A Parallel Algorithm for Clustering Protein-Protein Interaction Networks

Authors:
Qiaofeng Yang;Stefano Lonardi
Affiliations:
University of California, Riverside;University of California, Riverside
Venue:
CSBW '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference - Workshops
Year:
2005

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Abstract

The increasing availability of interaction graphs requires new resource-efficient tools capable of extracting valuable biological knowledge from these networks. In this paper we report on a novel parallel implementation of Girvan and Newman驴s clustering algorithm that is capable of running on clusters of computers. Our parallel implementation achieves almost linear speed-up up to 32 processors and allows us to run this computationally intensive algorithm on large protein-protein interaction networks. Preliminary experiments show that the algorithm has very high accuracy in identifying functional related protein modules. Software will be made available in the public domain at http://www.cs.ucr.edu/qyang/