B4371 [6.2.1.1],      reu:Reut_D6480 [6.2.1.3])       => [3.1.2.-]
(rfr:Rfer_0388 [6.2.1.1],       rfr:Rfer_2283 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_0388 [6.2.1.1],       rfr:Rfer_3503 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_0388 [6.2.1.1],       rfr:Rfer_3752 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_0388 [6.2.1.1],       rfr:Rfer_3775 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_0388 [6.2.1.1],       rfr:Rfer_3898 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2581 [6.2.1.1],       rfr:Rfer_2283 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2581 [6.2.1.1],       rfr:Rfer_3752 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2581 [6.2.1.1],       rfr:Rfer_3775 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2581 [6.2.1.1],       rfr:Rfer_3898 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2698 [6.2.1.1],       rfr:Rfer_2283 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2698 [6.2.1.1],       rfr:Rfer_3752 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2698 [6.2.1.1],       rfr:Rfer_3775 [6.2.1.3])        => [3.1.2.-]
(rfr:Rfer_2698 [6.2.1.1],       rfr:Rfer_3898 [6.2.1.3])        => [3.1.2.-]
(rge:RGE_18530 [6.2.1.1],       rge:RGE_06000 [6.2.1.3])        => [3.1.2.-]
(rge:RGE_18530 [6.2.1.1],       rge:RGE_07750 [6.2.1.3])        => [3.1.2.-]
(rge:RGE_18530 [6.2.1.1],       rge:RGE_46110 [6.2.1.3])        => [3.1.2.-]
(rge:RGE_18640 [6.2.1.1],       rge:RGE_06000 [6.2.1.3])        => [3.1.2.-]
(rge:RGE_18640 [6.2.1.1],       rge:RGE_46110 [6.2.1.3])        => [3.1.2.-]
(rgu:A4W93_12320 [6.2.1.1],     rgu:A4W93_02100 [6.2.1.3])      => [3.1.2.-]
(rgu:A4W93_12320 [6.2.1.1],     rgu:A4W93_06455 [6.2.1.3])      => [3.1.2.-]
(rgu:A4W93_12320 [6.2.1.1],     rgu:A4W93_06910 [6.2.1.3])      => [3.1.2.-]
(rgu:A4W93_12320 [6.2.1.1],     rgu:A4W93_17050 [6.2.1.3])      => [3.1.2.-]
(rgu:A4W93_12320 [6.2.1.1],     rgu:A4W93_25930 [6.2.1.3])      => [3.1.2.-]
(rhy:RD110_11125 [6.2.1.1],     rhy:RD110_25205 [6.2.1.3])      => [3.1.2.-]
(rin:ACS15_1222 [6.2.1.1],      rin:ACS15_0549 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_1222 [6.2.1.1],      rin:ACS15_3158 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_1222 [6.2.1.1],      rin:ACS15_3830 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_1222 [6.2.1.1],      rin:ACS15_5721 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_4031 [6.2.1.1],      rin:ACS15_0549 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_4031 [6.2.1.1],      rin:ACS15_3158 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_4031 [6.2.1.1],      rin:ACS15_3830 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_4031 [6.2.1.1],      rin:ACS15_5721 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_5715 [6.2.1.1],      rin:ACS15_0549 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_5715 [6.2.1.1],      rin:ACS15_3158 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_5715 [6.2.1.1],      rin:ACS15_3830 [6.2.1.3])       => [3.1.2.-]
(rin:ACS15_5715 [6.2.1.1],      rin:ACS15_5721 [6.2.1.3])       => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_2525 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_3148 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_3215 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_4068 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_4454 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_4502 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_4746 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_5140 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_5528 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_1061 [6.2.1.1],       rme:Rmet_5827 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_2525 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_3148 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_3215 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_4068 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_4454 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_4502 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_4746 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_5140 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_5528 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_2270 [6.2.1.1],       rme:Rmet_5827 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_2525 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_3148 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_3215 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_4068 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_4454 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_4502 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_4746 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_5140 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_5528 [6.2.1.3])        => [3.1.2.-]
(rme:Rmet_5743 [6.2.1.1],       rme:Rmet_5827 [6.2.1.3])        => [3.1.2.-]
(rmn:TK49_13410 [6.2.1.1],      rmn:TK49_03220 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_13410 [6.2.1.1],      rmn:TK49_05770 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_13410 [6.2.1.1],      rmn:TK49_06095 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_13410 [6.2.1.1],      rmn:TK49_20335 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_20305 [6.2.1.1],      rmn:TK49_03220 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_20305 [6.2.1.1],      rmn:TK49_05770 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_20305 [6.2.1.1],      rmn:TK49_06095 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_20305 [6.2.1.1],      rmn:TK49_20335 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_21165 [6.2.1.1],      rmn:TK49_03220 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_21165 [6.2.1.1],      rmn:TK49_05770 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_21165 [6.2.1.1],      rmn:TK49_06095 [6.2.1.3])       => [3.1.2.-]
(rmn:TK49_21165 [6.2.1.1],      rmn:TK49_20335 [6.2.1.3])       => [3.1.2.-]
(rpi:Rpic_2099 [6.2.1.1],       rpi:Rpic_0109 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_2099 [6.2.1.1],       rpi:Rpic_0413 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_2099 [6.2.1.1],       rpi:Rpic_3104 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_2099 [6.2.1.1],       rpi:Rpic_3685 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_2099 [6.2.1.1],       rpi:Rpic_3980 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_3974 [6.2.1.1],       rpi:Rpic_0109 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_3974 [6.2.1.1],       rpi:Rpic_0413 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_3974 [6.2.1.1],       rpi:Rpic_3104 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_3974 [6.2.1.1],       rpi:Rpic_3685 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_3974 [6.2.1.1],       rpi:Rpic_3980 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4143 [6.2.1.1],       rpi:Rpic_0109 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4143 [6.2.1.1],       rpi:Rpic_0413 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4143 [6.2.1.1],       rpi:Rpic_3104 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4143 [6.2.1.1],       rpi:Rpic_3685 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4143 [6.2.1.1],       rpi:Rpic_3980 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4644 [6.2.1.1],       rpi:Rpic_0109 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4644 [6.2.1.1],       rpi:Rpic_0413 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4644 [6.2.1.1],       rpi:Rpic_3104 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4644 [6.2.1.1],       rpi:Rpic_3685 [6.2.1.3])        => [3.1.2.-]
(rpi:Rpic_4644 [6.2.1.1],       rpi:Rpic_3980 [6.2.1.3])        => [3.1.2.-]
(rsb:RS694_05140 [6.2.1.1],     rsb:RS694_14185 [6.2.1.3])      => [3.1.2.-]
(rsb:RS694_05140 [6.2.1.1],     rsb:RS694_18870 [6.2.1.3])      => [3.1.2.-]
(rsb:RS694_07695 [6.2.1.1],     rsb:RS694_18870 [6.2.1.3])      => [3.1.2.-]
(rso:RSc1952 [6.2.1.1],         rso:RSc0064 [6.2.1.3])          => [3.1.2.-]
(rso:RSc1952 [6.2.1.1],         rso:RSc2857 [6.2.1.3])          => [3.1.2.-]
(rso:RSp0651 [6.2.1.1],         rso:RSc0064 [6.2.1.3])          => [3.1.2.-]
(rso:RSp0651 [6.2.1.1],         rso:RSc2857 [6.2.1.3])          => [3.1.2.-]
(rso:RSp1265 [6.2.1.1],         rso:RSc0064 [6.2.1.3])          => [3.1.2.-]
(rso:RSp1265 [6.2.1.1],         rso:RSc2857 [6.2.1.3])          => [3.1.2.-]
(rta:Rta_10430 [6.2.1.1],       rta:Rta_02130 [6.2.1.3])        => [3.1.2.-]
(rta:Rta_15940 [6.2.1.1],       rta:Rta_02130 [6.2.1.3])        => [3.1.2.-]
(shd:SUTH_02307 [6.2.1.1],      shd:SUTH_00250 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02307 [6.2.1.1],      shd:SUTH_00507 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02307 [6.2.1.1],      shd:SUTH_02599 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02929 [6.2.1.1],      shd:SUTH_00250 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02929 [6.2.1.1],      shd:SUTH_00507 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02929 [6.2.1.1],      shd:SUTH_00625 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02929 [6.2.1.1],      shd:SUTH_02599 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02977 [6.2.1.1],      shd:SUTH_00096 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02977 [6.2.1.1],      shd:SUTH_00250 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02977 [6.2.1.1],      shd:SUTH_00507 [6.2.1.3])       => [3.1.2.-]
(shd:SUTH_02977 [6.2.1.1],      shd:SUTH_02599 [6.2.1.3])       => [3.1.2.-]
(sulf:CAP31_04890 [6.2.1.1],    sulf:CAP31_12695 [6.2.1.3])     => [3.1.2.-]
(tcl:Tchl_1007 [6.2.1.1],       tcl:Tchl_3371 [6.2.1.3])        => [3.1.2.-]
(tcl:Tchl_2541 [6.2.1.1],       tcl:Tchl_3371 [6.2.1.3])        => [3.1.2.-]
(thi:THI_1197 [6.2.1.1],        thi:THI_2917 [6.2.1.3])         => [3.1.2.-]
(thi:THI_2397 [6.2.1.1],        thi:THI_2917 [6.2.1.3])         => [3.1.2.-]
(thk:CCZ27_01710 [6.2.1.1],     thk:CCZ27_04350 [6.2.1.3])      => [3.1.2.-]
(thk:CCZ27_11050 [6.2.1.1],     thk:CCZ27_04350 [6.2.1.3])      => [3.1.2.-]
(thu:AC731_003990 [6.2.1.1],    thu:AC731_000675 [6.2.1.3])     => [3.1.2.-]
(thu:AC731_018930 [6.2.1.1],    thu:AC731_000675 [6.2.1.3])     => [3.1.2.-]
(thu:AC731_019020 [6.2.1.1],    thu:AC731_000675 [6.2.1.3])     => [3.1.2.-]
(tin:Tint_0943 [6.2.1.1],       tin:Tint_2518 [6.2.1.3])        => [3.1.2.-]
(tin:Tint_2070 [6.2.1.1],       tin:Tint_2518 [6.2.1.3])        => [3.1.2.-]
(tmz:Tmz1t_1162 [6.2.1.1],      tmz:Tmz1t_3077 [6.2.1.3])       => [3.1.2.-]
(tmz:Tmz1t_1412 [6.2.1.1],      tmz:Tmz1t_3077 [6.2.1.3])       => [3.1.2.-]
(tmz:Tmz1t_2652 [6.2.1.1],      tmz:Tmz1t_3077 [6.2.1.3])       => [3.1.2.-]
(tmz:Tmz1t_3467 [6.2.1.1],      tmz:Tmz1t_3077 [6.2.1.3])       => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_07095 [6.2.1.3])      => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_08370 [6.2.1.3])      => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_11705 [6.2.1.3])      => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_11750 [6.2.1.3])      => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_17410 [6.2.1.3])      => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_17515 [6.2.1.3])      => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_19120 [6.2.1.3])      => [3.1.2.-]
(vaa:AX767_18465 [6.2.1.1],     vaa:AX767_20040 [6.2.1.3])      => [3.1.2.-]
(vap:Vapar_2526 [6.2.1.1],      vap:Vapar_0394 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_2526 [6.2.1.1],      vap:Vapar_4793 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_2526 [6.2.1.1],      vap:Vapar_5352 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_5367 [6.2.1.1],      vap:Vapar_0394 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_5367 [6.2.1.1],      vap:Vapar_4793 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_5367 [6.2.1.1],      vap:Vapar_5352 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_6251 [6.2.1.1],      vap:Vapar_0394 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_6251 [6.2.1.1],      vap:Vapar_4793 [6.2.1.3])       => [3.1.2.-]
(vap:Vapar_6251 [6.2.1.1],      vap:Vapar_5352 [6.2.1.3])       => [3.1.2.-]
(vbo:CKY39_15680 [6.2.1.1],     vbo:CKY39_02235 [6.2.1.3])      => [3.1.2.-]
(vbo:CKY39_15680 [6.2.1.1],     vbo:CKY39_02280 [6.2.1.3])      => [3.1.2.-]
(vbo:CKY39_15680 [6.2.1.1],     vbo:CKY39_27080 [6.2.1.3])      => [3.1.2.-]
(vbo:CKY39_15680 [6.2.1.1],     vbo:CKY39_29675 [6.2.1.3])      => [3.1.2.-]
(vei:Veis_3218 [6.2.1.1],       vei:Veis_1683 [6.2.1.3])        => [3.1.2.-]
(vei:Veis_3218 [6.2.1.1],       vei:Veis_2551 [6.2.1.3])        => [3.1.2.-]
(vei:Veis_3218 [6.2.1.1],       vei:Veis_3437 [6.2.1.3])        => [3.1.2.-]
(vei:Veis_3218 [6.2.1.1],       vei:Veis_3839 [6.2.1.3])        => [3.1.2.-]
(vei:Veis_3218 [6.2.1.1],       vei:Veis_3874 [6.2.1.3])        => [3.1.2.-]
(vff:VITFI_CDS2558 [6.2.1.1],   vff:VITFI_CDS1234 [6.2.1.3])    => [3.1.2.-]
(vei:Veis_4861 [2.4.2.-],       vei:Veis_4553 [5.1.1.7])        => [4.1.3.-]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_026 [6.1.1.20])      => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_041 [2.7.7.7])       => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_071 [6.1.1.10])      => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_127 [6.1.1.5])       => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_151 [6.1.1.4])       => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_177 [6.1.1.15])      => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_189 [6.1.1.14])      => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_193 [4.1.99.17])     => [6.3.4.2]
(zin:ZICARI_050 [2.7.7.6],      zin:ZICARI_194 [6.1.1.9])       => [6.3.4.2]
(zin:ZICARI_052 [2.7.7.6],      zin:ZICARI_026 [6.1.1.20])      => [6.3.4.2]
(zin:ZICARI_052 [2.7.7.6],      zin:ZICARI_189 [6.1.1.14])      => [6.3.4.2]
(zin:ZICARI_163 [1.2.4.2],      zin:ZICARI_050 [2.7.7.6])       => [6.3.4.2]
Conclusion

Alphaproteobacteria and Betaproteobacteria are very comparable in the percentage of neofunctionalisations contributing to robustness. In total numbers, however, Betaproteobacteria have more neofunctionalisations. But they also have the larger core metabolism.

FEV_KEGG.Experiments.50.getCladeA()[source]
FEV_KEGG.Experiments.50.getCladeB()[source]
FEV_KEGG.Experiments.51 module
Context

In 50, we printed long lists of enzymes and EC numbers. This is hard to read and hard to use for further research, which is why we now export this information in HTML.

Question

Which neofunctionalisations exist in Archaea? Grouped by function change, sorted lexicographically, annotated with links to KEGG, annotated with human-readable names (if possible), and exported into an HTML file.

Method
  • get clade
  • get neofunctionalisations
  • export to HTML, including links and further info
Result 
[see file Archaea_Neofunctionalisations-For-FunctionChange.html]
Conclusion

Much more useful than a plain text list of cryptic IDs.

FEV_KEGG.Experiments.51.getClade()[source]
FEV_KEGG.Experiments.52 module
Context

In 49, we did this before, but this time we export into pretty HTML.

Question

Which neofunctionalised enzymes cause the core metabolism of Deltaproteobacteria to have increased redundancy? How much do they contribute? Grouped by contributed functions, sorted lexicographically, annotated with links to KEGG, annotated with human-readable names (if possible), and exported into an HTML file.

Method
  • get clade
  • get core metabolism
  • calculate “neofunctionalised” ECs
  • calculate redundancy
  • REPEAT for each “neofunctionalised” EC contributing to redundancy
  • report enzyme pairs of neofunctionalisations, which caused the EC to be considered “neofunctionalised”, and are in return contributing to redundancy
  • print them into nice HTML
Result 
core metabolism majority: 80%
neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)

Deltaproteobacteria:

core metabolism ECs: 228

"neofunctionalised" ECs: 36 (16%)

Neofunctionalisations contributing to robustness: 84

[see file Deltaproteobacteria_ROBUSTNESS_Neofunctionalisations-For-Contributed-EC.html]
Conclusion

Much more useful than a plain text list of cryptic IDs.

The well-known neofunctionalisation 2.6.1.1 <-> 2.6.1.9 does not occur here. Maybe the core metabolism’s majority percentage is too high, or both of the two EC numbers can only contribute to partial redundancy?

FEV_KEGG.Experiments.52.getCladeA()[source]
FEV_KEGG.Experiments.53 module
Context

In 52, we did this before, but this time we include partial robustness.

Question

Which neofunctionalised enzymes cause the core metabolism of Deltaproteobacteria to have increased redundancy? How much do they contribute? Grouped by contributed functions, sorted lexicographically, annotated with links to KEGG, annotated with human-readable names (if possible), and exported into an HTML file.

Method
  • get clade
  • get core metabolism
  • calculate “neofunctionalised” ECs
  • calculate redundancy
  • REPEAT for each “neofunctionalised” EC contributing to redundancy
  • report enzyme pairs of neofunctionalisations, which caused the EC to be considered “neofunctionalised”, and are in return contributing to redundancy
  • print them into nice HTML
Result 
core metabolism majority: 80%
neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)

Deltaproteobacteria:

core metabolism ECs: 228

"neofunctionalised" ECs: 36 (16%)

Neofunctionalisations contributing to robustness: 61
[see file Deltaproteobacteria_ROBUSTNESS_PARTIAL_Neofunctionalisations-For-Contributed-EC.html]

"neofunctionalised" ECs: 36 (16%)

Neofunctionalisations contributing to robustness: 91

[see file Deltaproteobacteria_ROBUSTNESS_BOTH_Neofunctionalisations-For-Contributed-EC.html]
Conclusion

In 52, we saw 84 neofunctionalisations contributing to full robustness. Additionally, 61 neofunctionalisations contribute to partial redundancy.

However, when adding these two sets of neofunctionalisations (ROBUSTNESS_BOTH), they result in only 91 different neofunctionalisations. This means that some neofunctionalisations contribute to both, full and partial robustness. This is to be expected, because EC numbers (of which a neofunctionalisation’s function change has at least two) can, if they are in a central position, easily contribute to the redundancy of multiple other EC numbers. Some of which may be fully redundant, some only partially redundant.

Note: the well-known neofunctionalisation 2.6.1.1 <-> 2.6.1.9 does not occur in 52. Possible causes were believed to be a high majority percentage, or that both of the two EC numbers can only contribute to partial redundancy. In Deltaproteobacteria_ROBUSTNESS_PARTIAL_Neofunctionalisations-For-Contributed-EC.html we see seven neofunctionalisations involving 2.6.1.1 and 2.6.1.9, therefore, the cause of the non-appearance in 52 was indeed that they only contribute to partial redundancy. This shows that it might be wise to choose partial types of redundancy, to receive more interesting results, especially when dealing with incomplete data such as KEGG’s GENE and PATHWAY databases.

FEV_KEGG.Experiments.53.getCladeA()[source]
FEV_KEGG.Experiments.54 module
Context

Combining the list of all neofunctionalisations, sorted by their function change, from 51, and the list of neofunctionalisations contributing to robustness, sorted by the EC number they provide robustness for, from 53.

E-value also plays an important role in the number of neofunctionalisations reported, because the bigger the E-value is, the easier two enzymes match as gene-duplicates, the higher the probability of a discovered function change, together resulting in a neofunctionalisation.

Question

Which neofunctionalisations exist in the core metabolism of Archaea, using a certain E-value? Grouped by function change, sorted lexicographically, annotated with links to KEGG, annotated with human-readable names (if possible), and exported into an HTML file.

Which neofunctionalised enzymes cause the core metabolism of Archaea to have increased redundancy? Grouped by contributed functions, sorted lexicographically, annotated with links to KEGG, annotated with human-readable names (if possible), and exported into an HTML file.

Method
  • get clade
  • get core metabolism
  • calculate “neofunctionalised” ECs
  • report neofunctionalisations
  • print them into nice HTML
  • calculate redundancy
  • REPEAT for each “neofunctionalised” EC contributing to redundancy
  • report enzyme pairs of neofunctionalisations, which caused the EC to be considered “neofunctionalised”, and are in return contributing to redundancy
  • print them into nice HTML
Result 
core metabolism majority: 80%
neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)

Archaea:

core metabolism ECs: 114


All neofunctionalisations: 1140
    [see Archaea_Neofunctionalisations-For-FunctionChange.html]

"neofunctionalised" ECs: 16 (14%)

Neofunctionalisations contributing to robustness: 93 (8%)
    [see Archaea_Neofunctionalisations-For-Contributed-EC.html]
Conclusion

Archaea do not seem to have many neofunctionalisations contributing to robustness. This might be limited by: - the size of the core metabolism, i.e. the majority percentage. - the E-value. The lower the E-value, the closer two enzymes’ sequences have to match, for them to be recognised as gene-duplicated. Using a higher E-value will greatly increase the number of neofunctionalisations reported. Of course, this will also increase the number of false-positives.

FEV_KEGG.Experiments.54.getClade()[source]
FEV_KEGG.Experiments.55 module
Context

Extending 54 by a list of all the alternative paths each neofunctionalisation (or rather one of their EC numbers) occurs on.

Question

Which neofunctionalisations exist in the core metabolism of Archaea, using a certain E-value? Grouped by function change, sorted lexicographically, annotated with links to KEGG, annotated with human-readable names (if possible), and exported into an HTML file.

Which neofunctionalised enzymes cause the core metabolism of Archaea to have increased redundancy? Grouped by contributed functions, sorted lexicographically, annotated with links to KEGG, annotated with human-readable names (if possible), and exported into an HTML file. Also listing each alternative path a neofunctionalisation occurs on, contributing to redundancy of the current group’s redundant EC number.

Method
  • get clade
  • get core metabolism
  • calculate “neofunctionalised” ECs
  • report neofunctionalisations
  • print them into nice HTML
  • calculate redundancy
  • REPEAT for each “neofunctionalised” EC contributing to redundancy
  • report enzyme pairs of neofunctionalisations, which caused the EC to be considered “neofunctionalised”, and are in return contributing to redundancy
  • report the alternative paths constituting the redundancy
  • print them into nice HTML
Result 
core metabolism majority: 80%
neofunctionalisation majority: 0% (this means that gene duplication within a single organism is enough)

Archaea:

core metabolism ECs: 114


All neofunctionalisations: 1140
    [see Archaea_Neofunctionalisations-For-FunctionChange.html]

"neofunctionalised" ECs: 16 (14%)

Neofunctionalisations contributing to robustness: 93 (8%)
    [see Archaea_Neofunctionalisations-For-Contributed-EC.html]
Conclusion

Nice and shiny paths.

FEV_KEGG.Experiments.55.getClade()[source]
Module contents

FEV_KEGG.Graph package

Subpackages
FEV_KEGG.Graph.Implementations package
Submodules
FEV_KEGG.Graph.Implementations.NetworkX module
class FEV_KEGG.Graph.Implementations.NetworkX.MultiDiGraph(incoming_graph_data=None, **attr)[source]

Bases: networkx.classes.multidigraph.MultiDiGraph, FEV_KEGG.Graph.Implementations.NetworkX.NetworkX

Represents a MultiDiGraph from NetworkX

Initialize a graph with edges, name, or graph attributes.

Parameters:
  • incoming_graph_data (input graph) – Data to initialize graph. If incoming_graph_data=None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python packages are installed the data can also be a NumPy matrix or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph.
  • attr (keyword arguments, optional (default= no attributes)) – Attributes to add to graph as key=value pairs.

See also

convert

Examples

>>> G = nx.Graph()   # or DiGraph, MultiGraph, MultiDiGraph, etc
>>> G = nx.Graph(name='my graph')
>>> e = [(1, 2), (2, 3), (3, 4)] # list of edges
>>> G = nx.Graph(e)

Arbitrary graph attribute pairs (key=value) may be assigned

>>> G = nx.Graph(e, day="Friday")
>>> G.graph
{'day': 'Friday'}
class FEV_KEGG.Graph.Implementations.NetworkX.MultiGraph(incoming_graph_data=None, **attr)[source]

Bases: networkx.classes.multigraph.MultiGraph, FEV_KEGG.Graph.Implementations.NetworkX.NetworkX

Represents a UndirectedMultiGraph from NetworkX

Initialize a graph with edges, name, or graph attributes.

Parameters:
  • incoming_graph_data (input graph) – Data to initialize graph. If incoming_graph_data=None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python packages are installed the data can also be a NumPy matrix or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph.
  • attr (keyword arguments, optional (default= no attributes)) – Attributes to add to graph as key=value pairs.

See also

convert

Examples

>>> G = nx.Graph()   # or DiGraph, MultiGraph, MultiDiGraph, etc
>>> G = nx.Graph(name='my graph')
>>> e = [(1, 2), (2, 3), (3, 4)] # list of edges
>>> G = nx.Graph(e)

Arbitrary graph attribute pairs (key=value) may be assigned

>>> G = nx.Graph(e, day="Friday")
>>> G.graph
{'day': 'Friday'}
class FEV_KEGG.Graph.Implementations.NetworkX.NetworkX[source]

Bases: object

Represents the NetworkX library

Module contents
Submodules
FEV_KEGG.Graph.Elements module
exception FEV_KEGG.Graph.Elements.DrugIdError[source]

Bases: Exception

Raised if a SubstanceID is created from a drug ID, because only compounds and glycans are useful in our model of metabolism.

class FEV_KEGG.Graph.Elements.EcNumber(ecNumberString: 4.2.3.1)[source]

Bases: FEV_KEGG.Graph.Elements.Element

Represents an enzyme of metabolism by EC number, e.g. ‘4.2.3.1’.

Parameters:

ecNumberString (str) – EC number represented as a string. Will be checked for correct formatting!
Variables:
  • self.ecNumberString (str) – E.g. ‘4.2.3.-‘.
  • self.ecNumberLevels (List[str]) – E.g. [‘4’, ‘2’, ‘3’, ‘-‘].
  • self.ecNumberLevelsInteger (List[int]) – E.g. [4, 2, 3, -1]. A wildcard is translated to -1.
  • self.description (str) – Descriptive name of the enzymes behind this EC number. May likely be None. Usually a list of synonymous names.
  • self.name (str) – Short name of the enzymes behind this EC number. May likely be None. Is the shortest name occuring in description.
  • self.reaction (str) – IUBMB string describing the reaction formula. May likely be None.
Raises:

ValueError – If EC number is not formatted correctly.

See also

FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph.addEcDescriptions
The function to download and add self.description, self.name, and self.reaction.
REGEX_PATTERN = re.compile('^[1-7]\\.(([1-9][0-9]{0,1})|\\-)\\.(((?<!\\-\\.)([1-9][0-9]{0,1}))|\\-)\\.(((?<!\\-\\.)([1-9][0-9]{0,2}))|\\-)$')
WILDCARD = '-'
addDescription()[source]

Query KEGG and add further description to this EC number.

Warning

Much slower than doing addEcDescriptions() for several EC numbers in bulk!

static addEcDescriptions(ecNumbers: Iterable[T_co])[source]

Query KEGG for further descriptions and add them to each EC number in ecNumbers.

contains(ecNumber: FEV_KEGG.Graph.Elements.EcNumber) → bool[source]

Check whether this EC number is a superset of ecNumber, made possibly by the wildcard.

Parameters:ecNumber (EcNumber) – The EC number to compare against.
Returns:True, if the other EC number is part of the set of EC numbers defined by wildcard dashes in the levels of this EC number. For example 1.2.3.- contains 1.2.3.1 up to 1.2.3.999, but 1.2.3.4 can only contain itself.
Return type:bool
ecNumberLevelsInteger
classmethod fromArray(ecNumberLevels: Iterable[T_co]) → FEV_KEGG.Graph.Elements.EcNumber[source]

Creates EcNumber object from single EC number levels.

Parameters:ecNumberLevels (Iterable) – Iterable of the EC number levels, can be int or str. For a wildcard, obviously only str is reasonable.
Raises:ValueError – If the resulting EC number is not formatted correctly.
hasWildcard() → bool[source]

Whether this EC number contains a wildcard.

Returns:True if this EC number contains a wildcard (-) at any level, otherwise, returns False.
Return type:bool
static insertWildcards(ecNumbers: Iterable[T_co], keepLevels=3, allowHigherWildcards=True, returnSet=True, deduplicateList=False) → Iterable[T_co][source]

Turns EC numbers without wildcards into EC numbers with wildcards.

Returning them in a list preserves order.

Parameters:
  • ecNumbers (Iterable) – The EcNumber objects to abstract using wildcards.
  • keepLevels (int, optional) – The first x levels of each EC number are kept intact. If keepLevels == 3, turns 1.2.3.4 into 1.2.3.-. Only 1, 2, 3, and 4 are allowed. EC numbers already containing wildcards are left unchanged.
  • allowHigherWildcards (bool, optional) – If False and there is a wildcard in a level above ‘keepLevels’ (e.g. 3):, 1.2.3.4 -> 1.2.3.- and 2.3.4.- -> 2.3.4.-, but 3.4.-.- is removed completely.
  • returnSet (bool, optional) – If True, returns results in a set. Takes precedence over ‘deduplicateList’, as sets automatically deduplicate.
  • deduplicateList (bool, optional) – If True, result list is deduplicated before returning, preserving order.
Returns:

Either a list or a set of abstracted EC numbers.
Return type:

Iterable
Raises:

ValueError – If keepLevels is not one of [1, 2, 3, 4].
matchingLevels(ecNumber: FEV_KEGG.Graph.Elements.EcNumber, wildcardMatchesNumber=True) → int[source]

Determines the number of levels which match between this EC number and ecNumber.

This could act as a coarse distance measure for EC numbers.

Parameters:
  • ecNumber (EcNumber) – The EC number to compare against.
  • wildcardMatchesNumber (bool, optional) – If True, a wildcard acts as a sure match: ‘1.-.-.-‘.matchingLevels(‘1.2.3.4’) = 4. If False, a wildcard only matches another wildcard.
Returns:

Number of consecutive levels that match, if any, starting with the first (leftmost). ‘1.2.3.4’.matchingLevels(‘1.2.6.7’) = 2 because the first two levels match consecutively. ‘1.2.3.4’.matchingLevels(‘2.2.3.4’) = 0 because the very first level does not match.
Return type:

int
static removeWildcards(ecNumbers: Iterable[T_co]) → Iterable[T_co][source]

Remove EC numbers containing wildcards from an Iterable.

Parameters:ecNumbers (Iterable[EcNumber]) – The EcNumber objects to check for wildcards.
Returns:A new Iterable of the same type, containing only EC numbers which do not have a wildcard (-) anywhere. This does not deduplicate EC numbers.
Return type:Iterable[EcNumber]
class FEV_KEGG.Graph.Elements.Element(uniqueID: str)[source]

Bases: object

Generic graph element with a uniqueID.

Comparable (==, !=, <, >, <=, >=) and hashable by this unique ID. Converting to a string returns the uniqueID.

Parameters:uniqueID (str) – String uniquely identifying this element among all other possible elements.
Variables:self.uniqueID (str) – Unique element ID.
getRestUrl()[source]

Get the link to KEGG’s REST-API for this EC number.

Essentially the same as getUrl(), but meant to be read by machines, therefore no eye-candy.

Returns:URL to KEGG’s REST-API
Return type:str
getUrl()[source]

Get the link to KEGG for this EC number.

Returns:URL to KEGG.
Return type:str
toHtml(short=False, noTd=False)[source]

Get the Element’s string representation surrounded by its URL as an HTML line.

class FEV_KEGG.Graph.Elements.Enzyme(organismAbbreviation: eco, geneName: b0004, ecNumberStrings: List[str], name: thrC = None, description: (RefSeq) hydrogenase 4, subunit = None)[source]

Bases: FEV_KEGG.Graph.Elements.Element

Represents an enzyme of metabolism.

It has exactly one GeneID, which is its unique identifier.

Parameters:
  • organismAbbreviation (str) – Abbreviation string of the organism this enzyme belongs to, as known to KEGG, e.g. ‘eco’. Must obviously be unique and existant in KEGG.
  • geneName (str) – Name of the gene which represents this enzyme, e.g. ‘b0004’. Will be combined with organismAbbreviation to form the unique GeneID. Thus, must be unique within the organism.
  • ecNumberStrings (List[str]) – List of strings representing the EC numbers associated with this enzyme. Will be split and parsed into EcNumber objects.
  • name (str, optional) – Colloquial name of this enzyme, e.g. ‘thrC’. This is not used for automatic identification, you may make it None.
  • description (str, optional) – Full description of this enzyme from KEGG, e.g. ‘(RefSeq) hydrogenase 4, subunit’. This is not used for automatic identification, you may make it None.
Variables:
  • self.organismAbbreviation (str) –
  • self.geneName (str) –
  • self.geneID (GeneID) –
  • self.name (str) –
  • self.ecNumbers (Set[EcNumber]) –
  • self.description (str) –
Raises:

ValueError – If organismAbbreviation and geneName do not form a valid gene ID. Or if any of the EC numbers in ecNumberStrings is not a valid EC number.

Note

This does not check if the organism, gene ID, EC numbers, or anything else actually exist in KEGG! You will find out eventually when trying to retrieve information about them.

classmethod fromGene(gene: FEV_KEGG.KEGG.DataTypes.Gene) → FEV_KEGG.Graph.Elements.Enzyme[source]

Creates an Enzyme from a FEV_KEGG.KEGG.DataTypes.Gene.

Parameters:gene (Gene) – Gene object, retrieved and parsed from KEGG GENE at some point.
Returns:An enzyme object.
Return type:Enzyme
Raises:ValueError – If organismAbbreviation and geneName do not form a valid gene ID. Or if any of the EC numbers in ecNumberStrings is not a valid EC number.
getEcNumbersString()[source]

EC numbers associated with this enzyme as a string.

Returns:EC numbers associated with this enzyme in a string, eg. ‘1.2.3.4, 2.3.4.5’
Return type:str
class FEV_KEGG.Graph.Elements.EnzymeComplete(gene: FEV_KEGG.KEGG.DataTypes.Gene)[source]

Bases: FEV_KEGG.Graph.Elements.Enzyme

Represents an enzyme of metabolism, saving the original underlying gene description gene for later manual use.

The underlying gene description is usually not necessary, use the parent class to save memory space.

Parameters:gene (Gene) – Gene object, retrieved and parsed from KEGG GENE at some point. Will be kept in memory in the gene attribute.
Variables:self.gene (FEV_KEGG.KEGG.DataTypes.Gene) – Original underlying gene description.
Raises:ValueError – See parent class.
class FEV_KEGG.Graph.Elements.GeneID(geneIDString: eco:b0004)[source]

Bases: FEV_KEGG.Graph.Elements.Element

Represents am enzyme of metabolism by gene ID, e.g. ‘eco:b0004’.

Parameters:geneIDString (str) – Gene ID represented by a string, e.g. ‘eco:b0004’. Will be checked for correct formatting!
Variables:self.geneIDString (str) –
Raises:ValueError – If gene ID is not formatted correctly.
REGEX_PATTERN = re.compile('^[a-z]{3,4}:[a-zA-Z0-9_\\-\\.]+$')
geneName

returns: ‘b0004’ from ‘eco:b0004’. :rtype: str

organismAbbreviation

returns: ‘eco’ from ‘eco:b0004’. :rtype: str

class FEV_KEGG.Graph.Elements.KeggOrthologyID(keggOrthologyIDString: K01733)[source]

Bases: FEV_KEGG.Graph.Elements.Element

Represents an enzyme of metabolism by KEGG Orthology ID.

Parameters:keggOrthologyIDString (str) – String representation of a KEGG Orthology ID. Will be checked for correct formatting!
Variables:self.keggOrthologyIDString (str) –
Raises:ValueError – If KEGG Orthology ID is not formatted correctly.
REGEX_PATTERN = re.compile('^K[0-9]{5}$')
class FEV_KEGG.Graph.Elements.ReactionID(keggReactionID: R01899)[source]

Bases: FEV_KEGG.Graph.Elements.Element

Represents a reaction of metabolism by reaction ID from KEGG, eg. ‘R01899’.

Parameters:keggReactionID (str) – Unique ID of the reaction.
Variables:self.keggReactionID (str) – Unique reaction ID.

Note

This does not check if the reaction actually exists in KEGG! You will find out eventually when trying to retrieve information about it.

class FEV_KEGG.Graph.Elements.SubstanceID(keggSubstanceID: C01102)[source]

Bases: FEV_KEGG.Graph.Elements.Element

Represents a substrate/product of metabolism by compound/glycan ID from KEGG, eg. ‘C01102’ or ‘G00160’.

Parameters:
  • keggSubstanceID (str) – Unique ID of the compound or glycan.
  • description (str, optional) – Descriptive chemical name of the compound/glycan.
Variables:
  • self.keggCompoundID (str) – Unique compound/glycan ID.
  • self.description (str) – Descriptive chemical name of the compound/glycan. May likely be None. Usually a list of synonymous names.
  • self.name (str) – Short chemical name of the compound/glycan. May likely be None. Is the shortest name occuring in description.
Raises:

DrugIdError – Drug IDs, eg. D08603, raise a DrugIdError, because only compounds and glycans are useful in our model of metabolism. Use the synonymous Compound ID instead.

Note

This does not check if the compound/glycan actually exists in KEGG! You will find out eventually when trying to retrieve information about it.

See also

FEV_KEGG.Graph.SubstanceGraphs.SubstanceGraph.addSubstanceDescriptions
The function to download and add self.description, and self.name.
REGEX_PATTERN = re.compile('^C|G[0-9]{5}$')
FEV_KEGG.Graph.Models module
class FEV_KEGG.Graph.Models.CommonGraphApi(underlyingRawGraph=None)[source]

Bases: object

Represents any type of graph.

The library to implement graphs is chosen here.

Parameters:

underlyingRawGraph (implementationLib, optional) – If not None, copies underlyingRawGraph and stores it for this object.
Variables:
  • self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation chosen in implementationLib.
  • self.name (str) – Custom name of the graph. This is often set, but not necessary in any calculations.
  • self.nodeCounts (Dict[Element, int], optional) – Number of precursor graphs which contained certain Element nodes still in this graph. None by default.
  • self.edgeCounts (Dict[Tuple[Element, Element, Element], int], optional) – Number of precursor graphs which contained a certain edge (a Tuple of three Element) still in this graph. None by default.
  • self.edgeElementCounts (Dict[Element, int], optional) – Number of precursor graphs which contained certain Element edge keys still in this graph. None by default.
__eq__(other: object)[source]

Determine equality of two graphs.

Parameters:other (object) – The object to compare this graph with.
Returns:Both graphs are considered equal, if they have identical memory addresses OR (the same class AND the same number of nodes and edges AND they are ismorphic). WARNING: isomorphism check is NP-hard!
Return type:bool
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
__ne__(other: object)[source]

Determine non-equality of two graphs.

This simply negates __eq__().

Parameters:other (object) – The object to compare this graph with.
Returns:Both graphs are considered inequal, if they do not have identical memory addresses NOR (the same class AND the same number of nodes and edges AND they are ismorphic). WARNING: isomorphism check is NP-hard!
Return type:bool
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
addEdge(node1: FEV_KEGG.Graph.Elements.Element, node2: FEV_KEGG.Graph.Elements.Element, key: FEV_KEGG.Graph.Elements.Element, isReversible: bool = False)[source]

Add an edge to the graph.

Parameters:
  • node1 (Element) – Node from which the newly created edge starts. Is added to the graph, if not already present.
  • node2 (Element) – Node at which the newly created edge ends. Is added to the graph, if not already present.
  • key (Element) – Edge key element annotating the newly created edge.
  • isReversible (bool, optional) – If True, both directions are added, swapping node1 and node2. If the graph is undirected, this option is ignored.
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationGraph.
addEdges(edges: Iterable[Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element]])[source]

Add edges to the graph.

Parameters:edges (Iterable[Tuple[Element, Element, Element]]) – Iterable of edge tuples, defined as (node1, node2, edge key). If the nodes do not already exist, they are silently added. If the graph is directed, the order of node1 and node2 counts as direction.
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
addNode(node: FEV_KEGG.Graph.Elements.Element)[source]

Add a node to the graph.

Parameters:node (Element) – Node to add to the graph, if not already present.
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationGraph.
addNodes(nodes: Iterable[FEV_KEGG.Graph.Elements.Element])[source]

Add nodes to the graph.

Parameters:nodes (Iterable[Element]) – Iterable of elements to be added as nodes.
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
classmethod composeAll(graphs: Iterable[CommonGraphApi], name: str = None, pathwaySet=None) → FEV_KEGG.Graph.Models.CommonGraphApi[source]

Simple UNION of node and edge lists.

A node is defined by its hash(). An edge is defined by Tuple[node1, node2, hash(edge key)], while the order of node1 and node2 encodes the direction, if the graph is directed. This is similar to union(), but aims at a special use case. You will most likely want to use union().

Parameters:
Returns:

Composition of all graphs by simple union operation. Includes pathwaySet, if given.
Return type:

CommonGraphApi
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
copy(underlyingRawGraph=None) → FEV_KEGG.Graph.Models.CommonGraphApi[source]

Shallow copy of the whole graph.

However, some attributes are explicitly copied (although each attribute might in itself be shallowly copied):

  • .underlyingRawGraph
  • .name
  • .nodeCounts
  • .edgeCounts
  • .edgeElementCounts
Parameters:underlyingRawGraph (FEV_KEGG.Graph.Implementations, optional) – If given, does not copy the underlying raw graph, but uses this one.
Returns:Shallow copy of the whole graph.
Return type:CommonGraphApi
difference(subtrahend: Graph to be subtracted, subtractNodes=False, updateName=False) → CommonGraphApi[source]

Difference between this graph and subtrahend graph, i.e. self - subtrahend.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • subtrahend (CommonGraphApi) – The graph to be subtracted.
  • subtractNodes (bool, optional) – If True, also remove all nodes present in subtrahend from this graph. WARNING: This may remove edges that only exist in this graph, because they are removed with their associated node!
  • updateName (bool, optional) – If True, update this graph’s name.
Returns:

A copy of this graph, containing all nodes which are present in this graph and all edges present in this graph, but which are not present in subtrahend.
Return type:

CommonGraphApi
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getComponents() → Generator[Set[T], None, None][source]

Get all isolated components.

For a directed graph, this considers weakly connected components, too. This means that there do not have to be edges in both directions to be counted as a component. Even an edge in only one direction counts as connecting a component.

Returns:Generator of any isolated component of the graph. Each represented by a set of their nodes, each represented by an Element.
Return type:Generator[Set[Element]]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getEdgeKeys() → Set[FEV_KEGG.Graph.Elements.Element][source]

Get edge key elements of all edges.

Returns:Set of all edge’s key elements, extracted from edge tuples of (node1, node2, edge key). Element objects which are the edge key of multiple edges are only returned once in the set.
Return type:Set[Element]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getEdges(fromNode: FEV_KEGG.Graph.Elements.Element = None, toNode: FEV_KEGG.Graph.Elements.Element = None) → Set[Tuple][source]

Get all edges, optionally directly between two nodes.

Parameters:
  • fromNode (Element) – The node where the edges start.
  • toNode (Element) – The node where the edges end.
Returns:

A set-like object of all edges, defined by Tuples of (node1, node2, edge key). This is not a copy, but the original internal list. Do not change while iterating! Make a copy instead: copy = list(getEdges()) Only returns outgoing edges, so that no edge is reported twice. If fromNode and toNode are specified, returns only edges directly between these nodes. If there are none, returns an empty set. Does not report whole paths, only single edges!
Return type:

Set[Tuple[Element, Element, Element]]
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getEdgesForKey() → Dict[FEV_KEGG.Graph.Elements.Element, List[Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element]]][source]

Get all edges, sorted by their key element.

Returns:A dict of all key elements pointing to a list of their edge tuples.
Return type:Dict[Element, List[Tuple[Element, Element, Element]]]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getEdgesFromKey(key: FEV_KEGG.Graph.Elements.Element) → List[Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element]][source]

Get all edges with a certain key element.

Parameters:key (Element) – The key element of the edges to be returned.
Returns:A set of all edges, defined by Tuples of (node1, node2, edge key), where edge key == key. This is a copy of the original internal list. Only returns outgoing edges, so that no edge is reported twice.
Return type:Set[Tuple[Element, Element, Element]]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getIsolatedNodes() → Iterable[FEV_KEGG.Graph.Elements.Element][source]

Get all nodes without any edge to another node.

Returns:Iterable of nodes without any edge to another node. Even though the type does not enforce it, this should never return duplicates.
Return type:Iterable[Element]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getLargestComponent() → FEV_KEGG.Graph.Models.CommonGraphApi[source]

Get the largest component.

Returns:Copy of this graph, reduced to the largest component.
Return type:CommonGraphApi
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getLargestComponentNodes() → Set[FEV_KEGG.Graph.Elements.Element][source]

Get nodes of the largest component.

Returns:Set of all nodes, represented by an Element, of the largest component.
Return type:Set[Element]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getNodes() → Set[FEV_KEGG.Graph.Elements.Element][source]

Get all nodes.

Returns:A set-like object of all nodes. Even though the type list does not enforce it, this should never return duplicates.
Return type:Set[Element]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
getPaths(fromNode: FEV_KEGG.Graph.Elements.Element, toNode: FEV_KEGG.Graph.Elements.Element) → Set[FEV_KEGG.Graph.Models.Path][source]

Get all simple paths between two nodes.

Simple paths are loop-free. If one of the two nodes is None, searches for all paths starting/ending in the the one node given.

Parameters:
  • fromNode (Element) – Where to start searching for paths. If None, searches for all paths ending in toNode.
  • toNode (Element) – Where to stop searching. If None, searches for all paths starting in fromNode.
Returns:

Set of all paths between fromNode and toNode. If fromNode or toNode does not exist, or there is no path, returns an empty list.
Return type:

Set[Path]
Raises:
  • NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
  • ValueError – If both fromNode and toNode are given as None.
getShortestPaths(fromNode: FEV_KEGG.Graph.Elements.Element, toNode: FEV_KEGG.Graph.Elements.Element) → Set[FEV_KEGG.Graph.Models.Path][source]

Get all shortest paths between two nodes.

Parameters:
  • fromNode (Element) – Where to start searching for shortest paths. If None, searches for all shortest paths ending in toNode, which are obviously all of length 1.
  • toNode (Element) – Where to stop searching. If None, searches for all shortest paths starting in fromNode, which are obviously all of length 1.
Returns:

Set of all shortest paths between fromNode and toNode. If fromNode or toNode does not exist, or there is no path, returns an empty list.
Return type:

Set[Path]

Note

If one of the two nodes is None, determine if there is any path starting/ending in the one node given. If this is the case, the shortest paths are obviously always of length 1.

Raises:
  • NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
  • ValueError – If both fromNode and toNode are given as None.
getSubgraph(byNodes: Iterable[FEV_KEGG.Graph.Elements.Element] = None, byEdges: Iterable[Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element]] = None) → FEV_KEGG.Graph.Models.CommonGraphApi[source]

Get sub-graph defined by nodes or edges.

If both are passed, only nodes are used. If nothing is passed, None is returned.

Parameters:
  • byNodes (Iterable[Element], optional) – Iterable of nodes defining the sub-graph. All edges between these nodes are conserved.
  • byEdges (Iterable[Tuple[Element, Element, Element]], optional) – Iterable of edges defining the sub-graph, each defined as (node1, node2, edge key). All nodes involved with these edges, i.e. all node1’s and node2’s are preserved.
Returns:

Copy of the sub-graph specified by either nodes or edges.
Return type:

CommonGraphApi
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
implementationLib

alias of FEV_KEGG.Graph.Implementations.NetworkX.NetworkX

intersection(withGraph: Graph to be intersected with, allows list of graphs, addCount=False, updateName=False) → CommonGraphApi[source]

Intersection of this graph and the graph(s) in withGraph.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • withGraph (CommonGraphApi or Iterable[CommonGraphApi]) – The graph(s) this graph is to be intersected with.
  • addCount (bool, optional) –

    If True, the returned graph contains extra dicts:

    • graph.nodeCounts[node] = number of graphs which contained this node
    • graph.edgeCounts[(node, node, element)] = number of graphs which contained this edge
    • graph.edgeElementCounts[element] = number of graphs which contained this element
  • updateName (bool, optional) – If True, update this graph’s name.
Returns:

A copy of this graph, containing nodes and edges present in both this graph and the other graph(s).
Return type:

CommonGraphApi
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
majorityIntersection(withGraph: Graph to be majority-intersected with, allows list of graphs, majorityPercentage=51, addCount=False, updateName=False) → CommonGraphApi[source]

Majority-Intersection of this graph and the graph(s) in withGraph.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • withGraph (CommonGraphApi or Iterable[CommonGraphApi]) – The graph(s) this graph is to be intersected with.
  • majorityPercentage (float, optional) – The majority percentage means ‘at least x%’ and is rounded up. For example 90% of 11 organisms (including the organism this method is called on) would be ceiling(9,9) = 10 organisms. If the rounded majority total effectively equated to 100% of all graphs, regular intersection() is called instead. If only one graph is passed in withGraph AND the rounded majority total effectively equates 1, regular union() is called instead.
  • addCount (bool, optional) –

    If True, the returned graph contains extra dicts:

    • graph.nodeCounts[node] = number of graphs which contained this node
    • graph.edgeCounts[(node, node, element)] = number of graphs which contained this edge
    • graph.edgeElementCounts[element] = number of graphs which contained this element
  • updateName (bool, optional) – If True, update this graph’s name.
Returns:

A copy of this graph, containing all nodes and edges present in the majority of this graph and the other graph(s).
Return type:

CommonGraphApi
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
name

Custom name of the graph.

This is often set in calcuations, but not used for any calculations.

Returns:Custom name of the graph.
Return type:str
removeEdge(node1: FEV_KEGG.Graph.Elements.Element, node2: FEV_KEGG.Graph.Elements.Element, key: FEV_KEGG.Graph.Elements.Element, bothDirections: bool = False)[source]

Remove an edge from the graph.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • node1 (Element) – Node from which the edge to be removed starts. Is not removed itself.
  • node2 (Element) – Node at which the edge to be removed ends. Is not removed itself.
  • key (Element) – Edge key element annotating the edge to be removed.
  • bothDirections (bool, optional) – If True, both directions are removed, swapping node1 and node2. If the graph is undirected, this option is ignored.
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationGraph.
removeEdges(edges: Iterable[Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element]])[source]

Remove certain edges.

Parameters:edges (Iterable[Tuple[Element, Element, Element]]) – Iterable of edge tuples for edges to be removed, defined as (node1, node2, edge key). If an edge to be removed does not exist, the next edge will be tried, without any error message. If the graph is directed, the order of node1 and node2 counts as direction. The edge of opposing direction is not removed.
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
removeEdgesByElements(elements: Iterable[FEV_KEGG.Graph.Elements.Element])[source]

Removes all edges associated with each of the Element in elements.

Parameters:elements (Iterable[Element]) – Iterable of edge keys. Every edge keyed with an edge key equal (by __eq__) to any of these elements is removed. Direction of the graph does not affect removal.
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
removeIsolatedNodes()[source]

Remove all nodes without any edge to another node.

Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
removeNodes(nodes: Iterable[FEV_KEGG.Graph.Elements.Element])[source]

Remove all nodes.

Parameters:nodes (Iterable[Element]) – Iterable of elements representing nodes to be removed. Any edges involving these nodes are removed as well!
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
removeSmallComponents(upToNumberOfNodes: int)[source]

Remove every isolated component of the graph with a total count of nodes <= upToNumberOfNodes.

For a directed graph, this considers weakly connected components, too. This means that there do not have to be edges in both directions to be counted as a component. Even an edge in only one direction counts as connecting a component.

Parameters:upToNumberOfNodes (int) – Maximum number of nodes a component has to connect to be completely removed.
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
replaceEdgeElement(edge: Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element], newElement: FEV_KEGG.Graph.Elements.Element, bothDirections: bool = False)[source]

Replaces a certain edge key element, if the edge is present, with another element.

Silently ignores non-existing edge, especially never adds the new edge. Treats both directions independently.

Parameters:
  • edge (Tuple[Element, Element, Element]) – Tuple representing the edge which key element is to be replaced.
  • newElement (Element) – The element to replace the edge’s former key element.
  • bothDirections (bool, optional) – If True, automatically replace the edge key element of both directions. If the other direction does not exist, nothing happens.
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
replaceNode(oldNode: FEV_KEGG.Graph.Elements.Element, newNode: FEV_KEGG.Graph.Elements.Element)[source]

Replaces a certain node, if present, with another node.

Silently ignores non-existing nodes.

Parameters:
  • oldNode (Element) – Node to be replaced.
  • newNode (Element) – Node used to replace the oldNode.
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
replaceNodes(oldToNew: Dict[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element])[source]

Replaces certain nodes, if present, with another node each.

Silently ignores non-existing nodes.

Parameters:oldToNew (Dict[Element, Element]) – Node to be replaced pointing to the node to replace it.
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
union(withGraph: Graph to be unified with, allows list of graphs, addCount=False, updateName=False) → CommonGraphApi[source]

Union of this graph and the graph(s) in withGraph.

Parameters:
  • withGraph (CommonGraphApi or Iterable[CommonGraphApi]) – The graph(s) this graph is to be unified with.
  • addCount (bool, optional) –

    If True, the returned graph contains extra dicts:

    • graph.nodeCounts[node] = number of graphs which contained this node
    • graph.edgeCounts[(node, node, element)] = number of graphs which contained this edge
    • graph.edgeElementCounts[element] = number of graphs which contained this element
  • updateName (bool, optional) – If True, update this graph’s name.
Returns:

A copy of this graph, containing all nodes and all edges present in any of this graph or the other graph(s).
Return type:

CommonGraphApi
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationLib.
class FEV_KEGG.Graph.Models.DirectedMultiGraph(underlyingRawGraph: implementationGraph = None)[source]

Bases: FEV_KEGG.Graph.Models.CommonGraphApi

Represents a directed multigraph.

Parameters:

underlyingRawGraph (implementationGraph, optional) – If not None, copies underlyingRawGraph and stores it for this object.
Variables:
  • self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation chosen in implementationLib.
  • self.name (str) – Custom name of the graph. This is often set, but not necessary in any calculations.
  • self.nodeCounts (Dict[Element, int], optional) – Number of precursor graphs which contained certain Element nodes still in this graph. None by default.
  • self.edgeCounts (Dict[Tuple[Element, Element, Element], int], optional) – Number of precursor graphs which contained a certain edge (a Tuple of three Element) still in this graph. None by default.
  • self.edgeElementCounts (Dict[Element, int], optional) – Number of precursor graphs which contained certain Element edge keys still in this graph. None by default.
getUnidirectionalEdges() → Set[Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element]][source]

Get all edges which are unidirectional only.

Returns:Set of all edge tuples (node1, node2, edge key) that have only one direction, i.e. there is no other edge tuple in reverse direction (node2, node1, edge key).
Return type:Set[Tuple[Element, Element, Element]]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationGraph.
getUnidirectionalEdgesElements() → Set[FEV_KEGG.Graph.Elements.Element][source]

Get the edge key elements of all edges which are unidirectional only.

Returns:Set of all edge key elements of edges returned by getUnidirectionalEdges().
Return type:Set[Element]
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationGraph.
implementationGraph

alias of FEV_KEGG.Graph.Implementations.NetworkX.MultiDiGraph

toUndirectedGraph(keepUnidirectionalEdges=False) → FEV_KEGG.Graph.Models.UndirectedMultiGraph[source]

Create undirected graph from this directed graph.

Parameters:keepUnidirectionalEdges (bool, optional) – If True, treat unidirectional edges in directedMultiGraph as undirected edges, thus keep them for this graph. If False (default), undirected edges are only created if there are edges for both directions in directedMultiGraph.
Returns:Undirected graph converted from this directed graph.
Return type:UndirectedMultiGraph
Raises:NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationGraph.
class FEV_KEGG.Graph.Models.MarkedPath(path: FEV_KEGG.Graph.Models.Path, specialKeys: Set[FEV_KEGG.Graph.Elements.Element] = None, specialNodes: Set[FEV_KEGG.Graph.Elements.Element] = None)[source]

Bases: FEV_KEGG.Graph.Models.Path

Immutable linear Path, including markings for special edges/nodes.

Parameters:
  • path (Path) – The path to be marked.
  • specialKeys (Set[Element], optional) – Special edge keys.
  • specialNodes (Set[Element], optional) – Special nodes.
Variables:
  • self.specialKeys (Set[Element]) – Set of edge keys of the path which have been marked as special. None if specialKeys == None, empty if no special edges found. Special edges with parallel edges are also listed here.
  • self.parallelSpecialKeys (Dict[Element, int]) – If there are multiple edges between two nodes, and one of them is marked as special, this special edge is one of x edges between those nodes. This dictionary contains the special edge pointing to its x. Special edges without parallel edges are not listed here. None if specialKeys == None, empty if no special edges with parallel edges found.
  • self.specialNodes (Set[Element]) – Set of nodes of the path which have been marked as special. None if specialNodes == None, empty if no special nodes found.
Raises:

ValueError – If both specialKeys and specialNodes are None.
hasSpecialKey

Whether this marked path has a special edge.

Returns:
Return type:bool
hasSpecialNode

Whether this marked path has a special node.

Returns:
Return type:bool
class FEV_KEGG.Graph.Models.MutablePath(node1: FEV_KEGG.Graph.Elements.Element, edge1: FEV_KEGG.Graph.Elements.Element, node2: FEV_KEGG.Graph.Elements.Element)[source]

Bases: object

Mutable directed path of nodes connected by multiple edges.

The path can be elongated after creation. Cycles or loops are not forbidden, you should stay aware of them.

Parameters:
  • node1 (Element) – First node of the path.
  • edge1 (Element or Iterable[Element]) – First edge key of the path, connecting node1 and node2. May be an Iterable, if multiple edges connect the two nodes.
  • node2 (Element) – Second node of the path.
Variables:
  • self.nodes (List[Element]) – List of nodes in order of appearance in the path.
  • self.edges (List[Element or FrozenSet[Element]]) – List of multi-edges in order of appearance in the path. A multi-edge may be just a single edge, or a set of parallel edges.
  • self.edgesExpanded (Set[Element]) – Set of all edges in the path in arbitrary order. This is calculated by expanding all multi-edges in self.edges into a single set.
  • self.path (List[Element or FrozenSet[Element]]) – List of nodes and multi-edges, alternating in order of appearance in the path. A multi-edge may be just a single edge, or a set of parallel edges.
Raises:
  • ValueError – If edge1 is an empty Iterable.
  • TypeError – If you try to use a mutable path in a set.

Warning

A path must be made immutable to be able to use it in a set! See Path. Otherwise, a TypeError will be raised at some point.

edges
edgesExpanded
elongate(nextEdge: FEV_KEGG.Graph.Elements.Element, nextNode: FEV_KEGG.Graph.Elements.Element)[source]

Elongates the path by another (multiple) edge and node.

Parameters:
  • nextEdge (Element or Iterable[Element]) – Next edge key of the path, connecting the last node with nextNode. May be an Iterable, if multiple edges connect the two nodes.
  • nextNode (Element) – Next node of the path.
Raises:

ValueError – If nextEdge is an empty Iterable.
nodes
class FEV_KEGG.Graph.Models.Path(mutablePath: FEV_KEGG.Graph.Models.MutablePath)[source]

Bases: object

Directed path of nodes connected by multiple edges, immutable.

The path can not be changed after creation. Cycles or loops are not forbidden, you should stay aware of them.

Parameters:

mutablePath (MutablePath) – The path to be made immutable.
Variables:
  • self.nodes (Tuple[Element]) – List of nodes in order of appearance in the path.
  • self.edges (Tuple[Element or FrozenSet[Element]]) – List of multi-edges in order of appearance in the path. A multi-edge may be just a single edge, or a set of parallel edges.
  • self.edgesExpanded (FrozenSet[Element]) – Set of all edges in the path in arbitrary order. This is calculated by expanding all multi-edges in self.edges into a single set.
  • self.path (Tuple[Element or FrozenSet[Element]]) – List of nodes and multi-edges, alternating in order of appearance in the path. A multi-edge may be just a single edge, or a set of parallel edges.
Raises:
  • ValueError – If edge1 is an empty Iterable.
  • TypeError – If you try to use a mutable path in a set.

Warning

A path must be made immutable to be able to use it in a set! See Path. Otherwise, a TypeError will be raised at some point.

edges
edgesExpanded
nodes
toHtml(short=False)[source]
class FEV_KEGG.Graph.Models.UndirectedMultiGraph(underlyingRawGraph: implementationGraph = None)[source]

Bases: FEV_KEGG.Graph.Models.CommonGraphApi

Represents an undirected multi graph.

Parameters:

underlyingRawGraph (implementationGraph, optional) – If not None, copies underlyingRawGraph and stores it for this object.
Variables:
  • self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation chosen in implementationLib.
  • self.name (str) – Custom name of the graph. This is often set, but not necessary in any calculations.
  • self.nodeCounts (Dict[Element, int], optional) – Number of precursor graphs which contained certain Element nodes still in this graph. None by default.
  • self.edgeCounts (Dict[Tuple[Element, Element, Element], int], optional) – Number of precursor graphs which contained a certain edge (a Tuple of three Element) still in this graph. None by default.
  • self.edgeElementCounts (Dict[Element, int], optional) – Number of precursor graphs which contained certain Element edge keys still in this graph. None by default.
classmethod fromDirectedMultiGraph(directedMultiGraph: FEV_KEGG.Graph.Models.DirectedMultiGraph, keepUnidirectionalEdges=False)[source]

Create undirected graph from a directed graph.

Parameters:
  • directedMultiGraph (DirectedMultiGraph) – Directed graph to use for conversion.
  • keepUnidirectionalEdges (bool, optional) – If True, treat unidirectional edges in directedMultiGraph as undirected edges, thus keep them for this graph. If False (default), undirected edges are only created if there are edges for both directions in directedMultiGraph.
Returns:

Undirected graph converted from directedMultiGraph.
Return type:

UndirectedMultiGraph
Raises:

NotImplementedError – If this function has not been adapted to the chosen graph implementation, yet. See implementationGraph.
implementationGraph

alias of FEV_KEGG.Graph.Implementations.NetworkX.MultiGraph

FEV_KEGG.Graph.SubstanceGraphs module
class FEV_KEGG.Graph.SubstanceGraphs.Conversion[source]

Bases: object

static KeggPathway2SubstanceReactionGraph(pathway: FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway, localVerbosity=1) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceReactionGraph[source]

Converts an organism’s pathway into a SubstanceReactionGraph.

Parameters:
Returns:

The substance-reaction graph calculated from pathway.
Return type:

SubstanceReactionGraph
classmethod KeggPathwaySet2SubstanceReactionGraph(pathways: Set[FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway], localVerbosity=1, name=None) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceReactionGraph[source]

Combine several pathways of an organism into one SubstanceReactionGraph.

Deduplicates nodes and edges.

Parameters:
  • pathways (Set[KGML_pathway.Pathway]) –
  • localVerbosity (int, optional) – Verbosity to be used locally. Useful to silence useless log messages. See FEV_KEGG.settings.verbosity.
  • name (str, optional) – Name to use for the new graph.
Returns:

The substance-reaction graph calculated from pathways.
Return type:

SubstanceReactionGraph
static SubstanceEnzymeGraph2SubstanceEcGraph(substanceEnzymeGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Convert a SubstanceEnzymeGraph into a SubstanceEcGraph.

Parameters:substanceEnzymeGraph (SubstanceEnzymeGraph) –
Returns:The substance-EC graph calculated from the substance-enzyme graph.
Return type:SubstanceEcGraph
static SubstanceGeneGraph2SubstanceEcGraph(substanceGeneGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGeneGraph, noMultifunctional=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Convert a SubstanceGeneGraph into a SubstanceEcGraph.

Parameters:
  • substanceGeneGraph (SubstanceGeneGraph) –
  • noMultifunctional (bool, optional) – If True, does not return enzymes associated with more than one EC number.
Returns:

The substance-EC graph calculated from the substance-gene graph.
Return type:

SubstanceEcGraph

Warning

Skips the substance-enzyme step. Still parses genes from Database, this is slow and expensive!

static SubstanceGeneGraph2SubstanceEnzymeGraph(substanceGeneGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGeneGraph, noMultifunctional=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Convert a SubstanceGeneGraph into a SubstanceEnzymeGraph.

Each unique gene ID is mapped to the same unique enzyme, because enzymes are unique by their gene ID.

Parameters:
  • substanceGeneGraph (SubstanceGeneGraph) –
  • noMultifunctional (bool, optional) – If True, does not return enzymes associated with more than one EC number.
Returns:

The substance-enzyme graph calculated from the substance-gene graph.
Return type:

SubstanceEnzymeGraph

Warning

Parses genes from Database, this is slow and expensive!

static SubstanceReactionGraph2SubstanceGeneGraph(substanceReactionGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceReactionGraph) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceGeneGraph[source]

Convert a SubstanceReactionGraph into a SubstanceGeneGraph.

Uses pathway information embedded into the substanceReactionGraph.

Parameters:substanceReactionGraph (SubstanceReactionGraph) –
Returns:The substance-gene graph calculated from the substance-reaction graph.
Return type:SubstanceGeneGraph
class FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph(underlyingRawGraph: implementationGraph = None)[source]

Bases: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGraph

Directed graph with SubstanceID nodes and EcNumber edges, allowing multiple edges.

Links two FEV_KEGG.Graph.Elements.SubstanceID (compound or glycan) nodes with each FEV_KEGG.Graph.Elements.EcNumber edge, associated with an FEV_KEGG.Graph.Elements.Enzyme, associated with a FEV_KEGG.Graph.Elements.GeneID, associated with a FEV_KEGG.Graph.Elements.ReactionID they occur in.

Variables:
  • self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation.
  • self.name (str) – Custom name of the graph. This is often set, but not necessary in any calculations.
  • self.substanceCounts (Dict[SubstanceID, int], optional) – Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.
  • self.ecCounts (Dict[Elements.EcNumber, int], optional) – Number of precursor graphs which contained certain EcNumber edge keys still in this graph. None by default.
addEC(substrate: FEV_KEGG.Graph.Elements.SubstanceID, product: FEV_KEGG.Graph.Elements.SubstanceID, ecNumber: FEV_KEGG.Graph.Elements.EcNumber, isReversible: bool = False)[source]

Add an ecNumber between the substances substrate and product.

Parameters:
  • substrate (SubstanceID) – Automatically added, if not already in the graph.
  • product (SubstanceID) – Automatically added, if not already in the graph.
  • ecNumber (EcNumber) –
  • isReversible (bool, optional) – If True, add in both directions, swapping substrate and product.
addEcDescriptions()[source]

Downloads and adds descriptions to .description, .name, and .reaction fields of each EC edge key.

Warning

This causes many downloads and is very slow when nothing has been downloaded to cache yet!

See also

FEV_KEGG.KEGG.DataTypes.EcEnzyme()
The data type occuring in KEGG used to download the info.
ecCounts

Number of precursor graphs which contained certain GeneID edge keys still in this graph. None by default.

static fromSubstanceEnzymeGraph(substanceEnzymeGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph)[source]

Create SubstanceEcGraph from a SubstanceEnzymeGraph.

Replaces Enzymes with their EcNumber. Splits Enzymes with several EC numbers. Deduplicates Enzymes with the same EC number. See the structure of a KEGG KGML pathway description file for further insight.

Parameters:substanceEnzymeGraph (SubstanceEnzymeGraph) – The substance-enzyme graph to use for creating this graph.
Returns:A new substance-EC graph.
Return type:SubstanceEcGraph
static fromSubstanceGeneGraph(substanceGeneGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGeneGraph)[source]

Create SubstanceEcGraph from a SubstanceGeneGraph.

Replaces GeneIDs with their EcNumber. Splits GeneIDs with several EC numbers. Deduplicates GeneIDs with the same EC number. See the structure of a KEGG KGML pathway description file for further insight.

Parameters:substanceGeneGraph (SubstanceGeneGraph) – The substance-gene graph to use for creating this graph.
Returns:A new substance-EC graph.
Return type:SubstanceEcGraph
getECs() → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get all EC numbers.

Returns:Set of all EC numbers in this graph.
Return type:Set[EcNumber]
getPartialEcNumberEdges() → List[Tuple[FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.EcNumber]][source]

Get all edges annotated with a partial EC number, i.e. containing a wildcard ‘-‘.

Returns:List of all edge tuples where its EC number is partial, i.e. has less than the full four EC levels, e.g. ‘4.1.2.-’. Even though the type list does not enforce it, this should never return duplicates.
Return type:List[Tuple[SubstanceID, SubstanceID, EcNumber]]
getPartialEcNumbers() → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get all partial EC numbers, i.e. containing a wildcard ‘-‘.

Returns:All EC numbers in this graph with less than the full four EC levels, e.g. ‘4.1.2.-‘.
Return type:Set[EcNumber]
getUnidirectionalEcNumbers() → Set[FEV_KEGG.Graph.Elements.EcNumber][source]

Get all EC numbers which have only one direction.

Returns:Set of EC numbers which take part in an edge with only one direction. Meaning there is no edge with the opposite direction between the same substances, annotated with the same gene.
Return type:Set[EcNumber]
removeAllECsExcept(ecToKeep: Iterable[FEV_KEGG.Graph.Elements.EcNumber])[source]

Remove all genes which are not in ecToKeep.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:ecToKeep (Iterable[EcNumber]) – Iterable of EC numbers to keep in the graph. All other genes are removed.
removeECs(ecNumbers: Iterable[FEV_KEGG.Graph.Elements.EcNumber])[source]

Remove all occurences of certain EC numbers.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:ecNumbers (Iterable[EcNumber]) – Iterable of EC numbers to be completely removed from the graph.
removeEcEdge(substrate: FEV_KEGG.Graph.Elements.SubstanceID, product: FEV_KEGG.Graph.Elements.SubstanceID, ecNumber: FEV_KEGG.Graph.Elements.EcNumber, bothDirections: bool = False)[source]

Remove a ecNumber between substrate and product.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • substrate (SubstanceID) – Not removed from the graph.
  • product (SubstanceID) – Not removed from the graph.
  • ecNumber (EcNumber) –
  • bothDirections (bool, optional) – If True, remove both directions, swapping substrate and product.
removeEcEdges(ecEdges: List[Tuple[FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.EcNumber]])[source]

Remove all EC numbers in certain edges.

Parameters:ecEdges (List[Tuple[SubstanceID, SubstanceID, EcNumber]]) – List of tuples, each describing an edge to be removed from the graph. If an edge to be removed does not exist, the next edge will be tried, without any error message.
removePartialEcNumbers()[source]

Remove edges annotated with a partial EC number, i.e. containing a wildcard ‘-‘.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

substanceCounts

Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.

class FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph(underlyingRawGraph: implementationGraph = None)[source]

Bases: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGraph

Directed graph with SubstanceID nodes and Enzyme edges, allowing multiple edges.

Links two FEV_KEGG.Graph.Elements.SubstanceID (compound or glycan) nodes with each FEV_KEGG.Graph.Elements.Enzyme edge, associated with a FEV_KEGG.Graph.Elements.GeneID, associated with a FEV_KEGG.Graph.Elements.ReactionID they occur in. Replaces each GeneID object with its associated Enzyme object.

Variables:
  • self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation.
  • self.name (str) – Custom name of the graph. This is often set, but not necessary in any calculations.
  • self.substanceCounts (Dict[SubstanceID, int], optional) – Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.
  • self.enzymeCounts (Dict[Elements.Enzyme, int], optional) – Number of precursor graphs which contained certain Enzyme edge keys still in this graph. None by default.
  • self.indexOnEC (Dict[EcNumber, Set[Enzyme]]) – Index to find all enzymes by a certain EC number.
  • self.indexOnGeneID (Dict[GeneID, Enzyme]) – Index to find an enzyme by its gene ID. An enzyme is uniquely identified by its gene ID.

Warning

Automatically parses genes from KEGG, this is slow and expensive!

addEdge(node1: FEV_KEGG.Graph.Elements.Element, node2: FEV_KEGG.Graph.Elements.Element, key: FEV_KEGG.Graph.Elements.Element, isReversible: bool = False)[source]

Automatically updates the indices. See FEV_KEGG.Graph.Models.DirectedMultiGraph for the original function.

addEdges(edges: List[Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element]])[source]

Automatically updates the indices. See FEV_KEGG.Graph.Models.DirectedMultiGraph for the original function.

addEnzyme(substrate: FEV_KEGG.Graph.Elements.SubstanceID, product: FEV_KEGG.Graph.Elements.SubstanceID, enzyme: FEV_KEGG.Graph.Elements.Enzyme, isReversible: bool = False)[source]

Add an enzyme between the substances substrate and product.

Automatically updates indices.

Parameters:
  • substrate (SubstanceID) – Automatically added, if not already in the graph.
  • product (SubstanceID) – Automatically added, if not already in the graph.
  • enzyme (Enzyme) –
  • isReversible (bool, optional) – If True, add in both directions, swapping substrate and product.
copy(underlyingRawGraph=None)[source]

Shallow copy of the whole graph.

However, some attributes are explicitly copied (although each attribute might in itself be shallowly copied):

  • .underlyingRawGraph
  • .name
  • .nodeCounts
  • .edgeCounts
  • .edgeElementCounts
  • .indexOnEC
  • .indexOnGeneID
Parameters:underlyingRawGraph (FEV_KEGG.Graph.Implementations, optional) – If given, does not copy the underlying raw graph, but uses this one.
Returns:Shallow copy of the whole graph.
Return type:SubstanceReactionGraph
enzymeCounts

Number of precursor graphs which contained certain Enzyme edge keys still in this graph. None by default.

static fromSubstanceGeneGraph(substanceGeneGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGeneGraph)[source]

Create SubstanceEnzymeGraph from a SubstanceGeneGraph.

Replaces reactions with their associated genes. Splits reactions associated with several genes. Deduplicates reactions associated with the same gene. See the structure of a KEGG KGML pathway description file for further insight.

Parameters:substanceGeneGraph (SubstanceGeneGraph) – The substance-gene graph to use for creating this graph. Apart from the graph structure itself, downloads from KEGG GENE are needed!
Returns:A new substance-enzyme graph.
Return type:SubstanceEnzymeGraph

Warning

Automatically parses genes from KEGG, this is slow and expensive!

getEnzymeForGeneID(geneID: FEV_KEGG.Graph.Elements.GeneID) → FEV_KEGG.Graph.Elements.Enzyme[source]

Get the enzyme uniquely identified with geneID.

Parameters:geneID (GeneID) – The gene encoding the enzyme.
Returns:The enzyme in this graph identified by the given geneID. If there is no such geneID, returns None.
Return type:Enzyme
getEnzymes() → Set[FEV_KEGG.Graph.Elements.Enzyme][source]

Get all enzymes.

Returns:Set of all enzymes in this graph.
Return type:Set[Enzyme]
getEnzymesForEcNumber(ecNumber: FEV_KEGG.Graph.Elements.EcNumber) → Set[FEV_KEGG.Graph.Elements.Enzyme][source]

Get enzymes associated with a certain EC number.

Parameters:ecNumber (EcNumber) –
Returns:Set of enzymes associated with the EC number in the ecNumber parameter. If there is no such EC number, returns an empty set.
Return type:Set[Enzyme]
getGeneIDsForEcNumber(ecNumber: FEV_KEGG.Graph.Elements.EcNumber) → Set[FEV_KEGG.Graph.Elements.GeneID][source]

Get genes associated with a certain EC number.

Parameters:ecNumber (EcNumber) –
Returns:Set of genes associated with the EC number in the ecNumber parameter. If there is no such EC number, returns an empty set.
Return type:Set[GeneID]
getMultifunctionalEnzymeEdges() → List[Tuple[FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.Enzyme]][source]

Get all edges annotated with an enzyme associated with more than one EC number.

Returns:List of all edge tuples where its enzyme is associated with more than one EC number.
Return type:List[Tuple[SubstanceID, SubstanceID, Enzyme]]
getMultifunctionalEnzymes() → Set[FEV_KEGG.Graph.Elements.Enzyme][source]

Get all enzymes which are associated with more than one EC number.

Returns:Set of enzymes associated with more than one EC number.
Return type:Set[Enzyme]
getUnidirectionalEnzymes() → Set[FEV_KEGG.Graph.Elements.Enzyme][source]

Get all enzymes which have only one direction.

Returns:Set of enzymes which take part in an edge with only one direction. Meaning there is no edge with the opposite direction between the same substances, annotated with the same enzyme.
Return type:Set[Enzyme]
keepEnzymesByEC(ecNumbers: Iterable[FEV_KEGG.Graph.Elements.EcNumber])[source]

Remove all enzymes from the graph, except the ones associated with the passed EC numbers.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:ecNumbers (Iterable[EcNumber]) –
removeAllEnzymesExcept(enzymesToKeep: Iterable[FEV_KEGG.Graph.Elements.Enzyme])[source]

Remove all enzymes which are not in enzymesToKeep.

Automatically updates indices. You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:enzymesToKeep (Iterable[Enzyme]) – Iterable of enzymes to keep in the graph. All other enzymes are removed.
removeEdge(node1: FEV_KEGG.Graph.Elements.Element, node2: FEV_KEGG.Graph.Elements.Element, key: FEV_KEGG.Graph.Elements.Element, bothDirections: bool = False)[source]

Automatically updates the indices. See FEV_KEGG.Graph.Models.DirectedMultiGraph for the original function.

removeEdges(edges: List[Tuple])[source]

Automatically updates the indices. See FEV_KEGG.Graph.Models.DirectedMultiGraph for the original function.

removeEdgesByElements(elements: Iterable[FEV_KEGG.Graph.Elements.Element])[source]

Automatically updates the indices. See FEV_KEGG.Graph.Models.DirectedMultiGraph for the original function.

removeEnzymeEdge(substrate: FEV_KEGG.Graph.Elements.SubstanceID, product: FEV_KEGG.Graph.Elements.SubstanceID, enzyme: FEV_KEGG.Graph.Elements.Enzyme, bothDirections: bool = False)[source]

Remove an enzyme between substrate and product.

Automatically updates indices. You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • substrate (SubstanceID) – Not removed from the graph.
  • product (SubstanceID) – Not removed from the graph.
  • enzyme (Enzyme) –
  • bothDirections (bool, optional) – If True, remove both directions, swapping substrate and product.
removeEnzymeEdges(enzymeEdges: List[Tuple[FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.Enzyme]])[source]

Remove all enzymes in certain edges.

Automatically updates indices.

Parameters:enzymeEdges (List[Tuple[SubstanceID, SubstanceID, Enzyme]]) – List of tuples, each describing an edge to be removed from the graph. If an edge to be removed does not exist, the next edge will be tried, without any error message.
removeEnzymes(enzymes: Iterable[FEV_KEGG.Graph.Elements.Enzyme])[source]

Remove all occurences of certain enzymes.

Automatically updates indices. You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:enzymes (Iterable[Enzyme]) – Iterable of enzymes to be completely removed from the graph.
removeEnzymesByEC(ecNumbers: Iterable[FEV_KEGG.Graph.Elements.EcNumber], keepInstead=False)[source]

Remove all enzymes associated with the passed EC numbers.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • ecNumbers (Iterable[EcNumber]) –
  • keepInstead (bool, optional) – If True, remove all enzymes except the ones associated with the passed EC numbers.
removeMultifunctionalEnzymes()[source]

Remove enzymes associated with more than one EC number.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

replaceEdgeElement(edge: Tuple[FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element, FEV_KEGG.Graph.Elements.Element], newElement: FEV_KEGG.Graph.Elements.Element, bothDirections: bool = False)[source]

Automatically updates the indices. See FEV_KEGG.Graph.Models.DirectedMultiGraph for the original function.

substanceCounts

Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.

class FEV_KEGG.Graph.SubstanceGraphs.SubstanceGeneGraph(underlyingRawGraph: implementationGraph = None)[source]

Bases: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGraph

Directed graph with SubstanceID nodes and GeneID edges, allowing multiple edges.

Links two FEV_KEGG.Graph.Elements.SubstanceID (compound or glycan) nodes with each FEV_KEGG.Graph.Elements.GeneID edge, associated with a FEV_KEGG.Graph.Elements.ReactionID they occur in.

Variables:
  • self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation.
  • self.name (str) – Custom name of the graph. This is often set, but not necessary in any calculations.
  • self.substanceCounts (Dict[SubstanceID, int], optional) – Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.
  • self.geneCounts (Dict[Elements.GeneID, int], optional) – Number of precursor graphs which contained certain GeneID edge keys still in this graph. None by default.
addGene(substrate: FEV_KEGG.Graph.Elements.SubstanceID, product: FEV_KEGG.Graph.Elements.SubstanceID, geneID: FEV_KEGG.Graph.Elements.GeneID, isReversible: bool = False)[source]

Add an geneID between the substances substrate and product.

Parameters:
  • substrate (SubstanceID) – Automatically added, if not already in the graph.
  • product (SubstanceID) – Automatically added, if not already in the graph.
  • geneID (GeneID) –
  • isReversible (bool, optional) – If True, add in both directions, swapping substrate and product.
static fromSubstanceReactionGraph(substanceReactionGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceReactionGraph)[source]

Create SubstanceGeneGraph from a SubstanceReactionGraph.

Replaces reactions with their associated genes. Splits reactions associated with several genes. Deduplicates reactions associated with the same gene. See the structure of a KEGG KGML pathway description file for further insight.

Parameters:substanceReactionGraph (SubstanceReactionGraph) – The substance-reaction graph to use for creating this graph. Apart from the graph structure itself, its attribute SubstanceReactionGraph.pathwaySet is needed!
Returns:A new substance-gene graph.
Return type:SubstanceGeneGraph
geneCounts

Number of precursor graphs which contained certain GeneID edge keys still in this graph. None by default.

getGenes() → Set[FEV_KEGG.Graph.Elements.GeneID][source]

Get all genes.

Returns:Set of all genes in this graph.
Return type:Set[GeneID]
getMultifunctionalGeneEdges() → List[Tuple[FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.GeneID]][source]

Get all edges annotated with a gene associated with more than one EC number.

Returns:List of all edge tuples where its gene, represented by a GeneID, is associated with more than one EC number.
Return type:List[Tuple[SubstanceID, SubstanceID, GeneID]]

Warning

Parses Database, this is slow and expensive!

getMultifunctionalGenes() → Set[FEV_KEGG.Graph.Elements.GeneID][source]

Get all genes which are associated with more than one EC number.

Returns:Set of genes associated with more than one EC number.
Return type:Set[GeneID]

Warning

Parses Database, this is slow and expensive!

getUnidirectionalGenes() → Set[FEV_KEGG.Graph.Elements.GeneID][source]

Get all genes which have only one direction.

Returns:Set of genes which take part in an edge with only one direction. Meaning there is no edge with the opposite direction between the same substances, annotated with the same gene.
Return type:Set[GeneID]
removeAllGenesExcept(genesToKeep: Iterable[FEV_KEGG.Graph.Elements.GeneID])[source]

Remove all genes which are not in genesToKeep.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:genesToKeep (Iterable[GeneID]) – Iterable of genes to keep in the graph. All other genes are removed.
removeGeneEdge(substrate: FEV_KEGG.Graph.Elements.SubstanceID, product: FEV_KEGG.Graph.Elements.SubstanceID, gene: FEV_KEGG.Graph.Elements.GeneID, bothDirections: bool = False)[source]

Remove a gene between substrate and product.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:
  • substrate (SubstanceID) – Not removed from the graph.
  • product (SubstanceID) – Not removed from the graph.
  • gene (GeneID) –
  • bothDirections (bool, optional) – If True, remove both directions, swapping substrate and product.
removeGeneEdges(geneEdges: List[Tuple[FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.SubstanceID, FEV_KEGG.Graph.Elements.GeneID]])[source]

Remove all genes in certain edges.

Parameters:geneEdges (List[Tuple[SubstanceID, SubstanceID, GeneID]]) – List of tuples, each describing an edge to be removed from the graph. If an edge to be removed does not exist, the next edge will be tried, without any error message.
removeGenes(geneIDs: Iterable[FEV_KEGG.Graph.Elements.GeneID])[source]

Remove all occurences of certain genes.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Parameters:geneIDs (Iterable[GeneID]) – Iterable of genes to be completely removed from the graph.
removeMultifunctionalGenes()[source]

Remove genes associated with more than one EC number.

You may want to removeIsolatedNodes() afterwards, to remove nodes that now have no edge.

Warning

Parses Database, this is slow and expensive!

substanceCounts

Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.

class FEV_KEGG.Graph.SubstanceGraphs.SubstanceGraph(underlyingRawGraph=None)[source]

Bases: FEV_KEGG.Graph.Models.DirectedMultiGraph

Directed graph with SubstanceID nodes.

Parameters:underlyingRawGraph (FEV_KEGG.Graph.Implementations) – If not None, copies underlyingRawGraph and stores it for this object.
Variables:self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation.
addSubstanceDescriptions()[source]

Downloads and adds description to .description and .name field of each substance node.

Warning

This causes many downloads and is very slow when nothing has been downloaded to cache yet!

See also

FEV_KEGG.KEGG.DataTypes.Substance()
The data type occuring in KEGG used to download the info.
class FEV_KEGG.Graph.SubstanceGraphs.SubstanceReactionGraph(underlyingRawGraph=None, pathwaySet=None)[source]

Bases: FEV_KEGG.Graph.SubstanceGraphs.SubstanceGraph

Directed graph with SubstanceID nodes and ReactionID edges, allowing multiple edges.

Links two FEV_KEGG.Graph.Elements.SubstanceID (compound or glycan) nodes with each FEV_KEGG.Graph.Elements.ReactionID edge they occur in. Substances have to occur on different sides of the reaction, one being a substrate, the other being a product. Reversible reactions will get two edges with swapped roles of substrate/product. There may be other substrates/products in the same reaction, they will be linked with another edge.

For example A1 + A2 -> B1 + B2 will yield four edges: (A1, B1); (A1, B2); (A2, B1); (A2, B2). Making this reaction reversible would yield eight edges, because each tuple will be swapped to form the other direction.

Parameters:
Variables:
  • self.underlyingRawGraph (FEV_KEGG.Graph.Implementations) – The actual graph containing the data. This is dependant on the implementation.
  • self.name (str) – Custom name of the graph. This is often set, but not necessary in any calculations.
  • self.pathwaySet (Set[KGML_pathway.Pathway]) – Set of pathways this graph was derived from. Especially useful for e.g. Conversion.SubstanceReactionGraph2SubstanceGeneGraph().
  • self.substanceCounts (Dict[SubstanceID, int], optional) – Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.
  • self.reactionCounts (Dict[Elements.ReactionID, int], optional) – Number of precursor graphs which contained certain ReactionID edge keys still in this graph. None by default.
addReaction(substrate: FEV_KEGG.Graph.Elements.SubstanceID, product: FEV_KEGG.Graph.Elements.SubstanceID, reaction: FEV_KEGG.Graph.Elements.ReactionID, isReversible: bool = False)[source]

Add a reaction edge between substrate and product.

Parameters:
  • substrate (SubstanceID) – Substance from which the reaction edge starts. Automatically added, if not already in the graph.
  • product (SubstanceID) – Substance where the reaction edge ends. Automatically added, if not already in the graph.
  • reaction (Elements.ReactionID) – Reaction with which the new edge is to be annotated, as its edge key.
  • isReversible (bool, optional) – If True, add reaction in both directions.
copy(underlyingRawGraph=None)[source]

Shallow copy of the whole graph.

However, some attributes are explicitly copied (although each attribute might in itself be shallowly copied):

  • .underlyingRawGraph
  • .name
  • .nodeCounts
  • .edgeCounts
  • .edgeElementCounts
  • .pathwaySet
Parameters:underlyingRawGraph (FEV_KEGG.Graph.Implementations, optional) – If given, does not copy the underlying raw graph, but uses this one.
Returns:Shallow copy of the whole graph.
Return type:SubstanceReactionGraph
static fromPathway(pathway: Set[FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway])[source]

Create SubstanceReactionGraph from certain pathways.

Parameters:pathway (Set[KGML_pathway.Pathway] or KGML_pathway.Pathway) – Pathway(s) to use for creating the graph.
Returns:A new substance-reaction graph.
Return type:SubstanceReactionGraph
getReactions() → Set[FEV_KEGG.Graph.Elements.ReactionID][source]

Get all reactions.

Returns:Set of all reaction edge keys in this graph.
Return type:Set[Elements.ReactionID]
getUnidirectionalReactions() → Set[FEV_KEGG.Graph.Elements.ReactionID][source]

Get the reactions of all edges which are unidirectional only.

Returns:Set of all reactions which are edge keys of edges that have only one direction, i.e. there is no other edge in reverse direction with the same reaction edge key.
Return type:Set[Elements.ReactionID]
reactionCounts

Number of precursor graphs which contained certain ReactionID edge keys still in this graph. None by default.

substanceCounts

Number of precursor graphs which contained certain SubstanceID nodes still in this graph. None by default.

Module contents

FEV_KEGG.KEGG package

Submodules
FEV_KEGG.KEGG.DataTypes module
class FEV_KEGG.KEGG.DataTypes.EcEnzyme(content)[source]

Bases: object

An enzyme found in KEGG pathways, defined by its EC number.

Variables:
  • self.uniqueID (str) – Unique string identifying the EC number, e.g. ‘4.1.2.48’.
  • self.description (str) – Human-readable description of the EC number, e.g. ‘low-specificity L-threonine aldolase;LtaE’.
  • self.name (str) – Short human-readable name of the EC number, e.g. ‘LtaE’. The shortest of all words in self.description.
class FEV_KEGG.KEGG.DataTypes.Gene(content)[source]

Bases: object

Gene as defined by a gene description file in KEGG GENE database.

All attributes might be None, depending on whether they actually occur in the gene description! Occurence varies between organisms and sources.

Parameters:

content (str) – A multi-line gene description.
Variables:
  • self.number (str) – The name of the gene, e.g. ‘Acav_0021’.
  • self.symbol (str) – Colloquial name of the gene product, e.g. ‘ThrC’.
  • self.name (str) – Long name of the gene, e.g. ‘(GenBank) Homoserine dehydrogenase’.
  • self.isProtein (bool) –
  • self.ecNumbers (List[str]) –
  • self.isEnzyme (bool) – If isProtein and has EC numbers.
  • self.keggOrthologyNames (List[str]) – Names for each KEGG Orthology ID associated with this gene, e.g. ‘homoserine dehydrogenase’.
  • self.keggOrthologyIDs (List[str]) – Each KEGG Orthology ID assocaited with this gene, e.g. ‘K00003’.
  • self.keggOrthologies (List[Tuple[str, str, List[str]]]) – List of each associated KEGG Orthology entry, represented as a tuple of (ID, name, EC numbers), e.g. (‘K00003’, ‘homoserine dehydrogenase’, [‘1.1.1.3’]).
  • self.organismAbbreviation (str) –
  • self.organismName (str) –
  • self.organismTnumber (str) – KEGG Onthology ID of the organism this gene belongs to, e.g. ‘T01445’.
  • self.pathways (List[Tuple[str, str]]) – List of organism-specific pathways this gene occurs in, represented as a tuple of (ID, name), e.g. (‘aaa00260’, ‘Glycine, serine and threonine metabolism’).
  • self.positionFrom (int) – Nucleotide sequence position this gene starts at.
  • self.positionTo (int) – Nucleotide sequence positon this gene ends at.
  • self.positionIsComplement (bool) – Whether the positions are on the complement strand.
  • self.aaseqLength (int) –
  • self.aaseq (str) –
  • self.ntseqLength (int) –
  • self.ntseq (str) –
getGeneID() → GeneID[source]
class FEV_KEGG.KEGG.DataTypes.Substance(content)[source]

Bases: object

A compound/glycan found in KEGG pathways.

Depending on whether this is a compound or a glycan, there are more attributes than listed below.

Variables:
  • self.uniqueID (str) – Unique string identifying a substance, e.g. ‘C00084’.
  • self.description (str) – Human-readable description of a substance, e.g. ‘Acetaldehyde;Ethanal’.
  • self.name (str) – Short human-readable description of a substance, e.g. ‘Acetaldehyde’. The shortest of all words in self.description.
FEV_KEGG.KEGG.Database module
exception FEV_KEGG.KEGG.Database.GeneDoesNotExistError[source]

Bases: ValueError

Raised if trying to download a certain gene that does not exist.

exception FEV_KEGG.KEGG.Database.ImpossiblyOrthologousError[source]

Bases: ValueError

Raised if trying to find orthologs in an organism using a GeneID from the very same organism.

exception FEV_KEGG.KEGG.Database.NoKnownPathwaysError[source]

Bases: ValueError

Raised if an organism has no known pathways and is therefore rather useless.

FEV_KEGG.KEGG.Database._filterHomologsBySignificanceBulk(matchings: Dict[FEV_KEGG.Graph.Elements.GeneID, FEV_KEGG.KEGG.SSDB.Matching], eValue, onlyGeneID=False)[source]

Filter sequence alignments by statistical significance.

Parameters:
  • matchings (Dict[GeneID, SSDB.Matching]) – Dictionary of a homolog matching, including homologous gene IDs and statistical data, keyed by the gene ID used to search for homologs.
  • eValue (float) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • onlyGeneID (bool, optional) – If True, return only the set of homologous gene IDs, not the whole matching including statistical data.
Returns:

matchings reduced to the significant sequence alignments, with an E-value below eValue. If onlyGeneID == True, matchings is further reduced to only contain the homologous gene IDs, not the complete matching.
Return type:

Dict[GeneID, SSDB.Matching] or Dict[GeneID, Set[GeneID]]
FEV_KEGG.KEGG.Database.doesOrganismExist(organismAbbreviation: eco) → bool[source]

Check whether an organism exists.

Parameters:organismAbbreviation (str) – The abbreviation of the organism to check.
Returns:True, if something was downloaded, and thus the organism exists. False, if the download was empty (400 Bad Request), because this organism does not exist.
Return type:bool
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.doesOrganismExistBulk(organismAbbreviations: List[str]) → List[str][source]

Check whether multiple organisms exist.

This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads.

Parameters:organismAbbreviations (List[str]) – The abbreviations of the organisms to check.
Returns:List of organism abbreviations, taken from organismAbbreviations for which doesOrganismExist() would return True.
Return type:List[str]
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getEcEnzymeBulk(ecNumbers: Iterable[FEV_KEGG.Graph.Elements.EcNumber]) → Dict[str, FEV_KEGG.KEGG.DataTypes.EcEnzyme][source]

Get multiple enzyme descriptions, defined by its EC number.

Downloads the data from KEGG in bulk, if not already present on disk. This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads.

Parameters:

ecNumbers (Iterable[EcNumber]) – Enzymes to be downloaded.
Returns:

Each found enzyme, keyed by the unique ID of the EC number used to search it.
Return type:

Dict[str, EcEnzyme]
Raises:
  • IOError – If result is too small. Possibly because none of the genes of a download-chunk existed.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getEnzymeEcNumbers(enzymeAbbreviation: MiaB) → List[str][source]

Get EC numbers of an enzyme for the enzyme’s abbreviation.

Also works for everything else in the description of an enzyme, not just the abbreviation.

Parameters:enzymeAbbreviation (str) – Part of the enzymes description string.
Returns:All EC numbers, as strings, for a given enzyme, identified by its abbreviation, from KEGG. Or None if no EC numbers could be found.
Return type:List[str] or None
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getGene(geneIdString: eco:b0004) → FEV_KEGG.KEGG.DataTypes.Gene[source]

Get certain gene.

Downloads the data from KEGG, if not already present on disk.

Parameters:

geneIdString (str) – Unique ID of the gene to be downloaded, represented as a string, including organism abbreviation and gene name, e.g. ‘eco:b0004’.
Returns:

Gene object.
Return type:

Gene
Raises:
  • HTTPError – If gene does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getGeneBulk(geneIDs: Iterable[FEV_KEGG.Graph.Elements.GeneID]) → Dict[FEV_KEGG.Graph.Elements.GeneID, FEV_KEGG.KEGG.DataTypes.Gene][source]

Get multiple certain genes.

Downloads the data from KEGG in bulk, if not already present on disk. This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads.

Parameters:

geneIDs (Iterable[GeneID]) – Unique IDs of the genes to be downloaded, represented as FEV_KEGG.Graph.Elements.GeneID objects.
Returns:

Each found Gene object, keyed by the GeneID used to search it.
Return type:

Dict[GeneID, Gene]
Raises:
  • IOError – If result is too small. Possibly because none of the genes of a download-chunk existed.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getOrganismInfo(organismAbbreviation: eco, checkExpiration=False) → str[source]

Get organism info.

Parameters:
  • organismAbbreviation (str) – The abbreviation of the organism.
  • checkExpiration (bool, optional) – If True, check whether the last download of the organism info is older than FEV_KEGG.settings.organismInfoExpiration. If yes, download it again. This can be useful when relying upon a current database size for calculating E-values for a FEV_KEGG.KEGG.SSDB.Match.
Returns:

Raw organism info.
Return type:

str
Raises:
  • ValueError – If organism with organismAbbreviation does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getOrganismList() → List[str][source]

Get list of all organisms known to KEGG.

Returns:

All organism descriptions known to KEGG.
Return type:

List[str]
Raises:
  • URLError – If connection to KEGG fails.
  • Returns the list of all known organisms from KEGG.
FEV_KEGG.KEGG.Database.getOrthologOverviewsBulk(geneIDs: Iterable[FEV_KEGG.Graph.Elements.GeneID]) → Dict[FEV_KEGG.Graph.Elements.GeneID, FEV_KEGG.KEGG.SSDB.MatchingOverview][source]

Get best orthologous matches for genes in all organisms in bulk.

This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads. If orthologs exist in a certain organism, you can use getOrthologsBulk() in a seconds step, to get all orthologs in that organism, not only the best match. Filtering the amount of possibly orthologous organisms with this function before using the aforementioned function is much faster in total. But, using this function with only a single organism in mind is not.

Parameters:

geneIDs (Iterable[GeneID]) – Genes to use for searching orthologs.
Returns:

A dictionary of a matching overview, containing the best FEV_KEGG.KEGG.SSDB.Match for each possibly orthologous organism, using each gene ID from geneIDs, searching the genome of all organisms, keyed by the used gene ID. Matching overviews are downloaded from KEGG SSDB.
Return type:

Dict[GeneID, MatchingOverview]
Raises:
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getOrthologs(geneID: FEV_KEGG.Graph.Elements.GeneID, comparisonOrganism: Organism or str, eValue: float = 1e-15) → FEV_KEGG.KEGG.SSDB.Matching[source]

Get orthologs for a gene in a certain organism, including metadata.

Parameters:
  • geneID (GeneID) – Gene to use for searching orthologs.
  • comparisonOrganism (Organism or str) – Organism to check for orthologs. May be an Organism object or an organism abbreviation string.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

A matching of orthologs for gene geneID, searching the genome of comparisonOrganism. Only matches with an E-value smaller or equal to eValue are returned. Matches are downloaded from KEGG SSDB.
Return type:

SSDB.Matching
Raises:
  • ImpossiblyOrthologousError – If geneID is from comparisonOrganism.
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getOrthologsBulk(geneIDs: Iterable[FEV_KEGG.Graph.Elements.GeneID], comparisonOrganism: Iterable[Organism] or Iterable[str] or Organism or str, eValue: float = 1e-15, ignoreImpossiblyOrthologous=False) → Dict[FEV_KEGG.Graph.Elements.GeneID, List[FEV_KEGG.KEGG.SSDB.Matching]][source]

Get orthologs for genes in a certain organism in bulk, including metadata.

This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads.

Parameters:
  • geneIDs (Iterable[GeneID]) – Genes to use for searching orthologs.
  • comparisonOrganism (Iterable[Organism] or Iterable[str] or Organism or str) – Organism(s) to check for orthologs. May be an organism abbreviation string.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
  • ignoreImpossiblyOrthologous (bool, optional) – If True, ignore if a searched gene is from any comparisonOrganism. Simply do not search for this particular gene in its own organism, but in all others from comparisonOrganism.
Returns:

A dictionary of a list of matchings of orthologous genes, using each gene ID from geneIDs, searching the genome of each comparisonOrganism, keyed by the used gene ID. Only matches with an E-value smaller or equal to eValue are returned. Matches are downloaded from KEGG SSDB.
Return type:

Dict[GeneID, List[SSDB.Matching]]
Raises:
  • ImpossiblyOrthologousError – If any gene ID in geneIDs is from comparisonOrganism. Unless ignoreImpossiblyOrthologous == True.
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getOrthologsOnlyGeneID(geneID: FEV_KEGG.Graph.Elements.GeneID, comparisonOrganism: Organism or str, eValue: float = 1e-15) → Set[FEV_KEGG.Graph.Elements.GeneID][source]

Get orthologs for a gene in a certain organism, without metadata.

Parameters:
  • geneID (GeneID) – Gene to use for searching orthologs.
  • comparisonOrganism (Organism or str) – Organism to check for orthologs. May be an Organism object or an organism abbreviation string.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

Set of orthologous genes, using geneID to search the genome of comparisonOrganism. Only matches with an E-value smaller or equal to eValue are returned. Matches are downloaded from KEGG SSDB.
Return type:

Set[GeneID]
Raises:
  • ImpossiblyOrthologousError – If geneID is from comparisonOrganism.
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getParalogs(geneID: FEV_KEGG.Graph.Elements.GeneID, eValue: float = 1e-15) → FEV_KEGG.KEGG.SSDB.Matching[source]

Get paralogs for a gene, including metadata.

Parameters:
  • geneID (GeneID) – Gene to use for searching paralogs.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

A matching of paralogous genes, using geneID to search the genome of the same organism. Only matches with an E-value smaller or equal to eValue are returned. Matches are downloaded from KEGG SSDB.
Return type:

SSDB.Matching
Raises:
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getParalogsBulk(geneIDs: Iterable[FEV_KEGG.Graph.Elements.GeneID], eValue: float = 1e-15) → Dict[FEV_KEGG.Graph.Elements.GeneID, FEV_KEGG.KEGG.SSDB.Matching][source]

Get paralogs for genes in bulk, including metadata.

This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads.

Parameters:
  • geneIDs (Iterable[GeneID]) – Genes to use for searching paralogs.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

A dictionary of matchings of paralogous genes, using each gene ID from geneIDs to search the genome of the same organism, keyed by the used gene ID. Only matches with an E-value smaller or equal to eValue are returned. Matches are downloaded from KEGG SSDB.
Return type:

Dict[GeneID, SSDB.Matching]
Raises:
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getParalogsOnlyGeneID(geneID: FEV_KEGG.Graph.Elements.GeneID, eValue: float = 1e-15) → Set[FEV_KEGG.Graph.Elements.GeneID][source]

Get paralogs for a gene, without metadata.

Parameters:
  • geneID (GeneID) – Gene to use for searching paralogs.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

Set of paralogous genes, using geneID to search the genome of the same organism. Only matches with an E-value smaller or equal to eValue are returned. Matches are downloaded from KEGG SSDB.
Return type:

Set[GeneID]
Raises:
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getPathway(organismAbbreviation: eco, pathwayName: 00260) → FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway[source]

Get certain pathway object of an organism.

Downloads the data from KEGG, if not already present on disk.

Parameters:
  • organismAbbreviation (str) – The organism for which to retrieve the pathway.
  • pathwayName (str) – The code of the pathway, e.g. ‘00260’.
Returns:

Pathway object. None if pathway does not exist.
Return type:

KGML_pathway.Pathway
Raises:

URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getPathwayBulk(organismAbbreviation: eco, pathwayNames: Iterable[str]) → Dict[str, FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway][source]

Get multiple pathway objects of an organism.

Downloads the data from KEGG in bulk, if not already present on disk. This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads.

Parameters:
  • organismAbbreviation (str) – The organism for which to retrieve the pathway.
  • pathwayNames (Iterable[str]) – The codes of the pathways, e.g. [‘00260’, ‘00530’].
Returns:

Pathway objects, keyed by their respective pathway name. A pathway object is None if the pathway does not exist.
Return type:

Dict[str, KGML_pathway.Pathway]
Raises:

URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getPathwayDescriptions(organismAbbreviation: eco) → Set[str][source]

Get full pathway descriptions for an organism.

Downloads the data from KEGG, if not already present on disk.

Parameters:

organismAbbreviation (str) – The organism for which to retrieve all known pathways.
Returns:

Set of pathway description lines for given organism.
Return type:

Set[str]
Raises:
  • NoKnownPathwaysError – If the organism has no known pathways.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getPathwayGeneIDs(organismAbbreviation: eco, pathwayName: 00260) → Set[str][source]

Get all gene ID strings in an organism’s pathway, if previously saved.

Parameters:
  • organismAbbreviation (str) – The organism for which to retrieve the pathway.
  • pathwayName (str) – The code of the pathway, e.g. ‘00260’.
Returns:

Gene ID strings from a pathway, or None, if not previously saved on disk.
Return type:

Set[str]

Note

This requires you to previously call setPathwayGeneIDs()!

FEV_KEGG.KEGG.Database.getSubstanceBulk(substances: Iterable[FEV_KEGG.Graph.Elements.SubstanceID]) → Dict[str, FEV_KEGG.KEGG.DataTypes.Substance][source]

Get multiple substance descriptions.

Downloads the data from KEGG in bulk, if not already present on disk. This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads.

Parameters:

substances (Iterable[SubstanceID]) – Substances to be downloaded.
Returns:

Each found substance, keyed by the unique ID of the substance used to search it.
Return type:

Dict[str, Substance]
Raises:
  • IOError – If result is too small. Possibly because none of the genes of a download-chunk existed.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getTaxonomyKEGG() → List[str][source]

Get KEGG taxonomy from KEGG BRITE.

Returns:Taxonomy of organisms in KEGG, in special text format, following KEGG’s own scheme, line by line.
Return type:List[str]
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.getTaxonomyNCBI() → List[str][source]

Get NCBI taxonomy from KEGG BRITE.

Returns:Taxonomy of organisms in KEGG, in special text format, following the NCBI scheme, line by line.
Return type:List[str]
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.hasOrthologsBulk(geneIDs: Iterable[FEV_KEGG.Graph.Elements.GeneID], comparisonOrganisms: Iterable[Organism] or Iterable[str], eValue: float = 1e-15) → Dict[FEV_KEGG.Graph.Elements.GeneID, List[str]][source]

Find out whether orthologs for genes exist in certain organisms in bulk.

This is done in parallel in a thread pool, see FEV_KEGG.settings.downloadThreads. If orthologs exist in a certain organism, you can use getOrthologsBulk() in a seconds step, to get all orthologs in that organism. Filtering the amount of possibly orthologous organisms with this function before using the aforementioned function is much faster in total. But, using this function with only a single comparisonOrganisms is not. If you want to find only the best matches in every organism, use getOrthologOverviewsBulk() instead.

Parameters:
  • geneIDs (Iterable[GeneID]) – Genes to use for searching orthologs.
  • comparisonOrganisms (Iterable[Organism] or Iterable[str]) – Organisms to check for orthologs. May be an organism abbreviation string.
  • eValue (float, optional) – Statistical expectation value (E-value), below which a sequence alignment is considered significant.
Returns:

A dictionary of a list of organisms which have at least one orthologous gene, using each gene ID from geneIDs, searching the genome of each comparisonOrganisms, keyed by the used gene ID. Only organisms with matches with an E-value smaller or equal to eValue are returned. Matching overviews are downloaded from KEGG SSDB.
Return type:

Dict[GeneID, List[str]]
Raises:
  • ValueError – If any organism does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Database.setPathwayGeneIDs(organismAbbreviation: eco, pathwayName: 00260, geneIDs: Set[str])[source]

Save all gene ID strings in an organism’s pathway.

Parameters:
  • organismAbbreviation (str) – The organism for which to retrieve the pathway.
  • pathwayName (str) – The code of the pathway, e.g. ‘00260’.
  • geneIDs (Set[str]) – Gene ID strings of the specified organism-specific pathway.
FEV_KEGG.KEGG.Download module
FEV_KEGG.KEGG.Download.downloadEcEnzyme(ecNumberID)[source]

Download an enzyme description file from KEGG, defined by its EC number.

Parameters:ecNumber (str) – The EC number string of the enzyme to download, e.g. ‘4.1.2.48’.
Returns:Content of the EcEnzymes’s description.
Return type:str
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadEnzymeEcNumbers(enzymeAbbreviation) → str[source]

Download the list of all EC numbers for a given enzyme, identified by its abbreviation, from KEGG.

Also works for everything else in the description of an enzyme, not just the abbreviation. Tries several times before giving up, see FEV_KEGG.settings.retryDownloadBackoffFactor.

Parameters:enzymeAbbreviation (str) – Common abbreviation of the desired enzyme, as it appears in its description, e.g. ‘MiA’. Also works for everything else in the description of an enzyme, not just the abbreviation.
Returns:EC numbers, delimited by ‘\n’.
Return type:str
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadGene(geneID: eco:b0004) → str[source]

Downloads gene description for a given gene ID (includes organism) from KEGG.

Tries several times before giving up, see FEV_KEGG.settings.retryDownloadBackoffFactor.

Parameters:

geneID (str) – ID of the gene, including organism abbreviation, e.g. ‘eco:b0004’.
Returns:

Gene in KEGG GENE format.
Return type:

str
Raises:
  • HTTPError – If gene does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadGeneBulk(geneIDs: [eco:b0004, eco:b0015,...]) → str[source]

Downloads gene descriptions for a given list of gene IDs (includes organism) from KEGG

Tries several times before giving up, see FEV_KEGG.settings.retryDownloadBackoffFactor.

Parameters:

geneIDs (Iterable) – IDs of the genes, including organism abbreviation, e.g. ‘[eco:b0004, eco:b0015,…]’.
Returns:

Genes in KEGG GENE format, delimited by a line of ‘///’. You will have to split them! Order is arbitrary.
Return type:

str
Raises:
  • IOError – If result is too small. Possibly because none of the genes exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadOrganismInfo(organismAbbreviation) → str[source]

Downloads the info file of an organism.

Parameters:organismAbbreviation (str) – Abbreviation of the organism to check, e.g. ‘eco’.
Returns:Raw organism info. None, if download was empty (400 Bad Request), because this organism does not exist.
Return type:str
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadOrganismList() → str[source]

Download the list of all organisms known to KEGG.

Tries several times before giving up, see FEV_KEGG.settings.retryDownloadBackoffFactor.

Returns:List of organism descriptions known to KEGG, delimited by ‘\n’.
Return type:str
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadOrthologOverview(geneID: GeneID) → Tuple[int, List[FEV_KEGG.KEGG.SSDB.Match]][source]

Download overview of orthologs of gene geneID found in any organism.

Parameters:geneID (GeneID) – GeneID object of the gene to be compared against, i.e. against its amino acid sequence.
Returns:List of Matches, containing gene IDs of orthologs, and other data necessary for sequence matching. Will be empty, if nothing is found.
Return type:List[SSDB.Match]
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadOrthologs(geneID: GeneID, comparisonOrganismString: eco) → Tuple[int, List[FEV_KEGG.KEGG.SSDB.PreMatch]][source]

Download orthologs of gene geneID found in organism comparisonOrganismString.

Parameters:
  • geneID (GeneID) – GeneID object of the gene to be compared against, i.e. against its amino acid sequence.
  • comparisonOrganismString (str) – Abbreviation of the organism to search for orthologs of geneID.
Returns:

List of Pre-Matches, containing gene IDs of orthologs, and other data necessary for sequence matching. Will be empty, if nothing is found.
Return type:

List[SSDB.PreMatch]
Raises:

URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadParalogs(geneID: GeneID) → Tuple[int, List[FEV_KEGG.KEGG.SSDB.PreMatch]][source]

Download paralogs of gene geneID.

Parameters:geneID (GeneID) – GeneID object of the gene to be compared against, i.e. against its amino acid sequence.
Returns:List of Pre-Matches, containing gene IDs of paralogs, and other data necessary for sequence matching. Will be empty, if nothing is found.
Return type:List[SSDB.PreMatch]
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadPathway(organismString: eco, pathwayName: 00260) → str[source]

Downloads pathway as KGML for a given organism from KEGG.

Tries several times before giving up, see FEV_KEGG.settings.retryDownloadBackoffFactor.

Parameters:
  • organismString (str) – Abbreviation of the organism, e.g. ‘eco’.
  • pathwayName (str) – Name of the pathway, e.g. ‘00260’. Will be automatically concatenated with organismString to form the pathway ID, e.g. ‘eco:00260’.
Returns:

Pathway in KGML format.
Return type:

str
Raises:
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadPathwayList(organismString: eco) → str[source]

Downloads list of all pathways for a given organism from KEGG.

Tries several times before giving up, see FEV_KEGG.settings.retryDownloadBackoffFactor.

Parameters:

organismString (str) – Abbreviation of the organism, e.g. ‘eco’.
Returns:

List of pathways, delimited by ‘\n’.
Return type:

str
Raises:
  • HTTPError – If pathway list does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadSubstance(substanceID)[source]

Download a substance description file from KEGG, compound or glycan.

Parameters:substanceID (str) – The ID string of the substance to download, e.g. ‘C00084’.
Returns:Content of the substance’s description.
Return type:str
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadTaxonomyKEGG()[source]

Download KEGG taxonomy from KEGG BRITE.

Returns:KEGG taxonomy in special text format.
Return type:str
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.downloadTaxonomyNCBI() → str[source]

Download NCBI taxonomy from KEGG BRITE.

Returns:NCBI taxonomy in special text format.
Return type:str
Raises:URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.Download.is_not_404(exception)[source]

Checks if exception is not an HTTP 404 error.

This is useful, because for most types of downloads 404 means ‘does not exist’ and is in itself a valid reply. Therefore, retrying a download because it raised a 404 error is usually unnecessary.

Parameters:exception (Exception) – Any error class instance. Must be of class urllib.error.HTTPError to be recognised as a 404 error.
Returns:False, if exception is an HTTP 404 error. True, if it is anythign else.
Return type:bool
FEV_KEGG.KEGG.File module
class FEV_KEGG.KEGG.File.CacheEntry(isCached: bool, absolutePath: str, result=None)[source]

Bases: object

Abstract entry of the cache.

While cache() returns the content of a cache entry directly, cacheEntry() returns an instance of this class. This allows for delayed disk access, because results are always computed within cache() or cacheEntry(), but using this class, the actual reading/writing of the cache file is only started upon executing getResult().

Parameters:
  • isCached (bool) – True if the underlying cache file already exists and, thus, will be read, not written.
  • absolutePath (str) – The absolute path of the underlying cache file.
  • result (Object, optional) – Contains the result of the computation to be written into the underlying cache file. Obviously only necessary if isCached == False.

Note

This is especially useful when calculating results within a process pool, to utilise parallelism, but writing results within a thread pool in the main process, keeping the process pool from idling, while waiting for the disk. All this is necessary, because neither ProcessPoolExecutor nor ThreadPoolExecutor support pre-emptive scheduling. The caveat of this approach is that the result of the computation, which might be several megabytes, has to be transferred between the background process and the main process via IPC, which is relatively slow. Still, on my laptop, this approach proved to be significantly faster overall.

getResult(noDiskIO=False)[source]

Result of the cached computation.

Automatically performs read or write operation in this thread, depending on whether the computation was already cached or has only been computed just now.

Parameters:noDiskIO (bool, optional) – If True, the result currently available in memory is returned, without any disk access. If the computation was already cached, i.e. an underlying cache file exists, this is most likely None! Only use if you know exactly what you are doing!
Returns:Result of the cached computation, no matter if it came from a cache file or from a fresh computation.
Return type:Object
Raises:OSError – File could not be opened. Only relevant if noDiskIO == False.
FEV_KEGG.KEGG.File.atomic_write(filename, text=True, keep=False, suffix='.bak', prefix='tmp')[source]

Context manager for overwriting a file atomically.

Usage:

with atomic_write("myfile.txt") as f:
    f.write("data")

The context manager opens a temporary file for writing in the same directory as filename. On cleanly exiting the with-block, the temp file is renamed to the given filename. If the original file already exists, it will be overwritten and any existing contents replaced. (On POSIX systems, the rename is atomic. Other operating systems may not support atomic renames, in which case the function name is misleading.)

If an uncaught exception occurs inside the with-block, the original file is left untouched. By default the temporary file is not preserved. To keep the temp file, pass keep=True. Any errors in deleting the temp file are ignored. By default, the temp file is opened in text mode. To use binary mode, pass text=False as an argument. On some operating systems, this make no difference.

By default, the temp file will have a name starting with “tmp” and ending with “.bak”. You can vary that by passing strings as the suffix and prefix arguments.

Note

Copyright (c) 2017 ActiveState Software Inc.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

FEV_KEGG.KEGG.File.cache(folder_path, file_name)[source]

Decorator for caching files on disk.

Checks if result of wrapped function has already been cached into the file specified by FEV_KEGG.settings.cachePath/folder_path/file_name. If yes, read file and return content. If no, execute wrapped function, write result to file, and then return result.

Parameters:
  • folder_path (str) – Path of the file, in a format your OS understands. Something like ‘subfolder/another_folder/’ should most likely work. Remember, this is relative to your FEV_KEGG.settings.cachePath!
  • file_name (str) – Name of the file itself.
Returns:

A decorator to automatically cache the decorated function’s return value into the file specified by folder_path/file_name.
Return type:

decorator
Raises:
  • Error – If the decorated function raises any error. Only relevant if the decorated function is executed at all, which it only is if the result has not already been cached.
  • OSError – File could not be opened.
FEV_KEGG.KEGG.File.cacheEntry(folder_path, file_name)[source]

Decorator for caching files on disk, but returning only an intermediate CacheEntry.

Similar to cache decorator, but does not read content from file nor write result to file. Checks if result of wrapped function has already been cached into the file specified by FEV_KEGG.settings.cachePath/folder_path/file_name. If yes, return appropriate CacheEntry. This object provides all information and methods necessary to read/write the desired data from cache. If no, execute wrapped function, and then return appropriate CacheEntry.

Parameters:
  • folder_path (str) – Path of the file, in a format your OS understands. Something like ‘subfolder/another_folder/’ should most likely work. Remember, this is relative to your FEV_KEGG.settings.cachePath!
  • file_name (str) – Name of the file itself.
Returns:

A decorator to automatically return the delayed disk access in a CacheEntry instance.
Return type:

decorator
Raises:
  • Error – If the decorated function raises any error. Only relevant if the decorated function is executed at all, which it only is if the result has not already been cached.
  • OSError – File could not be opened.

Note

This is especially handy when splitting computation (in this function) from disk I/O (in CacheEntry) in a parallel computation environment.

FEV_KEGG.KEGG.File.createPath(fileName)[source]

Extracts the path from fileName and ensures all folders exist.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath.

Parameters:fileName (str) – Path and file name in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
FEV_KEGG.KEGG.File.doesFileExist(fileName) → bool[source]

Does fileName already exist AND is a file?

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath.

Parameters:fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
Returns:Whether the file already exists.
Return type:bool
FEV_KEGG.KEGG.File.doesFolderExist(folderName) → bool[source]

Does fileName already exist AND is a folder?

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath.

Parameters:fileName (str) – Path and name of the folder, in a format your OS understands. Something like ‘subfolder/another_folder’ should most likely work.
Returns:Whether the folder already exists.
Return type:bool
FEV_KEGG.KEGG.File.getFileHandleRead(fileName) → io.IOBase[source]

A low-level read-only handle to a text file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath.

Parameters:

fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
Returns:

A handle to the open file. Be sure to close it eventually!
Return type:

IOBase
Raises:
  • ValueError – Decoding from UTF-8 failed.
  • OSError – File could not be opened.

Warning

Make sure your code will close this handle eventually! Else, you will waste a lot of resources and eventually prevent your code from opening any other resources!

FEV_KEGG.KEGG.File.getFileHandleWrite(fileName) → io.IOBase[source]

A low-level read-write handle to a text file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. File will be overwritten completely, if already present.

Parameters:

fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
Returns:

A handle to the open file. Be sure to close it eventually!
Return type:

IOBase
Raises:
  • ValueError – Decoding from UTF-8 failed.
  • OSError – File could not be opened.

Warning

Make sure your code will close this handle eventually! Else, you will waste a lot of resources and eventually prevent your code from opening any other resources!

FEV_KEGG.KEGG.File.readBytesFromFileAtOnce(fileName) → bytes[source]

Reads from a binary file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. Reads the file fully at once (more memory intensive).

Parameters:
  • data (bytes or bytearray) – Content of the file. Will not be encoded.
  • fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
  • atomic (bool, optional) – If True, write file atomically.
Returns:

Content of the file. Not decoded.
Return type:

bytes
Raises:

OSError – File could not be opened.
FEV_KEGG.KEGG.File.readGeneratorFromFileLinewise(fileName) → Generator[str, None, None][source]

Reads string-generator from a text file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. Returns a generator (can only be read once!) for reading a file line by line (less memory intensive). Does NOT return the newline characters.

Parameters:

fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
Yields:

str – Line of content of the file. Will be decoded from UTF-8.
Raises:
  • ValueError – Decoding from UTF-8 failed.
  • OSError – File could not be opened.
FEV_KEGG.KEGG.File.readListFromFileAtOnce(fileName) → List[str][source]

Reads list from a text file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. Reads the file fully at once (more memory intensive). Does NOT return the newline characters.

Parameters:

fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
Returns:

Content of the file as a list. Will be decoded from UTF-8.
Return type:

List[str]
Raises:
  • ValueError – Decoding from UTF-8 failed.
  • OSError – File could not be opened.
FEV_KEGG.KEGG.File.readSetFromFileAtOnce(fileName) → Set[str][source]

Reads set from a text file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. Reads the file fully at once (more memory intensive). Does NOT return the newline characters.

Parameters:

fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
Returns:

Content of the file as a set. Will be decoded from UTF-8.
Return type:

Set[str]
Raises:
  • ValueError – Decoding from UTF-8 failed.
  • OSError – File could not be opened.
FEV_KEGG.KEGG.File.readStringFromFileAtOnce(fileName) → str[source]

Reads from a text file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. Reads the file fully at once (more memory intensive).

Parameters:

fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
Returns:

Content of the file. Will be decoded from UTF-8.
Return type:

str
Raises:
  • ValueError – Decoding from UTF-8 failed.
  • OSError – File could not be opened.
FEV_KEGG.KEGG.File.writeToFile(content: will be encoded in UTF-8, fileName: will be overwritten, if already present, atomic=True)[source]

Writes content to a text file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. File will be overwritten completely, if already present.

Parameters:
  • content (str) – Content of the file. Will be encoded into UTF-8.
  • fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
  • atomic (bool, optional) – If True, write file atomically.
Raises:
  • ValueError – Encoding into UTF-8 failed.
  • OSError – File could not be opened.
FEV_KEGG.KEGG.File.writeToFileBytes(data, fileName: will be overwritten, if already present, atomic=True)[source]

Writes content to a binary file.

fileName is relative to your cache folder! See FEV_KEGG.settings.cachePath. File will be overwritten completely, if already present.

Parameters:
  • data (bytes or bytearray) – Content of the file. Will not be encoded.
  • fileName (str) – Path and name of the file, in a format your OS understands. Something like ‘subfolder/another_folder/myFile.txt’ should most likely work.
  • atomic (bool, optional) – If True, write file atomically.
Raises:

OSError – File could not be opened.
FEV_KEGG.KEGG.NUKA module
class FEV_KEGG.KEGG.NUKA.NUKA[source]

Bases: object

This is a hypothetical ‘complete’ organism - NUKA - which possesses all EC numbers known to all metabolic KEGG pathways.

Conversions to other graph types are not possible, because as a hypothetical organism, NUKA has no genes.

Variables:self.nameAbbreviation (str) –
_SubstanceReactionGraph2SubstanceEcGraph(speciesSubstanceReactionGraph: FEV_KEGG.Graph.SubstanceGraphs.SubstanceReactionGraph) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Converts NUKA’s substance-reaction graph into a substance-EC graph. Uses pathway information embedded into the graph object.

Parameters:speciesSubstanceReactionGraph (SubstanceReactionGraph) – NUKA’s substance-reaction graph.
Returns:NUKA’s substance-EC graph.
Return type:SubstanceEcGraph

Warning

This function is special to NUKA and MUST NOT be used anywhere else!

substanceEcGraph

NUKA’s substance-EC graph.

Returns:

Contains all substrates/products and all EC numbers known to KEGG’s metabolic pathways.
Return type:

SubstanceEcGraph
Raises:
  • HTTPError – If any underlying organism, pathway, or gene does not exist.
  • URLError – If connection to KEGG fails.
substanceReactionGraph

NUKA’s substance-reaction graph.

Returns:

Contains all substrates/products and all reactions known to KEGG’s metabolic pathways.
Return type:

SubstanceReactionGraph
Raises:
  • HTTPError – If any underlying organism, pathway, or gene does not exist.
  • URLError – If connection to KEGG fails.

Note

This SubstanceReactionGraph can NOT be converted into a SubstanceGeneGraph, as the pathways do not contain gene information!

FEV_KEGG.KEGG.Organism module
class FEV_KEGG.KEGG.Organism.Group(organismAbbreviations: Iterable[str] = None, searchString: any part of organism description = None, name=None, minimalSize=None)[source]

Bases: object

A Group of Organism.

If both parameters, organismAbbreviations and searchString, are specified, both lists will be appended, forming this group’s list of organisms. If none of the parameters is specified, this Group has an empty organism list.

Parameters:
  • organismAbbreviations (Iterable[str], optional) – Abbreviations of the desired organisms. If != None, tries to find one Organism for each abbreviation in the list.
  • searchString (str, optional) – Any part of the desired organisms’ description. If != None, searches the list of all organisms known to KEGG for the passed string. An example entry of the KEGG list of organisms looks as follows: “T00338 eci Escherichia coli O18:K1:H7 UTI89 (UPEC) Prokaryotes;Bacteria;Gammaproteobacteria - Enterobacteria;Escherichia”. Any list entry matching the search string creates one Organism, aggregated into this group.
  • name (str, optional) – Custom name of this group.
  • minimalSize (int, optional) – If not None, incorporate only organisms with EC graphs with at least minimalSize edges. Can be useful to filter incompletely annotated organisms.
Variables:
  • self.searchString (str) –
  • self.name (str) –
Raises:
  • ValueError – If any organism does not exist at all in KEGG.
  • URLError – If connection to KEGG fails.
_getGraphsParallelly(worker, organisms, noMultifunctional, debugText, minimalSize=None)[source]

Does the actual fetching and computing of the graphs in parallel.

Raises:TypeError – If you failed to enable FEV_KEGG.settings.automaticallyStartProcessPool or to provide a FEV_KEGG.Util.Parallelism.processPool.

Warning

If you did not enable parallel computation by either enabling FEV_KEGG.settings.automaticallyStartProcessPool or providing FEV_KEGG.Util.Parallelism.processPool, this will fail with a TypeError.

Note

If you enabled FEV_KEGG.settings.automaticallyStartProcessPool, this will run parallelly in multiple processes with multiple threads in each, depending on your settings and computer.

collectiveEcGraph(noMultifunctional=True, addCount=False, keepOnHeap=True, addEcDescriptions=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

The collective of all SubstanceEcGraphs, by union operation, from all organisms in this group.

Nodes of the same Substance are merged, all edges of differing ECs with a unique pair of nodes survive.

Parameters:
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
  • addCount (bool, optional) – If True, the returned graph contains extra dicts. 1 graph.nodeCounts[node] = number of organisms which contained this node. 2 graph.edgeCounts[(node, node, element)] = number of organisms which contained this edge. 3 graph.edgeElementCounts[element] = number of organisms which contained this element. Attention! These counter dictionaries are NOT updated if your add or remove a node/edge/element!
  • keepOnHeap (bool, optional) – Keeps a common graph in memory to speed up subsequent calls of this or other methods. This can take up a lot of memory! Once this object is garbage collected, the common graph will be, too.
Returns:

The substance-EC graph composed of all this group’s organism’s substance-EC graphs.
Return type:

SubstanceEcGraph
Raises:

See also

FEV_KEGG.Graph.Models.CommonGraphApi.union()
Union operator.
collectiveEnzymeGraph(noMultifunctional=True, keepOnHeap=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

The collective of all SubstanceEnzymeGraphs, by union operation, from all organisms in this group.

Nodes of the same Substance are merged, all edges of differing Enzymes with a unique pair of nodes survive. Enzymes are compared by their GeneID and should, thus, all be different!

Parameters:
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
  • keepOnHeap (bool, optional) – Keeps a common graph in memory to speed up subsequent calls of this or other methods. This can take up a lot of memory! Once this object is garbage collected, the common graph will be, too.
Returns:

The substance-enzyme graph composed of all this group’s organism’s substance-enzyme graphs.
Return type:

SubstanceEnzymeGraph
Raises:

See also

FEV_KEGG.Graph.Models.CommonGraphApi.union()
Union operator.
collectiveEnzymeGraphByEcConsensus(noMultifunctional=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

The collective SubstanceEnzymGraph, but containing only Enzymes whose EC numbers occur in the consensus of all SubstanceEcGraphs.

Parameters:

noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
Raises:
collectiveEnzymeGraphByEcMajority(majorityPercentage=80, majorityTotal=None, noMultifunctional=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

The collective SubstanceEnzymGraph, but containing only Enzymes whose EC numbers occur in the majority of all SubstanceEcGraphs.

Parameters:
  • majorityPercentage (float, optional) – Majority percentage means ‘at least x%’ and is rounded up. For example 90% of 11 organisms would be ceiling(9,9) = 10 organisms.
  • majorityTotal (int, optional) – If given (not None), majorityPercentage is ignored and the percentage of organisms for a majority is calculated from majorityTotal alone.
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
Raises:
consensusEcGraph(noMultifunctional=True, keepOnHeap=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

The consensus of all SubstanceEcGraphs, by intersection operation, from all organisms in this group.

Afterwards, removes isolated nodes.

Parameters:
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
  • keepOnHeap (bool, optional) – Keeps a common graph in memory to speed up subsequent calls of this or other methods. This can take up a lot of memory! Once this object is garbage collected, the common graph will be, too.
Returns:

The substance-EC graph intersected of all this group’s organism’s substance-EC graphs.
Return type:

SubstanceEcGraph
Raises:

See also

FEV_KEGG.Graph.Models.CommonGraphApi.intersection()
Intersection operator.
ecGraphs(noMultifunctional=True, minimalSize=None) → List[FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph][source]

All substance-EC graphs of this group.

Parameters:
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
  • minimalSize (int, optional) – If not None, return only EC graphs with at least minimalSize edges. Can be useful to filter incompletely annotated organisms.
Returns:

Substance-EC graphs of all organisms in this group. Order is arbitrary.
Return type:

List[SubstanceEcGraph]
Raises:
enzymeGraphs(noMultifunctional=True) → List[FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph][source]

All substance-enzyme graphs of this group.

Parameters:

noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
Returns:

Substance-enzyme graphs of all organisms in this group. Order is arbitrary.
Return type:

List[SubstanceEnzymeGraph]
Raises:
freeHeap()[source]

Free heap of memory-cached data.

Removes objects kept on heap, i.e. which have a pointer kept in this object, because some function was called with keepOnHeap == True. Also calls garbage collector to break reference cycles in previously uncollected objects (generation 0).

Note

Instead of using this, you will most likely want to never use any of the group methods with keepOnHeap == True. Then, calling this method would be unnecessary, as it would have no effect.

majorityEcGraph(majorityPercentage=90, majorityTotal=None, noMultifunctional=True, keepOnHeap=True) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

The majority-consensus of all SubstanceEcGraphs, by majority-intersection operation, from all organisms in this group.

If the majority of organisms contains an edge, it is added to the majority-consensus. Afterwards, removes isolated nodes.

Parameters:
  • majorityPercentage (float, optional) – Majority percentage means ‘at least x%’ and is rounded up. For example 90% of 11 organisms would be ceiling(9,9) = 10 organisms.
  • majorityTotal (int, optional) – If given (not None), majorityPercentage is ignored and the percentage of organisms for a majority is calculated from majorityTotal alone.
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
  • keepOnHeap (bool, optional) – Keeps a common graph in memory to speed up subsequent calls of this or other methods. This can take up a lot of memory! Once this object is garbage collected, the common graph will be, too.
Returns:

The substance-EC graph majority-intersected of all this group’s organism’s substance-EC graphs.
Return type:

SubstanceEcGraph
Raises:

See also

FEV_KEGG.Graph.Models.CommonGraphApi.majorityIntersection()
Majority intersection operator.
organisms

Organisms of this group.

Returns:The set of organisms which are part of this group. Order is arbitrary.
Return type:Set[Organism]
organismsCount

Number of organisms of this group.

Returns:The number of organisms in the set of organisms of this group.
Return type:int
class FEV_KEGG.KEGG.Organism.Organism(nameAbbreviation: eco, skipExistsCheck=False)[source]

Bases: object

An Organism as listed in KEGG, e.g. Escherichia coli K-12 MG1655 “eco”.

Checks whether the organism actually exists before creating the object.

Parameters:
  • nameAbbreviation (str) – The abbreviation of an organism as used in KEGG.
  • skipExistsCheck (bool, optional) – If True, skips the check for existence of an organism identified by nameAbbreviation. Any subsequent method access may raise an error if the organism does not exist in KEGG!
Variables:

self.nameAbbreviation (str) –

Raises:
  • ValueError – If the organism does not exist at all in KEGG.
  • URLError – If the connection to the KEGG server fails and the requested organism has not already been cached.

Note

All operations are cached via FEV_KEGG.KEGG.Database. This includes any downloads and the calculations available directly via this class.

GLOBAL_PATHWAY_PATTERN = re.compile('01[12][0-9]{2}')

Pattern defining a global/overview pathway.

These pathways should contain nothing more and nothing less than what is included in all non-global pathways. At least concerning metabolic pathways. Alas, they do not. Global/Overview pathways are often inconsistent with the union of all pathways. Also, they discard information about edge direction, containing only undirected edges.

classmethod __initBulk__(nameAbbreviations: List[str]) → List[FEV_KEGG.KEGG.Organism.Organism][source]

Creates many Organism objects at once.

Checking for existence is much faster when done this way, because it is parallelised. Pathologically non-existent organisms are automatically filtered, see FEV_KEGG.quirks.NON_EXISTING_ORGANISMS

Parameters:

nameAbbreviations (list[str]) – List of abbreviation strings which will be used to create an Organism.
Returns:

List of Organism objects. Or None if none of the nameAbbreviations existed.
Return type:

List[Organism]
Raises:
  • ValueError – If any organism does not exist at all in KEGG.
  • URLError – If the connection to the KEGG server fails and the requested organism has not already been cached.
classmethod _filterGlobalAndOverview(pathwayDescriptions: Set[str]) → Set[str][source]

Removes pathway descriptions of pathways belonging to global or overview maps.

Parameters:pathwayDescriptions (Set[str]) – The pathway descriptions to filter.
Returns:Pathway descriptions, leaving only the ones not from a global/overview pathway.
Return type:Set[str]
_filterNonMetabolic(pathwayDescriptions: Set[str]) → Set[str][source]

Removes pathway descriptions of pathways not belonging to metabolism.

Parameters:pathwayDescriptions (Set[str]) – The pathway descriptions to filter.
Returns:Pathway descriptions, leaving only the ones from pathways belonging to metabolism.
Return type:Set[str]

See also

FEV_KEGG.quirks.METABOLIC_PATHWAYS()
List of names for all pathways belonging to metabolism.
getGene(gene: eco:b0004 or b0004) → FEV_KEGG.KEGG.DataTypes.Gene[source]

Get a certain gene object for this organism.

Automatically recognises format.

Parameters:

gene (str) – Gene ID or name, e.g. ‘eco:b0004’ or ‘b0004’.
Returns:

Gene object.
Return type:

Gene
Raises:
  • HTTPError – If gene does not exist.
  • URLError – If connection to KEGG fails.
getGeneByID(geneID: eco:b0004) → FEV_KEGG.KEGG.DataTypes.Gene[source]

Get a certain gene object for this organism.

Does not check if the prefix matches this organism!

Parameters:

geneID (str) – Gene name, e.g. ‘eco:b0004’.
Returns:

Gene object.
Return type:

Gene
Raises:
  • HTTPError – If gene does not exist.
  • URLError – If connection to KEGG fails.
getGeneByName(geneName: b0004) → FEV_KEGG.KEGG.DataTypes.Gene[source]

Get a certain gene object for this organism.

Automatically prepends organism, eg. ‘eco:’+geneName.

Parameters:

geneName (str) – Gene name, e.g. ‘b0004’.
Returns:

Gene object.
Return type:

Gene
Raises:
  • HTTPError – If gene does not exist.
  • URLError – If connection to KEGG fails.
getGeneIDs(pathway: KGML_pathway.Pathway or 00260) → Set[str][source]

Get the set of all gene IDs of this organism in a certain pathway.

Automatically chooses getGeneIDsByName() or getGeneIDsByPathway(), depending on the type of pathway. Deduplicates original list.

Parameters:

pathway (Pathway or str) – The pathway to search, either as FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway object or its name as a string, e.g. ‘00260’.
Returns:

List of gene IDs in pathway, e.g. [‘eco:b0632’, ‘eco:b0839’, ‘eco:b2010’].
Return type:

Set[str]
Raises:
  • HTTPError – If name passed and pathway does not exist.
  • URLError – If name passed and connection fails.
getGeneIDsByName(pathwayName: 00260) → Set[str][source]

Get the set of all gene IDs of this organism for a pathway name.

Deduplicates original list.

Parameters:

pathwayName (str) – The pathway name to search, e.g. ‘00260’.
Returns:

List of gene IDs in pathwayName, e.g. [‘eco:b0632’, ‘eco:b0839’, ‘eco:b2010’].
Return type:

Set[str]
Raises:
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
getGeneIDsByPathway(pathway: FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway) → Set[str][source]

Get the set of all gene IDs of this organism for a FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway object.

Deduplicates original list.

Parameters:pathway (Pathway) – The pathway to search.
Returns:List of gene IDs in pathway, e.g. [‘eco:b0632’, ‘eco:b0839’, ‘eco:b2010’].
Return type:Set[str]
getGenes(pathway: KGML_pathway.Pathway or 00260) → Set[FEV_KEGG.KEGG.DataTypes.Gene][source]

Get the set of all genes of this organism in a certain pathway.

Automatically chooses getGenesByName() or getGenesByPathway(), depending on the type of pathway. Deduplicates original list.

Parameters:

pathway (Pathway or str) – The pathway to search, either as FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway object or its name as a string, e.g. ‘00260’.
Returns:

List of gene IDs in pathway, e.g. [‘eco:b0632’, ‘eco:b0839’, ‘eco:b2010’].
Return type:

Set[Gene]
Raises:
  • HTTPError – If name passed and pathway does not exist.
  • URLError – If name passed and connection fails.
getGenesByName(pathwayName: 00260) → Set[FEV_KEGG.KEGG.DataTypes.Gene][source]

Get the set of all genes of this organism for a pathway name.

Deduplicates original list.

Parameters:

pathwayName (str) – The pathway name to search, e.g. ‘00260’.
Returns:

List of gene IDs in pathwayName, e.g. [‘eco:b0632’, ‘eco:b0839’, ‘eco:b2010’].
Return type:

Set[Gene]
Raises:
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
getGenesByPathway(pathway: FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway) → Set[FEV_KEGG.KEGG.DataTypes.Gene][source]

Get the set of all genes of this organism for a FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway object.

Deduplicates original list.

Parameters:pathway (Pathway) – The pathway to search.
Returns:List of gene IDs in pathway, e.g. [‘eco:b0632’, ‘eco:b0839’, ‘eco:b2010’].
Return type:Set[Gene]
getMetabolicPathwayDescriptions(includeOverviewMaps=False) → Set[str][source]

Get descriptions of pathways that are part of metabolism.

Parameters:

includeOverviewMaps (bool, optional) – Whether to include global/overview maps.
Returns:

Set of pathway descriptions for all known metabolic pathways.
Return type:

Set[str]
Raises:
  • NoKnownPathwaysError – If the organism has no known pathways.
  • HTTPError – If pathway description list should not exist. Which would be odd, if we are certain and tested that the organism itself exists.
  • URLError – If connection to KEGG fails.
getMetabolicPathways(includeOverviewMaps=False) → Set[FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway][source]

Gets a set of all metabolic pathway objects for this organism.

Parameters:

includeOverviewMaps (bool, optional) – Whether to include global/overview maps.
Returns:

Set of pathways objects for all known metabolic pathways.
Return type:

Set[Pathway]
Raises:
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
getNumberOfGenes()[source]

Get the number of known genes within this genome.

Returns:Count of genes in this organism’s genome. These do not necessarily have to be mentioned in any pathway.
Return type:int
getPathway(pathwayName: 00260) → FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway[source]

Gets a certain pathway for this organism.

Parameters:

pathwayName (str) – The name/number of the pathway, e.g. “00260”. This will be expanded with self.nameAbbreviation to, e.g. “eco:00260”.
Returns:

The pathway object, or None if such a pathway does not exist.
Return type:

Pathway
Raises:
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
getPathwayDescriptions(includeOverviewMaps=False) → Set[str][source]

Get pathway descriptions for this organism.

Parameters:

includeOverviewMaps (bool, optional) – Whether to include global/overview maps.
Returns:

Set of pathway descriptions for all known pathways.
Return type:

Set[str]
Raises:
  • NoKnownPathwaysError – If the organism has no known pathways.
  • HTTPError – If any other HTTP error occurs.
  • URLError – If connection to KEGG fails.
getPathwayIDs(pathwayDescriptions: Set[str]) → Set[str][source]

Get pathway IDs from a set of descriptions.

A pathway ID is the occurence of a specific pathway in a specific organism, e.g. pathway ‘00260’ in ‘eco’ -> ‘eco00260’.

Parameters:pathwayDescriptions (Set[str]) – The pathway descriptions to be searched, e.g. ‘path:eco00260 Glycine, serine and threonine metabolism - Escherichia coli K-12 MG1655’.
Returns:Pathway IDs, e.g. ‘eco00260’.
Return type:Set[str]
getPathwayNames(pathwayIDs: Set[str]) → Set[str][source]

Get pathway names from a set of IDs.

A pathway name is a specific pathway, independent from any organism.

Parameters:pathwayDescriptions (Set[str]) – The pathway IDs to be searched, e.g. ‘eco00260’.
Returns:Pathway name, e.g. ‘00260’.
Return type:Set[str]
getPathways(includeOverviewMaps=False) → Set[FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway][source]

Gets a set of all pathway objects for this organism.

Parameters:

includeOverviewMaps (bool, optional) – Whether to include global/overview maps.
Returns:

Set of pathways objects for all known pathways.
Return type:

Set[Pathway]
Raises:
  • NoKnownPathwaysError – If the organism has no known pathways.
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
getPathwaysFromNames(pathwayNameSet: Set[str]) → Set[FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway][source]

Gets a set of pathway objects for this organism, based on a set of pathway names, eg. {‘00260’, ‘01100’}.

Parameters:

pathwayNameSet (Set[str]) – The names/numbers of the pathways, e.g. ‘00260’. This will be expanded with self.nameAbbreviation to, e.g. ‘eco00260’.
Returns:

Set of pathways objects for all pathways from pathwayNameSet. If pathway exists, but has no KGML format, the entry for this pathway is None.
Return type:

Set[Pathway]
Raises:
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
metabolicPathways

Pathways of metabolism, without overview or global maps.

Returns:

Set of pathways objects for all known metabolic pathways, excluding global/overview pathways.
Return type:

Set[Pathway]
Raises:
  • HTTPError – If pathway does not exist.
  • URLError – If connection to KEGG fails.
substanceEcGraph(noMultifunctional=True, returnCacheEntry=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEcGraph[source]

Substance-EC graph of this organism.

Parameters:
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
  • returnCacheEntry (bool, optional) – If True, do not return the graph, but instead a FEV_KEGG.KEGG.File.CacheEntry. This cache entry can be useful for parallel computation.
Returns:

The graph has substrates/products as its nodes and EC numbers as the connecting edges. Edges have a direction.
Return type:

SubstanceEcGraph
Raises:
  • HTTPError – If any gene or pathway does not exist.
  • URLError – If connection to KEGG fails.
substanceEnzymeGraph(noMultifunctional=True, returnCacheEntry=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceEnzymeGraph[source]

Substance-Enzyme graph of this organism.

Parameters:
  • noMultifunctional (bool, optional) – If True, ignore enzymes with multiple EC numbers.
  • returnCacheEntry (bool, optional) – If True, do not return the graph, but instead a FEV_KEGG.KEGG.File.CacheEntry. This cache entry can be useful for parallel computation.
Returns:

The graph has substrates/products as its nodes and enzymes as the connecting edges. Edges have a direction.
Return type:

SubstanceEnzymeGraph
Raises:
  • HTTPError – If any gene or pathway does not exist.
  • URLError – If connection to KEGG fails.
substanceGeneGraph(returnCacheEntry=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceGeneGraph[source]

Substance-Gene graph of this organism.

Parameters:

returnCacheEntry (bool, optional) – If True, do not return the graph, but instead a FEV_KEGG.KEGG.File.CacheEntry. This cache entry can be useful for parallel computation.
Returns:

The graph has substrates/products as its nodes and genes as the connecting edges. Edges have a direction.
Return type:

SubstanceGeneGraph
Raises:
  • HTTPError – If any gene or pathway does not exist.
  • URLError – If connection to KEGG fails.
substanceReactionGraph(returnCacheEntry=False) → FEV_KEGG.Graph.SubstanceGraphs.SubstanceReactionGraph[source]

Substance-Reaction graph of this organism.

Parameters:

returnCacheEntry (bool, optional) – If True, do not return the graph, but instead a FEV_KEGG.KEGG.File.CacheEntry. This cache entry can be useful for parallel computation.
Returns:

The graph has substrates/products as its nodes and reactions as the connecting edges. Edges have a direction.
Return type:

SubstanceReactionGraph
Raises:
  • HTTPError – If any gene or pathway does not exist.
  • URLError – If connection to KEGG fails.
FEV_KEGG.KEGG.SSDB module

This module represents the model of all intermediate stages of matches acquired via KEGG SSDB database, partly in conjunction with KEGG GENE.

The methods to actually perform the retrieval are not part of this module. See FEV_KEGG.KEGG.Database and FEV_KEGG.KEGG.Download for these.

class FEV_KEGG.KEGG.SSDB.JSONpickable[source]

Bases: object

__str__()[source]

Encodes object to “unpickable” JSON.

Returns:Object in JSON format, including information to “unpickle” it back into an object.
Return type:str
class FEV_KEGG.KEGG.SSDB.Match(foundGeneIdString, swScore, bitScore, identity, overlap, length)[source]

Bases: FEV_KEGG.KEGG.SSDB.PreMatch

A sequence comparison match between two distinct genes, including calculated attributes.

During creation, foundGeneIdString is used to create a GeneID object, saved as foundGeneID

Parameters:
  • foundGeneIdString (str) – ID of the gene found by SSDB to be a paralog/ortholog, e.g. syn:sll1452.
  • swScore (int) – Smith-Waterman score of the match between the gene which was searched for and the found gene specified by foundGeneIdString.
  • bitScore (float) – Length-normalised swScore scaled to bits.
  • identity (float) – Percentage of equal amino acids, without substitution.
  • overlap (int) – Number of amino acids the found gene sequence overlaps with the gene which was searched for. Maximum is the length of the searched-for gene.
  • length (int) – Length in amino acids of the found gene. Derived from downloading the gene’s information file.
Variables:
  • self.foundGeneIdString (str) –
  • self.swScore (int) –
  • self.bitScore (float) –
  • self.identity (float) –
  • self.overlap (int) –
  • self.length (int) –
  • self.foundGeneID (FEV_KEGG.Graph.Elements.GeneID) –

See also

PreMatch
Handles all other parameters.
classmethod fromPreMatch(preMatch: FEV_KEGG.KEGG.SSDB.PreMatch, length)[source]

Cast a PreMatch object to an object of this class.

During casting, foundGeneIdString is used to create a GeneID object, stored as foundGeneID. Also, save is stored.

Parameters:
  • preMatch (PreMatch) – The object to cast into this class’ type.
  • length (int) – Length in amino acids of the found gene. Derived from downloading the gene’s information file.

Note

This class method simply casts the PreMatch object, instead of going through creating a new Match object. This helps performance and does not significantly impact complexity.

class FEV_KEGG.KEGG.SSDB.Matching(queryGeneID: FEV_KEGG.Graph.Elements.GeneID, queryLength, databaseOrganism, databaseSize, matches: Iterable[FEV_KEGG.KEGG.SSDB.Match], timestamp)[source]

Bases: FEV_KEGG.KEGG.SSDB.JSONpickable

Result of a search for orthologs or paralogs in SSDB, concerning a single target organism.

The E-values for the resulting Matches depend on database size and are therefore only valid at the specified timestamp.

Parameters:
  • queryGeneID (GeneID) – ID of the gene to search homologs for, e.g. “syn:sll1450”.
  • queryLength (int) – Length of the gene product in amino acids.
  • databaseOrganism (str) – Organism to search in to find homologs for queryGeneID, e.g. “eco”.
  • databaseSize (int) – Number of genes known to belong to the databaseOrganism. This can be queried by http://rest.kegg.jp/info/eco, currently yielding “4,498 entries”.
  • matches (Iterable[Match]) – Iterable of Match objects, one for each match found during the matching.
  • timestamp (int) – When was the query run? As UNIX epoch timestamp in seconds.
Variables:
class FEV_KEGG.KEGG.SSDB.MatchingOverview(queryGeneID: FEV_KEGG.Graph.Elements.GeneID, queryLength, bestMatches: Iterable[FEV_KEGG.KEGG.SSDB.Match], timestamp)[source]

Bases: FEV_KEGG.KEGG.SSDB.JSONpickable

Result of a search for orthologs in SSDB, concerning all possible target organisms.

Because all possible organisms are searched, only the best matches are returned. If you want all matches, you will have to use Matching in a second step. The E-values for the resulting Matches depend on database size and are therefore only valid at the specified timestamp.

Parameters:
  • queryGeneID (GeneID) – ID of the gene to search homologs for, e.g. “syn:sll1450”.
  • queryLength (int) – Length of the gene product in amino acids.
  • bestMatches (Iterable[Match]) – Iterable of best Match objects, one for each orthologous organism found during the matching overview.
  • timestamp (int) – When was the query run? As UNIX epoch timestamp in seconds.
Variables:
getTransientMatches(relevantOrganisms: Iterable[str]) → List[FEV_KEGG.KEGG.SSDB.TransientMatch][source]

Get full transient matches, considering only relevant orthologous organisms.

Considering only relevant organisms is necessary, because a gene can have several thousand orthologs, including ones from organisms completely out of scope, while calculating the E-value for each of those matches is rather slow and involves several downloads.

Parameters:relevantOrganisms (Iterable[str]) – Iterable of organism abbreviations, for each organism to be considered relevant.
Returns:List of transient matches. These include E-values, which are slow to calculate, which is why only relevantOrganisms are considered. This means that only matches found in self.bestMatches which come from relevant organisms are actually converted to transient matches.
Return type:List[TransientMatch]
class FEV_KEGG.KEGG.SSDB.PreMatch(foundGeneIdString, swScore, bitScore, identity, overlap)[source]

Bases: object

A sequence comparison match between two distinct genes, without calculated attributes.

The parameters can be retrieved via KEGG SSDB [1].

Parameters:
  • foundGeneIdString (str) – ID of the gene found by SSDB to be a paralog/ortholog, e.g. syn:sll1452.
  • swScore (int) – Smith-Waterman score of the match between the gene which was searched for and the found gene specified by foundGeneIdString.
  • bitScore (float) – Length-normalised swScore scaled to bits.
  • identity (float) – Percentage of equal amino acids, without substitution.
  • overlap (int) – Number of amino acids the found gene sequence overlaps with the gene which was searched for. Maximum is the length of the searched-for gene.
Variables:
  • self.foundGeneIdString (str) –
  • self.swScore (int) –
  • self.bitScore (float) –
  • self.identity (float) –
  • self.overlap (int) –

See also

FEV_KEGG.KEGG.Database.getOrthologs
Function to retrieve PreMatches from KEGG SSDB.

References

[1]Sato et al. (2001), “SSDB: Sequence Similarity Database in KEGG”, https://www.researchgate.net/publication/254718427_SSDB_Sequence_Similarity_Database_in_KEGG
class FEV_KEGG.KEGG.SSDB.TransientMatch(foundGeneIdString, swScore, bitScore, identity, overlap, length, eValue)[source]

Bases: FEV_KEGG.KEGG.SSDB.Match

A sequence comparison match between two distinct genes, only valid at a certain point in time.

This match is transient, because it is only valid for a certain point in time, because eValue changes with the size of the database.

Parameters:
  • foundGeneIdString (str) – ID of the gene found by SSDB to be a paralog/ortholog, e.g. syn:sll1452.
  • swScore (int) – Smith-Waterman score of the match between the gene which was searched for and the found gene specified by foundGeneIdString.
  • bitScore (float) – Length-normalised swScore scaled to bits.
  • identity (float) – Percentage of equal amino acids, without substitution.
  • overlap (int) – Number of amino acids the found gene sequence overlaps with the gene which was searched for. Maximum is the length of the searched-for gene.
  • length (int) – Length in amino acids of the found gene. Derived from downloading the gene’s information file.
  • eValue (float) – Statistical expectation value for the chance of yielding a match of the same score by pure randomness alone.
Variables:
  • self.foundGeneIdString (str) –
  • self.swScore (int) –
  • self.bitScore (float) –
  • self.identity (float) –
  • self.overlap (int) –
  • self.length (int) –
  • self.foundGeneID (FEV_KEGG.Graph.Elements.GeneID) –
  • self.eValue (float) –

See also

Match
Handles all other parameters.
classmethod fromMatch(match: FEV_KEGG.KEGG.SSDB.Match, eValue)[source]

Cast a Match object to an object of this class.

During casting, eValue is stored.

Note

This class method simply casts the Match object, instead of going through creating a new TransientMatch object. This helps performance and does not significantly impact complexity.

Module contents

FEV_KEGG.Robustness package

Subpackages
FEV_KEGG.Robustness.Topology package
Submodules
FEV_KEGG.Robustness.Topology.Redundancy module

In this module robustness is reduced to the topological point of view. When doing so robustness equals redundancy. The term ‘robustness’ is treated as a special case of ‘flexibility’, meaning both are concepts of redundancy.

Definitions

If a key element is deleted from a graph, e.g. all enzymes realising a certain EC number are deleted from an organism’s genome:

‘Flexibility’ exists if the former substrates and/or products can still be (at least partially) metabolised via alternative paths, in their original respective direction. This does not mean the alternative paths have to include both, the orginal substrate and product, at the same time.

‘Robustness’ exists if the former substrates and products are (at least partially) still connected, in their original direction, albeit via alternative paths. This means the alternative paths have to include both, the orginal substrate and product, at the same time.

class FEV_KEGG.Robustness.Topology.Redundancy.Comparison(graphA: FEV_KEGG.Graph.Models.DirectedMultiGraph, graphB: FEV_KEGG.Graph.Models.DirectedMultiGraph)[source]

Bases: object

Compare redundancy between two graphs.

Parameters:
Variables:
classmethod fromCladePair(cladePair: FEV_KEGG.Evolution.Clade.CladePair, majorityPercentage=None)[source]

Compare redundancy between two clades’ core metabolisms.

Parameters:
  • cladePair (CladePair) – The pair of clades from which to extract the graph.
  • majorityPercentage (float, optional) – If None, use collective EC graph. If not None, use majority EC graph with majorityPercentage % majority.
Returns:
Return type:

Comparison
classmethod fromOrganismGroups(groupA: FEV_KEGG.KEGG.Organism.Group, groupB: FEV_KEGG.KEGG.Organism.Group, majorityPercentage=None)[source]

Compare redundancy between two groups’ core metabolisms.

Parameters:
  • groupA (Organism.Group) – First group from which to extract the graph.
  • groupB (Organism.Group) – Second group from which to extract the graph.
  • majorityPercentage (float, optional) – If None, use collective EC graph. If not None, use majority EC graph with majorityPercentage % majority.
Returns:
Return type:

Comparison
getAddedRedundancyKeys(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Elements.Element][source]

Get keys which have become redundant from graph A to graph B.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:Set[Element]
getAddedRedundancyKeysPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Models.Path]][source]

Get alternative paths of keys which have become redundant from graph A to graph B.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths belonging to a key which has become redundant, keyed by this key.
Return type:Dict[Element, Set[Path]]
getAddedRedundancyPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.Path][source]

Get all alternative paths which have been added from graph A to graph B.

This counts all paths, no matter which key they provide redundancy for!

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths which have been added in graph B.
Return type:Set[Path]
getAddedRedundancyRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of keys, which have become redundant from graph A to graph B, to all keys.

This only counts keys which exist in both graphs, for both ‘redundant keys’ and ‘all keys’.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:float
getConservedRedundancyKeys(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Elements.Element][source]

Get keys which have conserved redundancy from graph A to graph B.

This only counts keys which exist in both graphs. Beware, this only means there is some redundancy in A and B, not the exact same paths providing redundancy in A and B!

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:Set[Element]
getConservedRedundancyKeysPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Tuple[Set[FEV_KEGG.Graph.Models.Path], Set[FEV_KEGG.Graph.Models.Path], Set[FEV_KEGG.Graph.Models.Path]]][source]

Get tuple of alternative paths of keys which have conserved redundancy from graph A to graph B.

This only counts keys which exist in both graphs. However, even if a key is redundant in both graphs, it does not have to be redundant due to the exact same paths. This is why the tuple has three sets, the first for paths which only exist only in A, the second for paths which exist in both, and the third for paths which exist only in B.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Tuple of sets of alternative paths belonging to a key which conserved redundancy, keyed by this key. The first set of the tuple contains paths which only exists in graph A. The second set of the tuple contains paths which exist in both graphs. The third set of the tuple contains paths which only exists in graph B.
Return type:Dict[Element, Tuple[Set[Path], Set[Path], Set[Path]]]
getConservedRedundancyPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.Path][source]

Get all alternative paths which have been conserved between graph A and graph B.

This counts all paths, no matter which key they provide redundancy for!

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths which are both in graph A and in graph B.
Return type:Set[Path]
getConservedRedundancyRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of keys, which have conserved redundancy from graph A to graph B, to all keys.

This only counts keys which exist in both graphs, for both ‘redundant keys’ and ‘all keys’.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:float
getLostRedundancyKeys(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Elements.Element][source]

Get keys which have lost redundancy from graph A to graph B.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:Set[Element]
getLostRedundancyPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.Path][source]

Get all alternative paths which have been lost from graph A to graph B.

This counts all paths, no matter which key they provide redundancy for!

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths which have been lost in graph B.
Return type:Set[Path]
getLostRedundancyPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Models.Path]][source]

Get alternative paths of keys which have lost redundancy from graph A to graph B.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths belonging to a key which lost redundancy, keyed by this key.
Return type:Dict[Element, Set[Path]]
getLostRedundancyRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of keys, which have lost redundancy from graph A to graph B, to all keys.

This only counts keys which exist in both graphs, for both ‘redundant keys’ and ‘all keys’.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:float
class FEV_KEGG.Robustness.Topology.Redundancy.ContributionComparison(comparison: FEV_KEGG.Robustness.Topology.Redundancy.Comparison, specialKeysA: Set[FEV_KEGG.Graph.Elements.Element], specialKeysB: Set[FEV_KEGG.Graph.Elements.Element])[source]

Bases: object

Compare contribution to redundancy between two graphs.

Allows to answer the question how much certain key elements contribute to certain comparing aspects of the flexibility/robustness of two graphs. Special keys will usually differ between the two graphs, however, they are also allowed to be the same set.

Parameters:
  • comparison (Comparison) – You first have to calculate a comparison object using your two graphs.
  • specialKeysA (Set[Element]) – Set of key elements of graph A in comparison viewed to be somehow special. One type of special could be ‘neofunctionalised’.
  • specialKeysB (Set[Element]) – Set of key elements of graph B in comparison viewed to be somehow special. One type of special could be ‘neofunctionalised’.
Variables:
getAddedRedundancyKeyContributionRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of contribution to rendundancy of keys, which have become redundant.

This only counts keys which exist in both graphs. The ratio is to the number of redundant keys, not to all keys.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Ratio of contribution to redundant keys, which have become redundant from graph A to graph B, and for which a special key contributes to redundancy.
Return type:float
getConservedRedundancyKeyContributionRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of contribution to rendundancy of keys, which have conserved redundancy.

A or B may have a special key on an alternative path of a redundant key, for the key to be counted here. It is not necessary, that both A and B have such a special key. This only counts keys which exist in both graphs. The ratio is to the number of redundant keys, not to all keys.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Ratio of contribution to redundant keys, which have conserved redundancy from graph A to graph B, and for which a special key contributes to redundancy.
Return type:float
getContributedAddedRedundancyKeysForSpecial(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Elements.Element]][source]

Get keys, which have become redundant, for which a special key contributes to redundancy.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Sets of key elements, which have become redundant from graph A to graph B, and which have a redundant path that contains a special key, keyed by the special key. All of these paths (except for maybe one) exist only in B.
Return type:Dict[Element, Set[Element]]
getContributedAddedRedundancyPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.MarkedPath][source]

Get all alternative paths which have become redundant, and have a special key on them.

This counts all paths, no matter which key they provide redundancy for!

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths which have become redundant from graph A to graph B.
Return type:Set[MarkedPath]
getContributedAddedRedundancyPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Models.MarkedPath]][source]

Get alternative paths of keys which have become redundant, and have a special key on them.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative marked paths belonging to a key which has become redundant from graph A to graph B, keyed by this key.
Return type:Dict[Element, Set[MarkedPath]]
getContributedConservedRedundancyKeysForSpecial(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Elements.Element]][source]

Get keys, which have conserved redundancy, for which a special key contributes to redundancy.

A or B may have a special key on an alternative path of a redundant key, for the key to be reported here. It is not necessary, that both A and B have such a special key. This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Sets of key elements, which have conserved redundancy from graph A to graph B, and which have a redundant path that contains a special key, keyed by the special key. All of these paths may exist in only A, only B, or in both. One occurence is enough to be reported here.
Return type:Dict[Element, Set[Element]]
getContributedConservedRedundancyPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.MarkedPath][source]

Get all alternative paths which have been conserved, and have a special key on them.

This counts all paths, no matter which key they provide redundancy for!

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths which have been conserved from graph A to graph B.
Return type:Set[MarkedPath]
getContributedConservedRedundancyPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Tuple[Set[FEV_KEGG.Graph.Models.MarkedPath], Set[FEV_KEGG.Graph.Models.MarkedPath], Set[FEV_KEGG.Graph.Models.MarkedPath]]][source]

Get alternative paths of keys which have conserved redundancy, and have a special key on them.

This only counts keys which exist in both graphs. However, even if a key is redundant in both graphs, it does not have to be redundant due to the exact same paths. This is why the tuple has three sets, the first for paths which only exist only in A, the second for paths which exist in both, and the third for paths which exist only in B.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Tuple of sets of alternative marked paths belonging to a key which conserved redundancy from graph A to graph B, keyed by this key. The first set of the tuple contains paths which only exists in graph A. The second set of the tuple contains paths which exist in both graphs. The third set of the tuple contains paths which only exists in graph B.
Return type:Dict[Element, Tuple[Set[MarkedPath], Set[MarkedPath], Set[MarkedPath]]]
getContributedLostRedundancyKeysForSpecial(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Elements.Element]][source]

Get keys, which have lost redundancy, for which a special key contributes to redundancy.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Sets of key elements, which have lost redundancy from graph A to graph B, and which have a redundant path that contains a special key, keyed by the special key. All of these paths (except for maybe one) exist only in A.
Return type:Dict[Element, Set[Element]]
getContributedLostRedundancyPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.MarkedPath][source]

Get all alternative paths which have been lost, and have a special key on them.

This counts all paths, no matter which key they provide redundancy for!

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative paths which have been lost from graph A to graph B.
Return type:Set[MarkedPath]
getContributedLostRedundancyPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Models.MarkedPath]][source]

Get alternative paths of keys which have lost redundancy, and have a special key on them.

This only counts keys which exist in both graphs.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of alternative marked paths belonging to a key which lost redundancy from graph A to graph B, keyed by this key.
Return type:Dict[Element, Set[MarkedPath]]
getLostRedundancyKeyContributionRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of contribution to rendundancy of keys, which have lost redundancy.

This only counts keys which exist in both graphs. The ratio is to the number of redundant keys, not to all keys.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Ratio of contribution to redundant keys, which have lost redundancy from graph A to graph B, and for which a special key contributes to redundancy.
Return type:float
class FEV_KEGG.Robustness.Topology.Redundancy.Flexibility(graph: FEV_KEGG.Graph.Models.DirectedMultiGraph, onlyLargestComponent=False)[source]

Bases: object

Flexibility metrics for a graph.

Parameters:
  • graph (DirectedMultiGraph) – The graph to be measured for its flexibility.
  • onlyLargestComponent (bool, optional) – If True, reduce graph to its largest component before measuring robustness.
Variables:
  • self.redundantPathsTupleForEdgeForKey (Dict[Element, Dict[Tuple[Element, Element], Tuple[Set[Path], Set[Path]]]]) – Each key element in graph pointing to a pseudo-set (dictionary.keys()) of its edges, represented by a tuple of both participating nodes. Each edge points to a set of paths, which would provide redundancy for this edge if it (or the whole key element) were to be removed.
  • self.sumKeys (int) – Sum of all individual key elements in graph.
  • = 0 (self.sumEdges) – Sum of all edges in graph.
  • self.sumPaths (int) – Sum of all paths providing redundancy for edges.
self.sumNonRedundantKeys : int
Sum of keys which, if removed, have not a single redundant edge. An edge is only redundant if it has redundant paths for both its source and its target node.
self.sumPartiallyRedundantKeys : int
Sum of keys which, if removed, have redundant edges, but not all of them are redundant. An edge is only redundant if it has redundant paths for both its source and its target node.
self.sumRedundantKeys : int
Sum of keys which, if removed, have only redundant edges. An edge is only redundant if it has redundant paths for both its source and its target node.
self.sumNonTargetRedundantKeys : int
Sum of keys which, if removed, have not a single target-redundant edge. An edge is target-redundant if it has redundant paths for its target node.
self.sumPartiallyTargetRedundantKeys : int
Sum of keys which, if removed, have target-redundant edges, but not all of them are target-redundant. An edge is target-redundant if it has redundant paths for its target node.
self.sumTargetRedundantKeys : int
Sum of keys which, if removed, have only target-redundant edges. An edge is target-redundant if it has redundant paths for its target node.
self.sumNonSourceRedundantKeys : int
Sum of keys which, if removed, have not a single source-redundant edge. An edge is source-redundant if it has redundant paths for its source node.
self.sumPartiallySourceRedundantKeys : int
Sum of keys which, if removed, have source-redundant edges, but not all of them are source-redundant. An edge is source-redundant if it has redundant paths for its source node.
self.sumSourceRedundantKeys : int
Sum of keys which, if removed, have only source-redundant edges. An edge is source-redundant if it has redundant paths for its source node.
self.nonRedundantKeys : Set[Element]
Set of key elements which, if removed, have not a single redundant edge. An edge is only redundant if it has redundant paths for both its source and its target node.
self.partiallyRedundantKeys : Set[Element]
Set of key elements which, if removed, have redundant edges, but not all of them are redundant. An edge is only redundant if it has redundant paths for both its source and its target node.
self.redundantKeys : Set[Element]
Set of key elements which, if removed, have only redundant edges. An edge is only redundant if it has redundant paths for both its source and its target node.
self.nonTargetRedundantKeys : Set[Element]
Set of key elements which, if removed, have not a single target-redundant edge. An edge is target-redundant if it has redundant paths for its target node.
self.partiallyTargetRedundantKeys : Set[Element]
Set of key elements which, if removed, have target-redundant edges, but not all of them are target-redundant. An edge is target-redundant if it has redundant paths for its target node.
self.targetRedundantKeys : Set[Element]
Set of key elements which, if removed, have only target-redundant edges. An edge is target-redundant if it has redundant paths for its target node.
self.nonSourceRedundantKeys : Set[Element]
Set of key elements which, if removed, have not a single source-redundant edge. An edge is source-redundant if it has redundant paths for its source node.
self.partiallySourceRedundantKeys : Set[Element]
Set of key elements which, if removed, have source-redundant edges, but not all of them are source-redundant. An edge is source-redundant if it has redundant paths for its source node.
self.sourceRedundantKeys : Set[Element]
Set of key elements which, if removed, have only source-redundant edges. An edge is source-redundant if it has redundant paths for its source node.
self.paths : Set[Path]
Set of all paths which act as redundancy for edges when a key has been removed.
self.targetPaths : Set[Path]
Set of all paths which act as redundancy for the target node of edges when a key has been removed.
self.sourcePaths : Set[Path]
Set of all paths which act as redundancy for the source node of edges when a key has been removed.
self.redundantKeysRatio : float
Ratio of the sum of redundant key elements to the sum of all key elements. An edge is only redundant if it has redundant paths for both its source and its target node.
self.partiallyRedundantKeysRatio : float
Ratio of the sum of partially redundant key elements to the sum of all key elements. An edge is only redundant if it has redundant paths for both its source and its target node.
self.nonRedundantKeysRatio : float
Ratio of the sum of non-redundant key elements to the sum of all key elements. An edge is only redundant if it has redundant paths for both its source and its target node.
self.targetRedundantKeysRatio : float
Ratio of the sum of target-redundant key elements to the sum of all key elements. An edge is target-redundant if it has redundant paths for its target node.
self.partiallyTargetRedundantKeysRatio : float
Ratio of the sum of partially target-redundant key elements to the sum of all key elements. An edge is target-redundant if it has redundant paths for its target node.
self.nonTargetRedundantKeysRatio : float
Ratio of the sum of non-target-redundant key elements to the sum of all key elements. An edge is target-redundant if it has redundant paths for its target node.
self.sourceRedundantKeysRatio : float
Ratio of the sum of target-redundant key elements to the sum of all key elements. An edge is source-redundant if it has redundant paths for its source node.
self.partiallySourceRedundantKeysRatio : float
Ratio of the sum of partially target-redundant key elements to the sum of all key elements. An edge is source-redundant if it has redundant paths for its source node.
self.nonSourceRedundantKeysRatio : float
Ratio of the sum of non-target-redundant key elements to the sum of all key elements. An edge is source-redundant if it has redundant paths for its source node.
partiallyRedundantKeyPaths
partiallySourceRedundantKeyPaths
partiallyTargetRedundantKeyPaths
paths
redundantKeyPaths
sourceRedundantKeyPaths
sumPaths
targetRedundantKeyPaths
class FEV_KEGG.Robustness.Topology.Redundancy.FlexibilityContribution(flexibility: FEV_KEGG.Robustness.Topology.Redundancy.Flexibility, specialKeys: Dict[str, Set[FEV_KEGG.Graph.Elements.Element]])[source]

Bases: object

Contribution to flexibility accountable to edges with specialKeys.

Allows to answer the question how much certain key elements contribute to the flexibility of a graph.

Parameters:
  • flexibility (Flexibility) –
  • specialKeys (Set[Element]) – Set of key elements viewed to be somehow special. One type of special could be ‘neofunctionalised’.
Variables:
  • self.flexibility (Flexibility) –
  • self.sumSpecialKeys (int) – Sum of special keys passed.
  • self.sumPathsWithSpecialKeys (int) – Sum of alternative paths with a special key on it.
  • self.sumRedundantKeysWithSpecialKeyOnPaths (int) – Sum of redundant keys which have a special key on an alternative path.
  • self.sumPartiallyRedundantKeysWithSpecialKeyOnPaths (int) – Sum of partially redundant keys which have a special key on an alternative path.
  • self.sumTargetRedundantKeysWithSpecialKeyOnPaths (int) – Sum of target-redundant keys which have a special key on an alternative path.
  • self.sumPartiallyTargetRedundantKeysWithSpecialKeyOnPaths (int) – Sum of partially target-redundant keys which have a special key on an alternative path.
  • self.sumSourceRedundantKeysWithSpecialKeyOnPaths (int) – Sum of source-redundant keys which have a special key on an alternative path.
  • self.sumPartiallySourceRedundantKeysWithSpecialKeyOnPaths (int) – Sum of partially source-redundant keys which have a special key on an alternative path.
self.pathsWithSpecialKeys : Set[MarkedPath]
Set of redundant paths with special keys on them.
self.targetPathsWithSpecialKeys : Set[MarkedPath]
Set of target-redundant paths with special keys on them.
self.sourcePathsWithSpecialKeys : Set[MarkedPath]
Set of source-redundant paths with special keys on them.
self.redundantKeySpecialKeysOnPaths : Dict[Element, Set[Element]]
Sets of special keys which are on an alternative path of a redundant key, keyed by the key.
self.partiallyRedundantKeySpecialKeysOnPaths : Dict[Element, Set[Element]
Sets of special keys which are on an alternative path of a partially redundant key, keyed by the key.
self.targetRedundantKeySpecialKeysOnPaths : Dict[Element, Set[Element]]
Sets of special keys which are on an alternative path of a target-redundant key, keyed by the key.
self.partiallyTargetRedundantKeySpecialKeysOnPaths : Dict[Element, Set[Element]
Sets of special keys which are on an alternative path of a partially target-redundant key, keyed by the key.
self.sourceRedundantKeySpecialKeysOnPaths : Dict[Element, Set[Element]]
Sets of special keys which are on an alternative path of a source-redundant key, keyed by the key.
self.partiallySourceRedundantKeySpecialKeysOnPaths : Dict[Element, Set[Element]
Sets of special keys which are on an alternative path of a partially source-redundant key, keyed by the key.
self.specialKeyOnRedundantKeysPaths : Dict[Element, Set[Element]]
Sets of redundant keys which have an alternative path with a special key on it, keyed by the special key.
self.specialKeyOnPartiallyRedundantKeysPaths : Dict[Element, Set[Element]]
Sets of partially redundant keys which have an alternative path with a special key on it, keyed by the special key.
self.specialKeyOnTargetRedundantKeysPaths : Dict[Element, Set[Element]]
Sets of target-redundant keys which have an alternative path with a special key on it, keyed by the special key.
self.specialKeyOnPartiallyTargetRedundantKeysPaths : Dict[Element, Set[Element]]
Sets of partially target-redundant keys which have an alternative path with a special key on it, keyed by the special key.
self.specialKeyOnSourceRedundantKeysPaths : Dict[Element, Set[Element]]
Sets of source-redundant keys which have an alternative path with a special key on it, keyed by the special key.
self.specialKeyOnPartiallySourceRedundantKeysPaths : Dict[Element, Set[Element]]
Sets of partially source-redundant keys which have an alternative path with a special key on it, keyed by the special key.
self.pathsWithSpecialKeyRatio : float
Ratio of the sum of paths with a special key on it to the sum of all paths.
self.redundantKeysWithSpecialKeyOnPathsRatio : float
Ratio of the sum of redundant keys with a special key on its paths to the sum of all redundant keys.
self.partiallyRedundantKeysWithSpecialKeyOnPathsRatio : float
Ratio of the sum of partially redundant keys with a special key on its paths to the sum of all partially redundant keys.
self.targetRedundantKeysWithSpecialKeyOnPathsRatio : float
Ratio of the sum of target-redundant keys with a special key on its paths to the sum of all target-redundant keys.
self.partiallyTargetRedundantKeysWithSpecialKeyOnPathsRatio : float
Ratio of the sum of partially target-redundant keys with a special key on its paths to the sum of all partially target-redundant keys.
self.sourceRedundantKeysWithSpecialKeyOnPathsRatio : float
Ratio of the sum of source-redundant keys with a special key on its paths to the sum of all source-redundant keys.
self.partiallySourceRedundantKeysWithSpecialKeyOnPathsRatio : float
Ratio of the sum of partially source-redundant keys with a special key on its paths to the sum of all partially source-redundant keys.
class FEV_KEGG.Robustness.Topology.Redundancy.Redundancy(graph: FEV_KEGG.Graph.Models.DirectedMultiGraph, onlyLargestComponent=False, onlyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = None)[source]

Bases: object

Redundancy metrics, consisting of Flexibility and class:Robustness.

The most important metrics are realised as methods.

Parameters:
  • graph (DirectedMultiGraph) – The graph to calculate flexibility and robustness metrics for.
  • onlyLargestComponent (bool, optional) – If True, reduce graph to its largest component before measuring redundancy.
  • onlyType (RedundancyType, optional) – If give, only metrics for this type of redundancy are actually calculated. Requests for metrics of another type of redundancy will raise an error!
Variables:

Warning

The underlying algorithms have a rather high memory-complexity. This is fine for small graphs, i.e. substance-EC graphs of the core metabolism. But for bigger graphs, i.e. substance-enzyme graphs of the core metabolism, memory consumption can easily exceed 16 GiB. Be sure to have swap space available!

getRedundancyPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.Path][source]

Get all paths providing redundancy.

This always includes partial redundancy, use getRedundancyPathsForKey() if you want to differentiate.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:Set[Path]
Raises:ValueError – If onlyType was given in the contructor, but metrics of another type of redundancy are to be returned here.
getRedundancyPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Models.Path]][source]

Get paths providing redundancy, keyed by the key element they provide redundancy for.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:
Return type:Dict[Element, Set[Path]]
Raises:ValueError – If onlyType was given in the contructor, but metrics of another type of redundancy are to be returned here.
getRedundancyRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of redundant keys to all keys.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:
Return type:float
Raises:ValueError – If onlyType was given in the contructor, but metrics of another type of redundancy are to be returned here.
getRedundantKeys(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Elements.Element][source]

Get redundant key elements.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:
Return type:Set[Element]
Raises:ValueError – If onlyType was given in the contructor, but metrics of another type of redundancy are to be returned here.
class FEV_KEGG.Robustness.Topology.Redundancy.RedundancyContribution(redundancy: FEV_KEGG.Robustness.Topology.Redundancy.Redundancy, specialKeys: Set[FEV_KEGG.Graph.Elements.Element])[source]

Bases: object

Contribution to redundancy, consisting of Flexibility and class:Robustness, accountable to edges with specialKeys.

Allows to answer the question how much certain key elements contribute to the flexibility/robustness of a graph.

Parameters:
  • redundancy (Redundancy) –
  • specialKeys (Set[Element]) – Set of key elements viewed to be somehow special. One type of special could be ‘neofunctionalised’.
Variables:
classmethod fromGraph(graph: FEV_KEGG.Graph.Models.DirectedMultiGraph, specialKeys: Set[FEV_KEGG.Graph.Elements.Element])[source]

Create RedundancyContribution object from graph.

Parameters:
Returns:
Return type:

RedundancyContribution
getContributedKeysForSpecial(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Elements.Element]][source]

Get keys for which a special key contributes to redundancy.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Sets of key elements which have a redundant path that contains a special key, keyed by the special key.
Return type:Dict[Element, Set[Element]]
Raises:ValueError – If onlyType was given in the contructor of the underlying redundancy object, but metrics of another type of redundancy are to be returned here.
getContributedPaths(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Set[FEV_KEGG.Graph.Models.MarkedPath][source]

Get all paths on which any special key contributes to redundancy.

This always includes partial redundancy, use getContributedPathsForKey() if you want to differentiate.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of marked redundant paths that contain a special key.
Return type:Set[MarkedPath]
Raises:ValueError – If onlyType was given in the contructor of the underlying redundancy object, but metrics of another type of redundancy are to be returned here.
getContributedPathsForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Models.MarkedPath]][source]

Get paths on which any special key contributes to redundancy, keyed by the key element they provide redundancy for.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation. For target-/source-flexibility, only the paths for target/source nodes are reported, paths of the respective other node are ignored.
Returns:Set of marked redundant paths that contain any special key, keyed by the key element they provide redundancy for.
Return type:Dict[Element, Set[MarkedPath]]
Raises:ValueError – If onlyType was given in the contructor of the underlying redundancy object, but metrics of another type of redundancy are to be returned here.
getContributingSpecialForKey(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → Dict[FEV_KEGG.Graph.Elements.Element, Set[FEV_KEGG.Graph.Elements.Element]][source]

Get special keys which contribute to redundancy of a key.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Sets of special key elements which contribute to a redundant path of a key, keyed by that key.
Return type:Dict[Element, Set[Element]]
Raises:ValueError – If onlyType was given in the contructor of the underlying redundancy object, but metrics of another type of redundancy are to be returned here.
getKeyContributionRatio(redundancyType: FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType = <RedundancyType.ROBUSTNESS: [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]>) → float[source]

Get ratio of contribution to keys’ redundancy, to all keys.

Parameters:redundancyType (RedundancyType) – Type of redundancy to use for computation.
Returns:Ratio of redundant keys which have a special key on at least one of their alternative paths.
Return type:float
Raises:ValueError – If onlyType was given in the contructor of the underlying redundancy object, but metrics of another type of redundancy are to be returned here.
class FEV_KEGG.Robustness.Topology.Redundancy.RedundancyType[source]

Bases: enum.Enum

Type of a redundancy.

Redundancy comes in many forms, some are defined here as constants pointing to their realising classes.

FLEXIBILITY = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 0]

Flexibility exists if the former substrates and/or products can still be metabolised via alternative paths, in their original respective direction. This does not mean the alternative paths have to include both, the orginal substrate and product, at the same time.

Type:If a key element is deleted from a graph, e.g. all enzymes realising a certain EC number are deleted from an organism’s genome
FLEXIBILITY_BOTH = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 2]

This combines the results of both FLEXIBILITY and FLEXIBILITY_PARTIAL.

FLEXIBILITY_PARTIAL = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 1]

This is the same as FLEXIBILITY, but only one of the edges of a key has to be redundant, not all its edges at once. This does not include the results of FLEXIBILITY!

ROBUSTNESS = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]

Robustness exists if the former substrates and products are still connected, in their original direction, albeit via alternative paths. This means the alternative paths have to include both, the orginal substrate and product, at the same time.

This means robustness is a sub-type of FLEXIBILITY. Only some flexible edges are also robust. Robustness and flexibility have an inheritance relation.

Type:If a key element is deleted from a graph, e.g. all enzymes realising a certain EC number are deleted from an organism’s genome
ROBUSTNESS_BOTH = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 2]

This combines the results of both ROBUSTNESS and ROBUSTNESS_PARTIAL.

ROBUSTNESS_PARTIAL = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 1]

This is the same as ROBUSTNESS, but only one of the edges of a key has to be redundant, not all its edges at once. This does not include the results of ROBUSTNESS!

SOURCE_FLEXIBILITY = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 6]

This is a super-type of FLEXIBILITY, where only the source node of each edge has to have redundant paths (leaving from it), for the whole edge to be counted as redundant. It does not matter whether the target node also has redundant paths. Only some source-flexible edges are also flexible, in fact exactly the ones which are also target-flexible. This means that combining target-flexibility with source-flexibility yields flexibility, they have a composition relation.

SOURCE_FLEXIBILITY_BOTH = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 8]

This combines the results of both SOURCE_FLEXIBILITY and SOURCE_FLEXIBILITY_PARTIAL.

SOURCE_FLEXIBILITY_PARTIAL = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 7]

This is the same as SOURCE_FLEXIBILITY, but only one of the edges of a key has to be redundant, not all its edges at once. This does not include the results of SOURCE_FLEXIBILITY!

TARGET_FLEXIBILITY = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 3]

This is a super-type of FLEXIBILITY, where only the target node of each edge has to have redundant paths (leading to it), for the whole edge to be counted as redundant. It does not matter whether the source node also has redundant paths. Only some target-flexible edges are also flexible, in fact exactly the ones which are also source-flexible. This means that combining target-flexibility with source-flexibility yields flexibility, they have a composition relation.

TARGET_FLEXIBILITY_BOTH = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 5]

This combines the results of both TARGET_FLEXIBILITY and TARGET_FLEXIBILITY_PARTIAL.

TARGET_FLEXIBILITY_PARTIAL = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Flexibility'>, 4]

This is the same as TARGET_FLEXIBILITY, but only one of the edges of a key has to be redundant, not all its edges at once. This does not include the results of TARGET_FLEXIBILITY!

default = [<class 'FEV_KEGG.Robustness.Topology.Redundancy.Robustness'>, 0]

Defaults to robustness, which is (currently) the most picky measure of redundancy. If you absolutely have to over-simplify the question of redundancy, use this default redundancy type. Robustness was chosen as default, because it seems wise not to break the graph when dealing with incomplete datasets. Which can only be prevented (to the extent of our knowledge) by using the more narrow definition of ‘robustness’, not the broader ‘flexibility’, because the difference of ‘flexibility’ minus ‘robustness’ leaves the cases where the graph breaks, but source and/or target are still redundant.

class FEV_KEGG.Robustness.Topology.Redundancy.Robustness(graph: FEV_KEGG.Graph.Models.DirectedMultiGraph, onlyLargestComponent=False)[source]

Bases: object

Robustness metrics for a graph.

If a key element is deleted from a graph, e.g. all enzymes (edges from substrate [edge source] to product [edge target]) realising a certain EC number (key) are deleted from an organism’s genome: ‘Robustness’ exists if the former edges’ sources and targets are (at least partially) still connected, in their original direction, albeit via alternative paths. This means the alternative paths have to include both, the orginal source and target, at the same time.

Parameters:
  • graph (DirectedMultiGraph) – The graph to be measured for its robustness.
  • onlyLargestComponent (bool, optional) – If True, reduce graph to its largest component before measuring robustness.
Variables:
  • self.redundantPathsForEdgeForKey (Dict[Element, Dict[Tuple[Element, Element], Set[Path]]]) – Each key element in graph pointing to a psuedo-set (dictionary.keys()) of its edges, represented by a tuple of both participating nodes. Each edge points to a set of paths, which would provide redundancy for this edge if it (or the whole key element) were to be removed.
  • self.sumKeys (int) – Sum of all individual key elements in graph.
  • self.sumBreakingKeys (int) – Sum of keys which cause the graph to break when removed, i.e. which have not a single edge with redundant paths between the same source and target nodes.
  • self.sumPartiallyRedundantKeys (int) – Sum of keys which, if removed, have redundant edges, but not all of them are redundant.
  • self.sumRedundantKeys (int) – Sum of keys which, if removed, have only redundant edges.
  • = 0 (self.sumEdges) – Sum of all edges in graph.
  • self.sumBreakingEdges (int) – Sum of edges which, if removed, cause the graph to break, because they are not redundant.
  • self.sumRedundantEdges (int) – Sum of edges which, if removed, still have other redundant edges between the same source and target nodes.
  • self.sumPaths (int) – Sum of all paths providing redundancy for edges.
  • self.partiallyRedundantKeyPathCounts (Dict[Element, int]) – Edge key element pointing to the number of redundant paths it can be replaced with, although only partially. This is possible if the edge key occurs in multiple edges connecting more than two different nodes.
  • self.redundantKeyPathCounts (Dict[Element, int]) – Edge key element pointing to the number of redundant paths it can be replaced with.
  • self.redundantEdgePathCounts (Dict[Tuple[Element, Element, Element], int]) – Full edge tuples including nodes AND the key element, pointing to the number of redundant paths it can be replaced with.
  • self.nonRedundantKeys (Set[Element]) – Set of key elements which cause the graph to break when removed, i.e. which have not a single edge with redundant paths between the same source and target nodes.
  • self.partiallyRedundantKeys (Set[Element]) – Set of key elements which, if removed, have redundant edges, but not all of them are redundant.
  • self.redundantKeys (Set[Element]) – Set of key elements which, if removed, have only redundant edges.
  • self.nonRedundantEdges (Set[Tuple[Element, Element, Element]]) – Set of edge tuples including nodes AND the key element, which cause the graph to break, because they have no redundant path.
  • self.redundantEdges (Set[Tuple[Element, Element, Element]]) – Set of edge tuples including nodes AND the key element, which have redundant paths.
  • self.paths (Set[Path]) – Set of all paths which act as redundancy for edges when a key has been removed.
  • self.partiallyRedundantKeyPaths (Dict[Element, Set[Path]]) – Edge key element pointing to the set of redundant paths it can be replaced with, although only partially. This is possible if the edge key occurs in multiple edges connecting more than two different nodes.
  • self.redundantKeyPaths (Dict[Element, Set[Path]]) – Edge key element pointing to the set of redundant paths it can be replaced with.
  • self.redundantEdgesRatio (float) – Ratio of the sum of redundant edges to the sum of all edges.
  • self.nonRedundantEdgesRatio (float) – Ratio of the sum of nonRedundant edges to the sum of all edges.
  • self.redundantKeysRatio (float) – Ratio of the sum of redundant key elements to the sum of all key elements.
  • self.partiallyRedundantKeysRatio (float) – Ratio of the sum of partially redundant key elements to the sum of all key elements.
  • self.nonRedundantKeysRatio (float) – Ratio of the sum of non-redundant key elements to the sum of all key elements.
classmethod fromClade(clade: FEV_KEGG.Evolution.Clade.Clade, majorityPercentage=None)[source]

Robustness metrics for a clade core metabolism.

Parameters:
  • clade (Clade) – The clade from which to extract the graph.
  • majorityPercentage (float, optional) – If None, use collective EC graph. If not None, use majority EC graph with majorityPercentage % majority.
Returns:
Return type:

Robustness
classmethod fromOrganismGroup(group: FEV_KEGG.KEGG.Organism.Group, majorityPercentage=None)[source]

Robustness metrics for a group core metabolism.

Parameters:
  • group (Organism.Group) – The group from which to extract the graph.
  • majorityPercentage (float, optional) – If None, use collective EC graph. If not None, use majority EC graph with majorityPercentage % majority.
Returns:
Return type:

Robustness
partiallyRedundantKeyPaths
partiallyRedundantKeys
redundantEdges
redundantKeyPaths
redundantKeys
class FEV_KEGG.Robustness.Topology.Redundancy.RobustnessContribution(robustness: FEV_KEGG.Robustness.Topology.Redundancy.Robustness, specialKeys: Set[FEV_KEGG.Graph.Elements.Element])[source]

Bases: object

Contribution to robustness accountable to edges with specialKeys.

Allows to answer the question how much certain key elements contribute to the robustness of a graph.

Parameters:
  • robustness (Robustness) –
  • specialKeys (Set[Element]) – Set of key elements viewed to be somehow special. One type of special could be ‘neofunctionalised’.
Variables:
  • self.robustness (Robustness) –
  • self.sumSpecialKeys (int) – Sum of special keys passed.
  • self.sumRedundantKeysWithSpecialKeyOnPaths (int) – Sum of redundant keys which have a special key on an alternative path.
  • self.sumPartiallyRedundantKeysWithSpecialKeyOnPaths (int) – Sum of partially redundant keys which have a special key on an alternative path.
  • self.sumPathsWithSpecialKeys (int) – Sum of alternative paths with a special key on it.
  • self.pathsWithSpecialKeys (Set[MarkedPath]) – Set of paths with special keys on them.
  • self.redundantKeySpecialKeysOnPaths (Dict[Element, Set[Element]]) – Sets of special keys which are on an alternative path of a redundant key, keyed by the key.
  • self.partiallyRedundantKeySpecialKeysOnPaths (Dict[Element, Set[Element]) – Sets of special keys which are on an alternative path of a partially redundant key, keyed by the key.
  • self.specialKeyOnRedundantKeysPaths (Dict[Element, Set[Element]]) – Sets of redundant keys which have an alternative path with a special key on it, keyed by the special key.
  • self.specialKeyOnPartiallyRedundantKeysPaths (Dict[Element, Set[Element]]) – Sets of partially redundant keys which have an alternative path with a special key on it, keyed by the special key.
  • self.pathsWithSpecialKeyRatio (float) – Ratio of the sum of paths with a special key on it to the sum of all paths.
  • self.redundantKeysWithSpecialKeyOnPathsRatio (float) – Ratio of the sum of redundant keys with a special key on its paths to the sum of all redundant keys.
  • self.partiallyRedundantKeysWithSpecialKeyOnPathsRatio (float) – Ratio of the sum of partially redundant keys with a special key on its paths to the sum of all partially redundant keys.
  • self.redundantKeyPathsWithSpecialKey (Dict[Element, Set[MarkedPath]]) – Redundant key element pointing to the set of marked redundant paths it can be replaced with, which contain a special key.
  • self.partiallyRedundantKeyPathsWithSpecialKey (Dict[Element, Set[MarkedPath]]) – Partially redundant key element pointing to the set of marked redundant paths it can be replaced with, which contain a special key.
FEV_KEGG.Robustness.Topology.Statistics module
Module contents
Module contents

FEV_KEGG.Statistics package

Submodules
FEV_KEGG.Statistics.Percent module
FEV_KEGG.Statistics.Percent.floatToPercentString(x, decimalPlaces=1)[source]

Format a float as a truncated percent string.

Parameters:
  • x (float) – Must be between 0 and 1 to represent 0% to 100%.
  • decimalPlaces (int, optional) – The number of decimal places to the right to conserve.
Returns:

String of x, shortened to decimalPlaces decimal places, concatenated with the ‘%’ sign.
Return type:

str
FEV_KEGG.Statistics.Percent.getPercent(x, baseValue)[source]

Calculate percentage.

Parameters:
  • x (float or int) –
  • baseValue (float or int) –
Returns:

Percentage of x out of baseValue, normalised to 100.
Return type:

float
FEV_KEGG.Statistics.Percent.getPercentSentence(x, baseValue, decimalPlaces=1)[source]

Calculate percentage and return shortened string within a fancy sentence.

Parameters:
  • x (float or int) –
  • baseValue (float or int) –
  • decimalPlaces (int, optional) – The number of decimal places to the right to conserve.
Returns:

String of result of getPercent(), shortened to decimalPlaces decimal places, and put into a complete sentence of the form “x/baseValue -> result%””, i.e. 23/42 -> 54.76%.
Return type:

str
FEV_KEGG.Statistics.Percent.getPercentString(x, baseValue)[source]

Calculate percentage and return as string.

Parameters:
  • x (float or int) –
  • baseValue (float or int) –
Returns:

String of result of getPercent().
Return type:

str
FEV_KEGG.Statistics.Percent.getPercentStringShort(x, baseValue, decimalPlaces=1)[source]

Calculate percentage and return as shortened string.

Parameters:
  • x (float or int) –
  • baseValue (float or int) –
  • decimalPlaces (int, optional) – The number of decimal places to the right to conserve.
Returns:

String of result of getPercent(), shortened to decimalPlaces decimal places.
Return type:

str
FEV_KEGG.Statistics.SequenceComparison module
FEV_KEGG.Statistics.SequenceComparison.getExpectationValue(bitScore: float, searchSequenceLength: int, foundSequenceLength: int, numberOfSequencesInDatabase: int) → float[source]

Returns the E-value of a single query in a sequence database.

Parameters:
  • bitScore (float) – Comparison score, normalised to base 2 (bits).
  • searchSequenceLength (int) – Length of the sequence that was the input of the query.
  • foundSequenceLength (int) – Length of the sequence that was the result of the query. If you have several results, run this function for each of them individually.
  • numberOfSequencesInDatabase (int) – Count of all sequences that could have potentially be found. For example, a search in all genes of eco would mean the count of all sequenced genes for eco -> numberOfSequencesInDatabase = 4,498. A search in all organisms, however, would mean the count of all sequenced genes in KEGG -> numberOfSequencesInDatabase = 25,632,969.
Returns:

Statistical E-value (expectation value) for the occurence of a match of the same confidence with a totally unrelated, e.g. random, sequence.
Return type:

float
FEV_KEGG.Statistics.SequenceComparison.isMatchSignificant(bitScore: float, searchSequenceLength: int, foundSequenceLength: int, numberOfSequencesInDatabase: int, significanceThreshold: float = 1e-15) → bool[source]

Check if a sequence match is significant.

Calculates E-value, using getExpectationValue(). If E-value is smaller than significanceThreshold, match is significant, return True.

Parameters:
  • bitScore (float) – Comparison score, normalised to base 2 (bits).
  • searchSequenceLength (int) – Length of the sequence that was the input of the query.
  • foundSequenceLength (int) – Length of the sequence that was the result of the query. If you have several results, run this function for each of them individually.
  • numberOfSequencesInDatabase (int) – Count of all sequences that could have potentially be found. For example, a search in all genes of eco would mean the count of all sequenced genes for eco -> numberOfSequencesInDatabase = 4,498. A search in all organisms, however, would mean the count of all sequenced genes in KEGG -> numberOfSequencesInDatabase = 25,632,969.
  • significanceThreshold (float, optional) – Threshold of E-value below which to consider a match significant.
Returns:

Whether a sequence match is significant.
Return type:

bool
Module contents

FEV_KEGG.UnitTest package

Submodules
FEV_KEGG.UnitTest.collectiveEnzymeGraphByEcConsensus module

A unit test for the creation of collective enzyme graphs by using an EC consensus.

Two methods of doing so are compared and must always return the same value. At last, the identity of included enzymes is compared, which must result in 0.

Warning

The first result is time-dependant! It will certainly change on future updates of KEGG. However, it should be somewhere around 87.

class FEV_KEGG.UnitTest.collectiveEnzymeGraphByEcConsensus.Test(methodName='runTest')[source]

Bases: unittest.case.TestCase

Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

test_consensusEcGraph_difference()[source]
FEV_KEGG.UnitTest.collectiveEnzymeGraphByEcMajority module

A unit test for the creation of collective enzyme graphs by using an EC majority.

Two methods of doing so are compared and must always return the same value. At last, the identity of included enzymes is compared, which must result in 0.

Warning

The first result is time-dependant! It will certainly change on future updates of KEGG. However, it should be somewhere around 184.

class FEV_KEGG.UnitTest.collectiveEnzymeGraphByEcMajority.Test(methodName='runTest')[source]

Bases: unittest.case.TestCase

Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

test_majorityEcGraph_difference()[source]
Module contents

FEV_KEGG.Util package

Submodules
FEV_KEGG.Util.Parallelism module
FEV_KEGG.Util.Parallelism.enableShallCancelThreads()[source]

Set the global flag for cancelling all threads to “cancelling”.

FEV_KEGG.Util.Parallelism.getNumberOfThreadsDownload(isSSDB=False)[source]

Number of threads allowed for downloading.

Depends on whether this function is executed inside a process pool, because all processes will have to share the total number of allowed download threads, in order not to exceed it.

Parameters:isSSDB (bool. optional) – IF True, uses a lower number of threads, because KEGG SSDB can not handle too many parallel connections.
Returns:The number of allowed threads for downloading.
Return type:int
FEV_KEGG.Util.Parallelism.getNumberOfThreadsFile()[source]

Number of thread allowed for file access.

Depends on whether this function is executed inside a process pool, because all processes will have to share the total number of allowed file access threads, in order not to exceed it.

Returns:The number of allowed threads for file access.
Return type:int
FEV_KEGG.Util.Parallelism.getShallCancelThreads()[source]

Get the global flag for cancelling all threads.

Returns:Whether all tasks currently running in threads of this process shall abort and return early.
Return type:bool
FEV_KEGG.Util.Parallelism.getTqdmPosition()[source]

Get position where this process’ progress bar shall be printed.

Interprets current process’ name as the index for positioning its tqdm progress bar alongside the progress bar of all other processes.

Returns:Position index of this process’ progress bar, to be used by tqdm.
Return type:int

Note

This function depends on the naming of processes of your OS! You might have to replace this function to get clean positioning of progress bars.

FEV_KEGG.Util.Parallelism.isMainProcess()[source]

Check if this is running in the main process.

Returns:True if this is the main process (any thread), False if not.
Return type:bool
FEV_KEGG.Util.Parallelism.isMainThread()[source]

Check if this is running in the main thread.

Returns:True if this is the main thread (of any process), False if not.
Return type:bool
FEV_KEGG.Util.Parallelism.isMainThreadInMainProcess()[source]

Check if this is running in the main thread of the main process.

Returns:True if this is the main thread of the main process, False if not.
Return type:bool
FEV_KEGG.Util.Parallelism.keyboardInterruptHandler(processPoolFutures=None, threadPool=None, threadPoolFutures=None, silent=False, terminateProcess=False)[source]

Handle KeyboardInterrupt.

Tries to consistently handle KeyboardInterrupt in all current implementations of parallel computation. If this is inside a background process, cancel threadPool tasks, running and scheduled (if listed inside threadPoolFutures). If this is inside the main process, also cancel processPoolFutures and shut down the global process pool itself. May also exit this very process, if terminateProcess == True.

Parameters:
  • processPoolFutures (Iterable, optional) – An Iterable of all Future currently scheduled in the process pool.
  • threadPool (ThreadPoolExecutor, optional) – The thread pool currently running within the main process. This pool usually handles the process pool’s results in a parallel manner.
  • threadPoolFutures (Iterable, optional) – The Iterable of all Future currently scheduled in the threadPool.
  • silent (bool, optional) – If True, prints messages of the current state of handling the interrupt.
  • terminateProcess (bool, optional) – If True, calls sys.exit() on this very process, at the end of this function.

Warning

Only ever call this from main thread (in any process)! Else, you might get unexpected and dangerous behaviour!

Note

terminateProcess is useful to cancel tasks already scheduled inside the call_queue of the pool, because there is no method to empty this queue and cancel already scheduled tasks. Keep in mind that this queue is always populated with p + 1 tasks, while p (different) tasks are being executed, with p being the number of processes in the pool. However, this only works as long as ProcessPoolExecutor does not re-create broken processes!

FEV_KEGG.Util.Parallelism.printBelowProgress(message)[source]

Does a print() beneath any progress bars.

Simply prints as many newlines as there are processes in use by the process pool. Finally, prints the message.

Parameters:message (str) – Message to be printed below any progress bars.

Note

This is an indirect measure of currently possibly rendered progress bars, at best! There is no check if the possible progress bars are actually rendered. Therefore, a surplus of empty lines may appear, or there may not be enough.

FEV_KEGG.Util.Parallelism.processPool = <FEV_KEGG.lib.Python.concurrent.futures.InterruptibleProcessPoolExecutor object>

The global process pool.

If you want to run FEV@KEGG inside another thread or process, your will have to replace this with a concurrent.futures.Executor of your choice.

See also

startProcessPool
Default creator of a process pool.
FEV_KEGG.Util.Parallelism.resetShallCancelThreads()[source]

Reset the global flag for cancelling all threads to “not cancelling”.

FEV_KEGG.Util.Parallelism.shallCancelThreads = False

Allows threads to be canceled in a timely manner, across the whole process.

Specifically, any task currently running in a thread of this process can check this variable to see whether it is supposed to abort and return early.

Note

This is necessary because concurrent.futures.ThreadPoolExecutor does not have support for neither pre-emptively aborting tasks (call_queue) nor emptying the pending task queue (pending_work_items).

FEV_KEGG.Util.Parallelism.startProcessPool()[source]

Creates the process pool and stores it in processPool.

You might not want this when you already run your own concurrent.futures.Executor. If you run your own, let processPool point to it.

See also

FEV_KEGG.lib.Python.concurrent.futures.InterruptibleProcessPoolExecutor()
Our own executor used as a process pool, because it handles KeyboardInterrupt nicer than the default implementation.

Note

A process pool will only work from within the main thread in the main process of your application. If you want to run FEV@KEGG inside another thread or process, your will have to replace processPool with a concurrent.futures.Executor that allows running outside the main thread. This may be a dummy class.

FEV_KEGG.Util.Util module
FEV_KEGG.Util.Util.chunks(iterable, chunk_size)[source]

Chops Iterable into chunks.

Parameters:
  • iterable (Iterable) – The Iterable object to be chunked.
  • chunk_size (int) – The size if each chunk. Except for the last, of course.
Yields:

Iterable – Iterable of the same type as iterable, but with length chunk_size. Except for the last, of course.
FEV_KEGG.Util.Util.deduplicateList(anyList: List[T], preserveOrder=False)[source]

Deduplicates a list.

Does not preserve order by default, because it is faster.

Parameters:
  • anyList (list) – The list to be deduplicated.
  • preserveOrder (bool, optional) – If True, preserves order of elements in the list.
Returns:

A new list, containing all elements of anyList, but only once.
Return type:

List
FEV_KEGG.Util.Util.dictToHtml(dictionary, byValueFirst=False, addEcDescriptions=False, headingDescriptionForHeading=None) → str[source]
FEV_KEGG.Util.Util.dictToHtmlFile(dictionary, file, byValueFirst=False, inCacheFolder=False, addEcDescriptions=False, headingDescriptionForHeading=None)[source]
Parameters:
  • file (str) – Path and name of the exported file. See inCacheFolder.
  • inCacheFolder (bool, optional) – If True, interpret file relative to the cache folder. See FEV_KEGG.settings.cachePath. If False, interpret file relative to the current working directory.
FEV_KEGG.Util.Util.inverseDictKeepingAllKeys(dictionary) → Dict[KT, VT][source]
FEV_KEGG.Util.Util.prettySortDict(dictionary, byValueFirst=False) → List[Tuple][source]
FEV_KEGG.Util.Util.updateDictUpdatingValue(dictA, dictB)[source]

Update dictA using dictB. However, if key already exists in dictA, does not overwrite dictA[key] with dictB[key], as the defautl update() function does, instead does an update: dictA[key].update( dictB[key] ).

Warning

Only works if dictA’s values have an update() function, e.g. are sets!

Module contents

FEV_KEGG.lib package

Subpackages
FEV_KEGG.lib.Biopython package
Subpackages
FEV_KEGG.lib.Biopython.KEGG package
Subpackages
FEV_KEGG.lib.Biopython.KEGG.KGML package
Submodules
FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_parser module

Classes and functions to parse a KGML pathway map.

The KGML pathway map is parsed into the object structure defined in KGML_Pathway.py in this module.

Classes:
  • KGMLParser - Parses KGML file
Functions:
  • read - Returns a single Pathway object, using KGMLParser internally
class FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_parser.KGMLParser(elem)[source]

Bases: object

Parses a KGML XML Pathway entry into a Pathway object.

Example: Read and parse large metabolism file

>>> from FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_parser import read
>>> pathway = read(open('KEGG/ko01100.xml', 'r'))
>>> print(len(pathway.entries))
3628
>>> print(len(pathway.reactions))
1672
>>> print(len(pathway.maps))
149

>>> pathway = read(open('KEGG/ko00010.xml', 'r'))
>>> print(pathway) #doctest: +NORMALIZE_WHITESPACE
Pathway: Glycolysis / Gluconeogenesis
KEGG ID: path:ko00010
Image file: http://www.kegg.jp/kegg/pathway/ko/ko00010.png
Organism: ko
Entries: 99
Entry types:
    ortholog: 61
    compound: 31
    map: 7

Initialize the class.

parse()[source]

Parse the input elements.

FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_parser.parse(handle)[source]

Return an iterator over Pathway elements.

Parameters:handle - file handle to a KGML file for parsing, or a KGML string (-) –

This is a generator for the return of multiple Pathway objects.

FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_parser.read(handle)[source]

Parse a single KEGG Pathway from given file handle.

Returns a single Pathway object. There should be one and only one pathway in each file, but there may well be pathological examples out there.

FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway module

Classes to represent a KGML Pathway Map.

The KGML definition is as of release KGML v0.7.1 (http://www.kegg.jp/kegg/xml/docs/)

Classes:
  • Pathway - Specifies graph information for the pathway map
  • Relation - Specifies a relationship between two proteins or KOs, or protein and compound. There is an implied direction to the relationship in some cases.
  • Reaction - A specific chemical reaction between a substrate and a product.
  • Entry - A node in the pathway graph
  • Graphics - Entry subelement describing its visual representation
class FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Component(parent)[source]

Bases: object

An Entry subelement used to represents a complex node.

A subelement of the Entry element, used when the Entry is a complex node, as described in release KGML v0.7.1 (http://www.kegg.jp/kegg/xml/docs/)

The Component acts as a collection (with type ‘group’, and typically its own Graphics subelement), having only an ID.

element

Return the Component as a valid KGML element.

id

The pathway graph node ID for the Entry

class FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Entry[source]

Bases: object

Represent an Entry from KGML.

Each Entry element is a node in the pathway graph, as described in release KGML v0.7.1 (http://www.kegg.jp/kegg/xml/docs/)

Variables:
  • id - The ID of the entry in the pathway map (-) –
  • names - List of KEGG IDs for the entry (-) –
  • type - The type of the entry (-) –
  • link - URL of information about the entry (-) –
  • reaction - List of KEGG IDs of the corresponding reactions (-) – (integer)
  • graphics - List of Graphics objects describing the Entry's visual (-) – representation
  • components - List of component node ID for this Entry (-) –
  • alt - List of alternate names for the Entry (-) –

NOTE: The alt attribute represents a subelement of the substrate and product elements in the KGML file

__str__()[source]

Return readable descriptive string.

add_component(element)[source]

Add an element to the entry.

If the Entry is already part of a pathway, make sure the component already exists.

add_graphics(entry)[source]

Add the Graphics entry.

bounds

Coordinate bounds for all Graphics elements in the Entry.

Return the [(xmin, ymin), (xmax, ymax)] co-ordinates for the Entry Graphics elements.

element

Return the Entry as a valid KGML element.

id

The pathway graph node ID for the Entry.

is_reactant

Does this Entry participate in any reaction in parent pathway?

Returns True if the Entry participates in any reaction of its parent Pathway

name

List of KEGG identifiers for the Entry.

reaction

List of reaction KEGG IDs for this Entry.

remove_component(value)[source]

Remove the entry with the passed ID from the group.

remove_graphics(entry)[source]

Remove the Graphics entry with the passed ID from the group.

class FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Graphics(parent)[source]

Bases: object

An Entry subelement used to represents the visual representation.

A subelement of Entry, specifying its visual representation, as described in release KGML v0.7.1 (http://www.kegg.jp/kegg/xml/docs/)

Variables:
  • name Label for the graphics object (-) –
  • x X-axis position of the object (-) –
  • y Y-axis position of the object (-) –
  • coords polyline co-ordinates, list of (-) –
  • type object shape (-) –
  • width object width (-) –
  • height object height (-) –
  • fgcolor object foreground color (-) –
  • bgcolor object background color (-) –

Some attributes are present only for specific graphics types. For example, line types do not (typically) have a width. We permit non-DTD attributes and attribute settings, such as

dash List of ints, describing an on/off pattern for dashes

bgcolor

Background color.

bounds

Coordinate bounds for the Graphics element.

Return the bounds of the Graphics object as an [(xmin, ymin), (xmax, ymax)] tuple. Co-ordinates give the centre of the circle, rectangle, roundrectangle elements, so we have to adjust for the relevant width/height.

centre

Return the centre of the Graphics object as an (x, y) tuple.

coords

Polyline coordinates for the graphics element.

element

Return the Graphics as a valid KGML element.

fgcolor

Foreground color.

height

The height of the graphics element.

width

The width of the graphics element.

x

The X coordinate for the graphics element.

y

The Y coordinate for the graphics element.

class FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Pathway[source]

Bases: object

Represents a KGML pathway from KEGG.

Specifies graph information for the pathway map, as described in release KGML v0.7.1 (http://www.kegg.jp/kegg/xml/docs/)

Variables:
  • name - KEGGID of the pathway map (-) –
  • org - ko/ec/[org prefix] (-) –
  • number - map number (-) –
  • title - the map title (-) –
  • image - URL of the image map for the pathway (-) –
  • link - URL of information about the pathway (-) –
  • entries - Dictionary of entries in the pathway, keyed by node ID (-) –
  • reactions - Set of reactions in the pathway (-) –

The name attribute has a restricted format, so we make it a property and enforce the formatting.

The Pathway object is the only allowed route for adding/removing Entry, Reaction, or Relation elements.

Entries are held in a dictionary and keyed by the node ID for the pathway graph - this allows for ready access via the Reaction/Relation etc. elements. Entries must be added before reference by any other element.

Reactions are held in a dictionary, keyed by node ID for the path. The elements referred to in the reaction must be added before the reaction itself.

__str__()[source]

Returns a readable summary description string.

add_entry(entry)[source]

Add an Entry element to the pathway.

add_reaction(reaction)[source]

Add a Reaction element to the pathway.

add_relation(relation)[source]

Add a Relation element to the pathway.

bounds

Coordinate bounds for all Graphics elements in the Pathway.

Returns the [(xmin, ymin), (xmax, ymax)] coordinates for all Graphics elements in the Pathway

compounds

Get a list of entries of type compound.

element

Return the Pathway as a valid KGML element.

genes

Get a list of entries of type gene.

get_KGML()[source]

Return the pathway as a string in prettified KGML format.

maps

Get a list of entries of type map.

name

The KEGGID for the pathway map.

number

The KEGG map number.

orthologs

Get a list of entries of type ortholog.

reaction_entries

List of entries corresponding to each reaction in the pathway.

reactions

Get a list of reactions in the pathway.

relations

Get a list of relations in the pathway.

remove_entry(entry)[source]

Remove an Entry element from the pathway.

remove_reaction(reaction)[source]

Remove a Reaction element from the pathway.

remove_relation(relation)[source]

Remove a Relation element from the pathway.

class FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Reaction[source]

Bases: object

A specific chemical reaction with substrates and products.

This describes a specific chemical reaction between one or more substrates and one or more products.

Variables:
  • id Pathway graph node ID of the entry (-) –
  • names List of KEGG identifier (-) –
  • type String (-) – reversible or irreversible
  • substrate Entry object of the substrate (-) –
  • product Entry object of the product (-) –
__str__()[source]

Return an informative human-readable string.

add_product(product_id)[source]

Add a product, identified by its node ID, to the reaction.

add_substrate(substrate_id)[source]

Add a substrate, identified by its node ID, to the reaction.

element

Return KGML element describing the Reaction.

entry

Return the Entry corresponding to this reaction.

id

Node ID for the reaction.

name

List of KEGG identifiers for the reaction.

products

Return list of product Entry elements.

reactant_ids

Return a list of substrate and product reactant IDs.

substrates

Return list of substrate Entry elements.

class FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway.Relation[source]

Bases: object

A relationship between to products, KOs, or protein and compound.

This describes a relationship between two products, KOs, or protein and compound, as described in release KGML v0.7.1 (http://www.kegg.jp/kegg/xml/docs/)

Variables:
  • entry1 - The first Entry object node ID defining the (-) – relation (int)
  • entry2 - The second Entry object node ID defining the (-) – relation (int)
  • type - The relation type (-) –
  • subtypes - List of subtypes for the relation, as a list of (-) – (name, value) tuples
__str__()[source]

A useful human-readable string.

element

Return KGML element describing the Relation.

entry1

Entry1 of the relation.

entry2

Entry2 of the relation.

FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway._as_string(s)

Turn byte string or unicode string into a unicode string.

FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway._as_unicode(s)[source]

Turn byte string or unicode string into a unicode string.

FEV_KEGG.lib.Biopython.KEGG.KGML.KGML_pathway._is_int_or_long(i)[source]

Check if the value is an integer.

Note there are no longs on Python 3.

Module contents

Code to work with data from the KEGG database.

References: Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 29-34 (2000).

URL: http://www.genome.ad.jp/kegg/

Submodules
FEV_KEGG.lib.Biopython.KEGG.REST module

Provides code to access the REST-style KEGG online API.

This module aims to make the KEGG online REST-style API easier to use. See: https://www.kegg.jp/kegg/rest/keggapi.html

The KEGG REST-style API provides simple access to a range of KEGG databases. This works using simple URLs (which this module will construct for you), with any errors indicated via HTTP error levels.

The functionality is somewhat similar to Biopython’s Bio.TogoWS and Bio.Entrez modules.

Currently KEGG does not provide any usage guidelines (unlike the NCBI whose requirements are reasonably clear). To avoid risking overloading the service, Biopython will only allow three calls per second.

References: Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 29-34 (2000).

FEV_KEGG.lib.Biopython.KEGG.REST._binary_to_string_handle(handle)[source]

Treat a binary (bytes) handle like a text (unicode) handle.

FEV_KEGG.lib.Biopython.KEGG.REST.kegg_conv(target_db, source_db, option=None, timeout=None)[source]

KEGG conv - convert KEGG identifiers to/from outside identifiers

target_db - Target database source_db_or_dbentries - source database or database entries option - Can be “turtle” or “n-triple” (string).

FEV_KEGG.lib.Biopython.KEGG.REST.kegg_find(database, query, option=None, timeout=None)[source]

KEGG find - Data search.

Finds entries with matching query keywords or other query data in a given database.

db - database or organism (string) query - search terms (string) option - search option (string), see below.

For the compound and drug database, set option to the string ‘formula’, ‘exact_mass’ or ‘mol_weight’ to search on that field only. The chemical formula search is a partial match irrespective of the order of atoms given. The exact mass (or molecular weight) is checked by rounding off to the same decimal place as the query data. A range of values may also be specified with the minus(-) sign.

FEV_KEGG.lib.Biopython.KEGG.REST.kegg_get(dbentries, option=None, timeout=None)[source]

KEGG get - Data retrieval.

dbentries - Identifiers (single string, or list of strings), see below. option - One of “aaseq”, “ntseq”, “mol”, “kcf”, “image”, “kgml” (string)

The input is limited up to 10 entries. The input is limited to one pathway entry with the image or kgml option. The input is limited to one compound/glycan/drug entry with the image option.

Returns a handle.

FEV_KEGG.lib.Biopython.KEGG.REST.kegg_info(database, timeout=None)[source]

KEGG info - Displays the current statistics of a given database.

db - database or organism (string)

The argument db can be a KEGG database name (e.g. ‘pathway’ or its official abbreviation, ‘path’), or a KEGG organism code or T number (e.g. ‘hsa’ or ‘T01001’ for human).

A valid list of organism codes and their T numbers can be obtained via kegg_info(‘organism’) or https://rest.kegg.jp/list/organism

KEGG link - find related entries by using database cross-references.

target_db - Target database source_db_or_dbentries - source database option - Can be “turtle” or “n-triple” (string).

FEV_KEGG.lib.Biopython.KEGG.REST.kegg_list(database, org=None, timeout=None)[source]

KEGG list - Entry list for database, or specified database entries.

db - database or organism (string) org - optional organism (string), see below.

For the pathway and module databases the optional organism can be used to restrict the results.

Module contents
Module contents

Code from Biopython, copied because the whole import would have been unnecessarily big.

The code was changed in some spots to enable it to run independently. Also, the timeout parameter of the underlying socket was exposed.

Note

Biopython is currently released under the “Biopython License Agreement” (given in full below). Unless stated otherwise in individual file headers, all Biopython’s files are under the “Biopython License Agreement”.

Some files are explicitly dual licensed under your choice of the “Biopython License Agreement” or the “BSD 3-Clause License” (both given in full below). This is with the intention of later offering all of Biopython under this dual licensing approach.

Biopython License Agreement

Permission to use, copy, modify, and distribute this software and its documentation with or without modifications and for any purpose and without fee is hereby granted, provided that any copyright notices appear in all copies and that both those copyright notices and this permission notice appear in supporting documentation, and that the names of the contributors or copyright holders not be used in advertising or publicity pertaining to distribution of the software without specific prior permission.

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FEV_KEGG.lib.Python package
Subpackages
FEV_KEGG.lib.Python.concurrent package
Submodules
FEV_KEGG.lib.Python.concurrent.futures module
class FEV_KEGG.lib.Python.concurrent.futures.InterruptibleProcessPoolExecutor(max_workers=None, mp_context=None, initializer=None, initargs=())[source]

Bases: concurrent.futures.process.ProcessPoolExecutor

This class inherits from concurrent.futures.ProcessPoolExecutor and only replaces the worker function which pulls work items from the call_queue and reports their results back on the result_queue. A KeyboardInterrupt can be caught during execution of the work item, but not when the next work item is being pulled from the call_queue! A KeyboardInterrupt stack trace is printed and the process dies. This class catches a KeyboardInterrupt during call_queue-pulling and causes the current process (one within the pool) to sys.exit() immediately, without printing a KeyboardInterrupt stack trace. Per default, sys.exit() does not cause a stack trace print.

Initializes a new ProcessPoolExecutor instance.

Parameters:
  • max_workers – The maximum number of processes that can be used to execute the given calls. If None or not given then as many worker processes will be created as the machine has processors.
  • mp_context – A multiprocessing context to launch the workers. This object should provide SimpleQueue, Queue and Process.
  • initializer – A callable used to initialize worker processes.
  • initargs – A tuple of arguments to pass to the initializer.
FEV_KEGG.lib.Python.concurrent.futures.process_worker(call_queue, result_queue)[source]

A copy of Python’s process_worker function in concurrent.futures.ProcessPoolExecutor.

This copy was changed to not die on KeyboardInterrupt, but to exit gracefully. Also, no traceback is printed upon NoKnownPathwaysError or CancelledError.

Note

Copyright © 2001-2018 Python Software Foundation; All Rights Reserved

Module contents
Module contents

Code from Python, copied because of some small changes in behaviour of ProcessPoolExecutor.

Note

PSF LICENSE AGREEMENT FOR PYTHON 3.4.6

  1. This LICENSE AGREEMENT is between the Python Software Foundation (“PSF”), and the Individual or Organization (“Licensee”) accessing and otherwise using Python 3.4.6 software in source or binary form and its associated documentation.
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Module contents

This package contains code copied from other projects, because either parts of it were changed, or the original import would have been unnecessarily big.

Submodules

FEV_KEGG.quirks module

Sometimes, things do not work as expected. This is when quirk workarounds save the day.

Warning

These quirks are highly time-specific, they can change any moment! Be sure to re-evaluate the workarounds regularly.

FEV_KEGG.quirks.METABOLIC_PATHWAYS = ['01100', '01110', '01120', '01130', '01200', '01210', '01212', '01230', '01220', '00010', '00020', '00030', '00040', '00051', '00052', '00053', '00500', '00520', '00620', '00630', '00640', '00650', '00660', '00562', '00190', '00195', '00196', '00710', '00720', '00680', '00910', '00920', '00061', '00062', '00071', '00072', '00073', '00100', '00120', '00121', '00140', '00561', '00564', '00565', '00600', '00590', '00591', '00592', '01040', '00230', '00240', '00250', '00260', '00270', '00280', '00290', '00300', '00310', '00220', '00330', '00340', '00350', '00360', '00380', '00400', '00410', '00430', '00440', '00450', '00460', '00471', '00472', '00473', '00480', '00510', '00513', '00512', '00515', '00514', '00532', '00534', '00533', '00531', '00563', '00601', '00603', '00604', '00540', '00550', '00511', '00730', '00740', '00750', '00760', '00770', '00780', '00785', '00790', '00670', '00830', '00860', '00130', '00900', '00902', '00909', '00904', '00906', '00905', '00981', '00908', '00903', '00281', '01052', '00522', '01051', '01059', '01056', '01057', '00253', '00523', '01054', '01053', '01055', '00940', '00945', '00941', '00944', '00942', '00943', '00901', '00403', '00950', '00960', '01058', '00232', '00965', '00966', '00402', '00311', '00332', '00261', '00331', '00521', '00524', '00525', '00231', '00401', '00404', '00405', '00333', '00254', '00362', '00627', '00364', '00625', '00361', '00623', '00622', '00633', '00642', '00643', '00791', '00930', '00351', '00363', '00621', '00626', '00624', '00365', '00984', '00980', '00982', '00983', '00970']

KEGG PATHWAY does not provide a reliable naming convention for pathways which are part of metabolism and actually do contain ‘Compounds’ and Enzymes/Genes.

This is the list of all pathway names which currently provide usable information about metabolism.

Warning

It may change any time! Compare with KEGG PATHWAY to see whether you want to categorise different pathways as ‘metabolic’.

FEV_KEGG.quirks.NON_EXISTING_ORGANISMS = ['lni', 'scla', 'pavl', 'our', 'rox', 'dei', 'miq', 'phz', 'mela', 'simp', 'grs', 'deo', 'mdv', 'hag', 'ema', 'pset', 'stro', 'bmur', 'malk', 'lyb', 'ptc', 'pamg', 'vit', 'syo', 'thas', 'paih', 'otk', 'laca', 'pio', 'fsa', 'lcy', 'mgg', 'psai', 'bzg', 'cbae', 'git', 'aue', 'mbas', 'kit', 'vdb', 'aid', 'smur', 'phr', 'melm', 'mee']

Some organisms in KEGG supposedly exist, but when retrieved, their data returns empty, which raises an Error.

Warning

Today, some organisms might be in this list without reason, others might be missing. Please try to fetch the organisms in this list by executing

org = FEV_KEGG.Organism.Organism('lni')
org.getPathways()

If this fails, then lni still belongs in this list.

FEV_KEGG.settings module

Settings used across the application.

FEV_KEGG.settings.automaticallyStartProcessPool = True

Whether a pool of processes should automatically spin up.

You will want this False if:

  • you import FEV_KEGG inside a background thread or a child process only, because starting a process pool only works from within the main thread of the main process OR
  • you already have other means of providing parallelism OR
  • you want to save on the rather big overhead of spinning up, using, and tearing down processes. Especially when you import FEV_KEGG without actually using the process pool, e.g. when using something like Sphinx with autodoc.

If you do have this False, you will have to either:

  • run FEV_KEGG.startProcessPool(). You should do this as early as possible, because your whole main process will be copied, including all the RAM it hitherto occupied. Will only work within the main thread of the main process OR
  • replace FEV_KEGG.Util.Parallelism.processPool with a concurrent.futures.Executor of your choice, or else some functions will fail and raise an error, especially in FEV_KEGG.KEGG.Organism.Group. The object may be a dummy, as long as it adheres to the interface and successfully works on tasks.

You will want this True if:

  • you import FEV_KEGG in your main thread of the main process only AND
  • you want to use functions utilising parallelism in the process pool, especially in FEV_KEGG.KEGG.Organism.Group AND
  • you rarely import without actually using the process pool, because spinning up and tearing down processes can take several seconds.

See also

FEV_KEGG.Util.Parallelism.startProcessPool
Spins up a pool of processes. No further setup required.
FEV_KEGG.settings.cachePath = '/home/docs/.cache/FEV-KEGG'

File system path for the cache directory.

This directory is used for caching downloads and calculations. It is automatically set depending on your OS’s default cache folder.

See also

Caching
Readmy entry explaining caching in general.
FEV_KEGG.settings.defaultEvalue = 1e-15

Default threshold for the statistical expectation value (E-value), below which a sequence alignment is considered significant. This can usually be overwritten for a whole module, or in a function’s parameters.

FEV_KEGG.settings.defaultNoMultifunctional = True

Whether to exclude multifunctional enzymes from analysis. This is useful to exclude complex cases of multi-domain enzymes and known promiscuous enzymes.

FEV_KEGG.settings.defaultOneOrganismPerSpecies = True

Whether to use only one organism per species in a taxonomy. This is useful to reduce overrepresentation of species with many sequenced genomes in a group.

FEV_KEGG.settings.downloadThreads = 32

Number of threads to download with at once.

Depends on the speed of your internet connection.

Warning

Should only be used inside the main process. Else, the total number of download threads will multiply by the number of available processors!

FEV_KEGG.settings.downloadThreadsPerProcess = 16

Number of threads to download with at once, divided by the number of available processors.

Should be used inside background processes. Depends on your computer.

FEV_KEGG.settings.downloadThreadsPerProcessSSDB = 6

Number of threads to download with at once from KEGG SSDB, divided by the number of available processors.

Should be used inside background processes. Depends on your computer.

FEV_KEGG.settings.downloadThreadsSSDB = 12

Number of threads to download with at once from KEGG SSDB.

Depends on the speed of your internet connection. Also depends on SSDB, because this part of KEGG can obviously withstand far fewer parallel connections. If you get frequent HTTP 403 Forbidden errors, despite of retrying upon such errors, lower this value until the progress bar moves smoothly.

Warning

Should only be used inside the main process. Else, the total number of download threads will multiply by the number of available processors!

FEV_KEGG.settings.downloadTimeout = 60

Time in seconds after which a blocking socket is considered failed.

Should be well below retryDownloadMax, or else you will not retry at all.

FEV_KEGG.settings.downloadTimeoutSocket = 30

Quirks for downloadTimeout in Python 3.4 (and maybe above).

For some reason, in Python 3.4, sockets double the timeout value passed to them.

FEV_KEGG.settings.fileThreads = 8

Number of threads to access files with at once.

Depends on the speed of your data storage.

Warning

Should only be used inside the main process. Else, the total number of file threads will multiply by the number of available processors!

FEV_KEGG.settings.fileThreadsPerProcess = 4

Number of threads to acces files with at once, divided by the number of available processors.

Should be used inside background processes. Depends on your computer.

FEV_KEGG.settings.organismInfoExpiration = 86400

Seconds after which an organism info file is considered outdated. This can be useful when relying upon a current database size for calculating E-values for a FEV_KEGG.KEGG.SSDB.Match.

FEV_KEGG.settings.printElementUrl = False

If True, when a Graph.Elements.Element is returned in its string representation, append its URL to KEGG. This can quickly overencumber output!

FEV_KEGG.settings.processes = 2

Number of processes to calculate with.

Depends on your computer. Defaults to the number of logical CPU cores, or if unretrievable, to 1.

Warning

Processes have much more overhead than threads.

FEV_KEGG.settings.retryDownloadBackoffFactor = 1000

Factor in milliseconds for exponential backoff.

The backoff function waits 2^x * retryDownloadBackoffFactor milliseconds between retries, where x is the count of tries already failed.

FEV_KEGG.settings.retryDownloadBackoffMax = 10000

Maximum time between two retries, which the exponential backoff function can not exceed.

FEV_KEGG.settings.retryDownloadMax = 60000

Maximum total time in milliseconds a download should be retried before giving up.

Warning

Giving up usually throws an error and halts the whole program!

FEV_KEGG.settings.verbosity = 1

Verbosity of the output on the console.

0 = no unecessary output, only errors. 1 = informative output, including progess for long-running tasks. 2 = including short description of the process shown as a progress bar, e.g. ‘Calculating redundancy…’ 3 = debug output, including whether a file is downloaded or already in cache.

Module contents

FEV_KEGG.startProcessPool()[source]

Shortcut for starting the process pool for parallel computation.

See also

FEV_KEGG.Util.Parallelism.startProcessPool()
The actual function doing the work.

Indices and tables