title: Combining gene expression profiles and protein-protein interaction data to infer gene functions.
abstract: The ever-increasing flow of gene expression profiles and protein-protein interactions has catalyzed many computational approaches for inference of gene functions. Despite all the efforts, there is still room for improvement, for the information enriched in each biological data source has not been exploited to its fullness. A composite method is proposed for classifying unannotated genes based on expression data and protein-protein interaction (PPI) data, which extracts information from both data sources in novel ways. With the noise nature of expression data taken into consideration, importance is attached to the consensus expression patterns of gene classes instead of the actual expression profiles of individual genes, thus characterizing the composite method with enhanced robustness against microarray data variation. With regard to the PPI network, the traditional clear-cut binary attitude towards inter- and intra-functional interactions is abandoned, whereas a more objective perspective into the PPI network structure is formed through incorporating the varied function-function interaction probabilities into the algorithm. The composite method was implemented in two numerical experiments, where its improvement over single-data-source based methods was observed and the superiority of the novel data handling operations was discussed.
authors.affiliation: Bioinformatics Center, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences 320 Yueyang Road, Shanghai 200031, China.
authors.forename: Kang
authors.initials: K
authors.lastname: Tu
authors.forename: Hui
authors.initials: H
authors.lastname: Yu
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D030562:Databases, Protein; D015870:Gene Expression / Q000502:physiology*; D020869:Gene Expression Profiling / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D025941:Protein Interaction Mapping / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000145:classification* / Q000378:metabolism*
chemical_list: D029701:Saccharomyces cerevisiae Proteins