An automatic integrative method for learning interpretable communities of biological pathways.

ABSTRACT: Although knowledge of biological pathways is essential for interpreting results from computational biology studies, the growing number of pathway databases complicates efforts to efficiently perform pathway analysis due to high redundancies among pathways from different databases, and inconsistencies in how pathways are created and named. We introduce the PAthway Communities (PAC) framework, which reconciles pathways from different databases and reduces pathway redundancy by revealing informative groups with distinct biological functions. Uniquely applying the Louvain community detection algorithm to a network of 4847 pathways from KEGG, REACTOME and Gene Ontology databases, we identify 35 distinct and automatically annotated communities of pathways and show that they are consistent with e

SUBMITTER: Beebe-Wang N 

PROVIDER: S-EPMC9228877 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature