A Parallel Algorithm for Clustering Protein-Protein Interaction Networks

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/

• Type: Conference
• Year: 2005
• Where: CSB
• Authors: Qiaofeng Yang, Stefano Lonardi
• Keywords: Bioinformatics, CSB 2005, Parallel Implementation, Protein-protein Interaction Networks, Valuable Biological Knowledge