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Bioinformatics Advance Access originally published online on January 29, 2004
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Bioinformatics 20(6) © Oxford University Press 2004; all rights reserved.

Mapping gene ontology to proteins based on protein–protein interaction data

Minghua Deng , Zhidong Tu , Fengzhu Sun * and Ting Chen *

Department of Biological Sciences, Molecular and Computational Biology Program, University of Southern California, 1042 West 36th Place, Los Angeles, CA 90089-1113, USA

Received on July 29, 2003 ; revised on October 12, 2003 ; accepted on October 13, 2003

Motivation: Gene Ontology (GO) consortium provides structural description of protein function that is used as a common language for gene annotation in many organisms. Large-scale techniques have generated many valuable protein–protein interaction datasets that are useful for the study of protein function. Combining both GO and protein–protein interaction data allows the prediction of function for unknown proteins.

Result: We apply a Markov random field method to the prediction of yeast protein function based on multiple protein–protein interaction datasets. We assign function to unknown proteins with a probability representing the confidence of this prediction. The functions are based on three general categories of cellular component, molecular function and biological process defined in GO. The yeast proteins are defined in the Saccharomyces Genome Database (SGD). The protein–protein interaction datasets are obtained from the Munich Information Center for Protein Sequences (MIPS), including physical interactions and genetic interactions. The efficiency of our prediction is measured by applying the leave-one-out validation procedure to a functional path matching scheme, which compares the prediction with the GO description of a protein's function from the abstract level to the detailed level along the GO structure. For biological process, the leave-one-out validation procedure shows 52% precision and recall of our method, much better than that of the simple guilty-by-association methods.

Supplementary material: http://www.cmb.usc.edu/~msms/gomapping

Contact: fsun{at}hto.usc.edu

* To whom correspondence should be addressed.


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