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An automated method for finding molecular complexes in large protein interaction networks

BMC Bioinformatics · 2003 · Vol. 4(1) · pp. 2–2

Gary D. Bader✉(Lunenfeld-Tanenbaum Research Institute)Christopher W.V. Hogue(Lunenfeld-Tanenbaum Research Institute)

Abstract

Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from ftp://ftp.mshri.on.ca/pub/BIND/Tools/MCODE.

Bioinformatics and Genomic Networks Microbial Metabolic Engineering and Bioproduction Biotin and Related StudiesComputer scienceTree traversalCluster analysisProtein Interaction NetworksProtein–protein interactionInteraction networkData miningFalse positive paradoxComputational biologyTheoretical computer science

MeSH terms

AlgorithmsComputer GraphicsPredictive Value of TestsSoftware ValidationCluster AnalysisComputational BiologyProtein Interaction MappingSaccharomyces cerevisiae ProteinsProteomicsMacromolecular Substances