Tao Yue will present his research seminar/general exam on Monday May 11 at 10AM in room 402. The members of his committee are: Mona Singh, advisor, Olga Troyanskaya, and Tom Funkhouser. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ------------------------------------------- ABSTRACT --------- Sequence similarity has long been used to find orthologs between proteins in different species, or to find paralogs within a species. Predictions of these evolutionary relationships can be exploited to infer and transfer functional annotations between proteins. In the past decade, high-throughput screening techniques have enabled the construction of protein interaction networks for many model organisms. In addition to direct protein interactions, other associations can also be made between pairs of proteins: coexpression, phylogenetic, neighborhood, gene fusion, etc. Such networks provide the opportunity to characterize a protein not just by its sequence, but by its interaction and association partners. This talk explains how to exploit these networks to detect functionally similar proteins between different species. Such networks, particularly the protein interaction networks, provide more direct evidence of function than does sequence similarity. We evaluate the power of various metrics for uncovering functionally similar proteins without using sequence similarity. In addition, we apply Rankprop, a diffusion-based process that has previously been used on sequence similarity, to these networks. We show that the use of networks from multiple organisms yields improvements in precision and recall. Furthermore, this procedure can be used to disambiguate predictions made by sequence-based methods, as well as correct errors. These techniques show promising applications as more interaction data becomes available. They also have potential future applications to the detection of analogous proteins, i.e., those that evolved the same function independently and thus lack sequence similarity. TEXTBOOK --------- Mount, Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press, 2004. Chapters 1-7, 11. PAPERS: General area: Protein networks --------------------------------------- Barabasi and Oltvai, Network Biology: Understanding the Cell's Functional Organization. Nature Reviews Genetics, February 2004, 101-113. Nabieva and Singh, Protein function prediction via analysis of interactomes. Prediction of Protein Structures, Functions, and Interactions (ed J. Bujnicki), 2009. Zhu et al, Getting connected: analysis and principles of biological networks. Genes & Developmnent 21 (2007): 1010-1024. PAPERS: Subareas ----------------------------------------------------------------------- Bandyopadhyay et al. Systematic identification of functional orthologs based on protein network comparison. Genome Research 16 (2006), pp. 428-435. Li et al. OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes. Genome Research 13 (2003), pp. 2178-2189. Remm et al. Automatic Clustering of Orthologs and In-paralogs from Pairwise Species Comparisons. J. Molecular Biology (2001) 314, pp. 1041-1052. Sharan et al. Conserved patterns of protein interaction in multiple species. PNAS, February 8, 2005, 1974-1979. Sharan and Ideker. Modeling cellular machinery through biological network comparison. Nature Biotechnology 24 (2006), 427-433. Singh et al. Global alignment of multiple protein interaction networks with application to functional orthology detection. PNAS, September 2, 2008, pp. 12763-12768. Yosef et al. Improved Network-based Identification of Protein Orthologs. Bioinformatics Vol. 24 ECCB 2008, pp. i200-i206.