Detecting Functional Modules from Protein Interaction Networks

  • Authors:
  • Feng Luo;Richard H. Scheuermann

  • Affiliations:
  • Clemson University, USA;University of Texes, Southwestern Medical Center, USA

  • Venue:
  • IMSCCS '06 Proceedings of the First International Multi-Symposiums on Computer and Computational Sciences - Volume 1 (IMSCCS'06) - Volume 01
  • Year:
  • 2006

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Abstract

Accumulating evidence suggests that biological systems are composed of separable functional modules. Identifying these modules is essential in understanding the organization of biological systems. In this paper, we extend the indegree and outdegree concept of vertex to the sub-graph and propos a new formal definition of a module in a network. By combining our new network module definition with an adaptation of the Girvan-Newman algorithm, we propose a new divisive algorithm to detect modules from protein interaction networks. We applied our approach to the DIP yeast core protein interaction network and 81 compact simple modules with size larger than 3 are revealed. All 81 modules are significantly enriched for functional Gene Ontology terms. Comparison between our compact simple modules with the modules of Radicchi et al. showed that our modules are statistically more significant (lower P-value). Our approach provides a plausible way to identify functional modules within biological networks.