Commit f654bc88 authored by Ayse Berceste Dincer's avatar Ayse Berceste Dincer
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Although biological pathways are essential forinterpreting results from computational biologystudies, the growing number of pathway databasesmakes it difficult to perform pathway analysis.Our study seeks to reconcile pathways from dif-ferent databases and reduce pathway redundancyby revealing informative groups with distinct bio-logical functions. Uniquely applying the Louvaincommunity detection algorithm to a network of4,847 pathways from KEGG, REACTOME andGene Ontology databases, we identify 35 distinctcommunities of pathways and show that thesecommunities are consistent with expert-curatedpathway categories. Further, we develop an algo-rithm to automatically annotate each communitybased on member pathways’ names. By learn-ing informative categories, we progress towards atool that computational biologists can use to moreefficiently interpret their biological findings.
<img align="center" src="ConceptFigure.png" width="60%">.
<img align="center" src="Concept_Figure.png" width="60%">.
### Pipeline
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### Pipeline
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