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Title: FACETS : multi-faceted functional decomposition of protein interaction networks
Authors: Bhowmick, Sourav S.
Seah, Boon-Siew
Dewey Jr., C. Forbes
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Seah, B.-S., Bhowmick, S. S., & Jr., C. F. D. (2012). FACETS: multi-faceted functional decomposition of protein interaction networks. Bioinformatics, 28(20), 2624-2631.
Series/Report no.: Bioinformatics
Abstract: Motivation: The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein–protein interaction (PPI) network using graph theoretic analysis. Despite the recent progress, systems level analysis of high-throughput PPIs remains a daunting task because of the amount of data they present. In this article, we propose a novel PPI network decomposition algorithm called FACETS in order to make sense of the deluge of interaction data using Gene Ontology (GO) annotations. FACETS finds not just a single functional decomposition of the PPI network, but a multi-faceted atlas of functional decompositions that portray alternative perspectives of the functional landscape of the underlying PPI network. Each facet in the atlas represents a distinct interpretation of how the network can be functionally decomposed and organized. Our algorithm maximizes interpretative value of the atlas by optimizing inter-facet orthogonality and intra-facet cluster modularity. Results: We tested our algorithm on the global networks from IntAct, and compared it with gold standard datasets from MIPS and KEGG. We demonstrated the performance of FACETS. We also performed a case study that illustrates the utility of our approach.
ISSN: 1367-4803
DOI: 10.1093/bioinformatics/bts469
Rights: © 2012 The Author.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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