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Data Mining for Systems Biology

Volume 939 of the series Methods in Molecular Biology pp 1-8

Date:

Dense Module Enumeration in Biological Networks

  • Koji TsudaAffiliated withAIST Computational Biology Research CenterJST ERATO Minato Project Email author 
  • , Elisabeth GeorgiiAffiliated withSchool of Science, Helsinki Institute for Information Technology HIIT Aalto University

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Abstract

Automatic discovery of functional complexes from protein interaction data is a rewarding but challenging problem. While previous approaches use approximations to extract dense modules, our approach exactly solves the problem of dense module enumeration. Furthermore, constraints from additional information sources such as gene expression and phenotype data can be integrated, so we can systematically detect dense modules with interesting profiles. Given a weighted protein interaction network, our method discovers all protein sets that satisfy a user-defined minimum density threshold. We employ a reverse search strategy, which allows us to exploit the density criterion in an efficient way.

Key words

Protein complex Dense module enumeration Reverse search Gene expression Protein interaction