RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Pairwise local alignment of protein interaction networks guided by models of evolution
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
A Complex Networks Approach to Demographic Zonification
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Deterministic graph-theoretic algorithm for detecting modules in biological interaction networks
International Journal of Bioinformatics Research and Applications
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The increasing availability of protein-protein interaction graphs (PPI) requires new efficient tools capable of extracting valuable biological knowledge from these networks. Among the wide range of clustering algorithms, Girvan and Newman's edge betweenness algorithm showed remarkable performances in discovering clustering structures in several real-world networks. Unfortunately, their algorithm suffers from high computational cost and it is impractical for inputs of the size of large PPI networks. Here we report on a novel parallel implementation of Girvan and Newman's clustering algorithm that achieves almost linear speed-up for up to 32 processors. The tool is available in the public domain from the authors' website.