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Bioinformatics Advance Access originally published online on July 12, 2006
Bioinformatics 2006 22(18):2283-2290; doi:10.1093/bioinformatics/btl370
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Detecting functional modules in the yeast protein–protein interaction network

Jingchun Chen and Bo Yuan *

Integrated Biomedical Science Graduate Program, Department of Biomedical Informatics and Department of Pharmacology, The Ohio State University 333 W. 10th Avenue, Columbus, OH 43210, USA

*To whom correspondence should be addressed

Motivation: Identification of functional modules in protein interaction networks is a first step in understanding the organization and dynamics of cell functions. To ensure that the identified modules are biologically meaningful, network-partitioning algorithms should take into account not only topological features but also functional relationships, and identified modules should be rigorously validated.

Results: In this study we first integrate proteomics and microarray datasets and represent the yeast protein–protein interaction network as a weighted graph. We then extend a betweenness-based partition algorithm, and use it to identify 266 functional modules in the yeast proteome network. For validation we show that the functional modules are indeed densely connected subgraphs. In addition, genes in the same functional module confer a similar phenotype. Furthermore, known protein complexes are largely contained in the functional modules in their entirety. We also analyze an example of a functional module and show that functional modules can be useful for gene annotation.

Contact: yuan.33{at}osu.edu

Supplementary Information: Supplementary data are available at Bioinformatics online

Received on April 20, 2006; revised on July 3, 2006; accepted on July 4, 2006

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