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Bioinformatics Research and Applications

Volume 6674 of the series Lecture Notes in Computer Science pp 111-122

Algorithms to Detect Multiprotein Modularity Conserved during Evolution

  • Luqman HodgkinsonAffiliated withCarnegie Mellon UniversityComputer Science Division, University of CaliforniaCenter for Computational Biology, University of CaliforniaInternational Computer Science Institute
  • , Richard M. KarpAffiliated withCarnegie Mellon UniversityComputer Science Division, University of CaliforniaCenter for Computational Biology, University of CaliforniaInternational Computer Science Institute

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Abstract

Detecting essential multiprotein modules that change infrequently during evolution is a challenging algorithmic task that is important for understanding the structure, function, and evolution of the biological cell. In this paper, we present a linear-time algorithm, Produles, that improves on the running time of previous algorithms. We present a biologically motivated graph theoretic set of algorithm goals complementary to previous evaluation measures, demonstrate that Produles attains these goals more comprehensively than previous algorithms, and exhibit certain recurrent anomalies in the performance of previous algorithms that are not detected by previous measures.

Keywords

modularity interactomes evolution algorithms