Bioinformatics Advance Access originally published online on February 4, 2005
Bioinformatics 2005 21(9):2043-2048; doi:10.1093/bioinformatics/bti305
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Accurate extraction of functional associations between proteins based on common interaction partners and common domains
1Graduate School of Information Sciences, Nara Institute of Science and Technology 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
2Department of Computational Biology, Faculty of Frontier Sciences, The University of Tokyo 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
3Computational Biology Research Center, The National Institute of Advanced Industrial Science and Technology Aomi Frontier Building 2-43 Aomi, 17F, Koto-ku, Tokyo 135-0064, Japan
*To whom correspondence should be addressed.
Motivation: Genomic and proteomic approaches have accumulated a huge amount of data which provide clues to protein function. However, interpreting single omic data for predicting uncharacterized protein functions has been a challenging task, because the data contain a lot of false positives. To overcome this problem, methods for integrating data from various omic approaches are needed for more accurate function prediction.
Result: In this paper, we have developed a method which extracts functionally similar proteins with high confidence by integrating protein–protein interaction data and domain information. We used this method to analyze publicly available data from Saccharomyces cerevisiae. We identified 1042 functional associations, involving 765 proteins of which 98 (12.8%) had no previously ascribed function. Our method extracts functionally similar protein pairs more accurately than conventional methods, and predicting function for previously uncharacterized proteins can be achieved. Our method can of course be applied to protein–protein interaction data for any species.
Contact: okada-k{at}cb.k.u-tokyo.ac.jp
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