Collapse all genes', RNAs', miRNAs', and proteins' variants to their parents.
Collapse consistent edges together.
Collapse all equivalence edges away from Entrez. Assumes well formed, 2-way equivalencies.
Collapse Entrez equivalences to HGNC.
Collapse FlyBase orthologies to HGNC.
Collapse all gene's variants' edges to their parents, in-place.
Collapse MGI orthologies to HGNC.
Collapse all protein's variants' edges to their parents, in-place.
Collapse RGD orthologies to HGNC.
Collapse all protein, RNA, and miRNA nodes to their corresponding gene nodes.
Collapse to a graph made of only causal gene/protein edges.
Add all of the members of the complex abundances to the graph.
Adds all of the members of the composite abundances to the graph.
Add the missing unqualified edges between entities in the subgraph that are contained within the full graph.
Add the corresponding RNA for each protein then the corresponding gene for each RNA/miRNA.
Add the corresponding RNA node for each protein node and connect them with a translation edge.
Adds all of the reactants and products of reactions to the graph.
Add the corresponding gene node for each RNA/miRNA node and connect them with a transcription edge.
Enrich the sub-graph with the unqualified edges from the graph.
Add the reference nodes for all variants of the given function.
Add the downstream causal relations to the given sub-graph.
Add causal edges between entities in the sub-graph.
Add the upstream causal relations to the given sub-graph.
Build a new sub-graph induced over the causal edges.
Get the giant component of a graph.
Highlight all nodes/edges in the universe that in the given graph.
Add edges to the graph when a two way edge exists, and the opposite direction doesn't exist.
Delete RNA nodes that are only connected to one node - their correspond protein - by a translation edge.
Delete genes that are only connected to one node, their correspond RNA, by a translation edge.
Delete gene nodes that are only connected to one node, their correspond RNA, by a transcription edge.
Remove all associative relationships from the graph.
Remove biological process nodes from the graph.
Remove the metadata associated with a citation.
Remove all edges between node pairs with inconsistent edges.
Remove isolated list abundances from the graph.
Remove isolated nodes from the network, in place.
Build a new graph excluding the isolated nodes.
Remove nodes using the MGI and MGIID namespaces.
Remove pathology nodes from the graph.
Remove nodes using the RGD and RGDID namespaces.
Find all protein variants that are pointing to a gene and not a protein and fixes them by changing their function to be :data:`pybel.constants.GENE`, in place
Strip all the annotations from a BEL graph.
Updates the context of a subgraph from the universe of all knowledge.
BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.
If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.