title: Mapping Gene Ontology to proteins based on protein-protein interaction data.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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.
authors.affiliation: Department of Biological Sciences, Molecular and Computational Biology Program, University of Southern California, 1042 West 36th Place, Los Angeles, CA 90089-1113, USA.
authors.forename: Minghua
authors.initials: M
authors.lastname: Deng
authors.forename: Zhidong
authors.initials: Z
authors.lastname: Tu
authors.forename: Fengzhu
authors.initials: F
authors.lastname: Sun
authors.forename: Ting
authors.initials: T
authors.lastname: Chen
mesh_terms: D002874:Chromosome Mapping / Q000379:methods*; D030562:Databases, Protein; D020869:Gene Expression Profiling / Q000379:methods*; D015966:Gene Expression Regulation, Fungal / Q000502:physiology*; D016681:Genome, Fungal; D010802:Phylogeny; D025941:Protein Interaction Mapping / Q000379:methods*; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D013329:Structure-Activity Relationship
chemical_list: D029701:Saccharomyces cerevisiae Proteins