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A Parallel Algorithm for Clustering Protein-Protein Interaction Networks
Stanford, California August 08-August 11
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSBW.2005.132005 IEEE Computational Systems Bioin ...
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Qiaofeng Yang, University of California, Riverside
Stefano Lonardi, University of California, Riverside

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?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/

Citation:
Qiaofeng Yang, Stefano Lonardi, "A Parallel Algorithm for Clustering Protein-Protein Interaction Networks," csbw, pp.174-177, 2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05), 2005
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