Brief communication: Identification of functional modules in a PPI network by clique percolation clustering

Authors:
Shihua Zhang;Xuemei Ning;Xiang-Sun Zhang
Affiliations:
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China and Graduate University of the Chinese Academy of Sciences, Beijing 100049, China;Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China and Graduate University of the Chinese Academy of Sciences, Beijing 100049, China;Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China
Venue:
Computational Biology and Chemistry
Year:
2006

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Abstract

Large-scale experiments and data integration have provided the opportunity to systematically analyze and comprehensively understand the topology of biological networks and biochemical processes in cells. Modular architecture which encompasses groups of genes/proteins involved in elementary biological functional units is a basic form of the organization of interacting proteins. Here we apply a graph clustering algorithm based on clique percolation clustering to detect overlapping network modules of a protein-protein interaction (PPI) network. Our analysis of the yeast Sacchromyces cerevisiae suggests that most of the detected modules correspond to one or more experimentally functional modules and half of these annotated modules match well with experimentally determined protein complexes. Our method of analysis can of course be applied to protein-protein interaction data for any species and even other biological networks.