Accurate quantification of functional analogy among close homologs. Author Maria Chikina, Olga Troyanskaya Publication Year 2011 Type Journal Article Abstract Correctly evaluating functional similarities among homologous proteins is necessary for accurate transfer of experimental knowledge from one organism to another, and is of particular importance for the development of animal models of human disease. While the fact that sequence similarity implies functional similarity is a fundamental paradigm of molecular biology, sequence comparison does not directly assess the extent to which two proteins participate in the same biological processes, and has limited utility for analyzing families with several parologous members. Nevertheless, we show that it is possible to provide a cross-organism functional similarity measure in an unbiased way through the exclusive use of high-throughput gene-expression data. Our methodology is based on probabilistic cross-species mapping of functionally analogous proteins based on Bayesian integrative analysis of gene expression compendia. We demonstrate that even among closely related genes, our method is able to predict functionally analogous homolog pairs better than relying on sequence comparison alone. We also demonstrate that the landscape of functional similarity is often complex and that definitive "functional orthologs" do not always exist. Even in these cases, our method and the online interface we provide are designed to allow detailed exploration of sources of inferred functional similarity that can be evaluated by the user. Keywords Animals, Humans, Gene Expression Profiling, Evolution, Molecular, Gene Regulatory Networks, Species Specificity, Proteins, Computational Biology, Oligonucleotide Array Sequence Analysis, Bayes Theorem, Saccharomyces cerevisiae Proteins, Superoxide Dismutase, Sequence Homology, Amino Acid, Lamins, Structural Homology, Protein, Synaptosomal-Associated Protein 25 Journal PLoS Comput Biol Volume 7 Issue 2 Pages e1001074 Alternate Journal PLoS Comput. Biol. Google ScholarBibTeXEndNote X3 XML