A graph-theoretic method for mining overlapping functional modules in protein interaction networks

Authors:
Min Li;Jianxin Wang;Jianer Chen
Affiliations:
School of Information Science and Engineering, Central South University, Changsha, P.R. China;School of Information Science and Engineering, Central South University, Changsha, P.R. China;School of Information Science and Engineering, Central South University, Changsha, P.R. China and Department of Computer Science, Texas A&M University, College Station, TX
Venue:
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Year:
2008

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Abstract

Identification of functional modules in large protein interactionnetworks is crucial to understand principles of cellular organization,processes and functions. As a protein can perform different functions,functional modules overlap with each other. In this paper, we presenteda new algorithm OMFinder for mining overlapping functional modulesin protein interaction networks by using graph split and reduction. Weapplied algorithm OMFinder to the core protein interaction network ofbudding yeast collected from DIP database. The experimental resultsshowed that algorithm OMFinder detected many significant overlappingfunctional modules with various topologies. The significances of identifiedmodules were evaluated by using functional categories from MIPSdatabase. Most importantly, our algorithm had very low discard ratecompared to other approaches of detecting overlapping modules.