title: A parallel edge-betweenness clustering tool for Protein-Protein Interaction networks.
abstract: 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.
authors.affiliation: Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA. qyang@cs.ucr.edu
authors.forename: Qiaofeng
authors.initials: Q
authors.lastname: Yang
authors.forename: Stefano
authors.initials: S
authors.lastname: Lonardi
mesh_terms: D016000:Cluster Analysis; D016247:Information Storage and Retrieval; D016571:Neural Networks, Computer; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000502:physiology; D040901:Proteomics; D015398:Signal Transduction; D012984:Software; D049490:Systems Biology / Q000379:methods; D014941:Work Simplification
chemical_list: D011506:Proteins