| Modeling the evolution of biological systems
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| Biological systems are complex systems with an important property: they have evolved ultimately from simpler systems along a trajectory of successive steps where each step was selectively advantageous. Evolutionary constraints on the trajectories are reflected at the molecular level, and can be probed by a number of techniques including biochemistry and comparative analysis of extant successful protein sequences. These constraints should also be reflected at higher levels of organization in biological systems, such as biochemical pathways. Integrating information across these levels of organization is critical for understanding the evolution of biological systems.
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| The ESB Group has been developing software for computational representation and analysis of
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 the evolution of protein families, and the relationships between protein sequence and function, and |
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the interactions between different biological molecules (pathways) to accomplish complex processes. |
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To browse much of this work, take a look at the freely available PANTHER Classification System at http://www.pantherdb.org. The PANTHER (Protein Analysis Through Evolutionary Relationships) Classification System classifies proteins according to their evolutionary history and their known or predicted functions. PANTHER was originally developed at Celera Genomics and Applied Biosystems, and further development and maintenance will continue with the core group having moved to SRI. The database, covering over 5000 protein families and over 100 pathways, can be searched and browsed, and offers a number of tools for biologists interested in exploring protein function and evolution.
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Huaiyu Mi, Betty Lazareva-Ulitsky, Rozina Loo, Anish Kejariwal, Jody Vandergriff, Steven Rabkin, Nan Guo, Anushya Muruganujan, Olivier Doremieux, Michael J. Campbell, Hiroaki Kitano and Paul D. Thomas. 2005. The PANTHER database of protein families, subfamilies, functions and pathways. Nucl. Acids. Res., 31:334-341.
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Paul D. Thomas, Michael J. Campbell, Anish Kejariwal, Huaiyu Mi, Brian Karlak, Robin Daverman, Karen Diemer, Anushya Muruganujan, Apurva Narechania. 2003. PANTHER: a library of protein families and subfamilies indexed by function. Genome Res., 13: 2129-2141
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Huaiyu Mi, Jody Vandergriff, Michael Campbell, Apurva Narechania, William Majoros, Suzanna Lewis, Paul D. Thomas, Michael Ashburner. 2003. Assessment of genome-wide protein function classification for Drosophila melanogaster. Genome Res., 13: 2118-2128.
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| Application to understanding the genetics of disease
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| One of the group's greatest interests is in how evolutionary modeling can shed light on the molecular causes of human disease. For example, we and others have shown that most of the known mutations causing Mendelian disease in humans occur at evolutionarily conserved positions in proteins: in other words, patterns of negative selection (i.e. selection against changes at these positions) apparent from comparing related genes (in the same or in other species) reveal essential sites in proteins that, if mutated, cause human disease. We have recently shown that detailed evolutionary modeling, including signals of positive as well as negative selection, can significantly improve our predictions for both Mendelian and even complex disease. |
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Liam R. Brunham, Roshni R. Singaraja, Terry D. Pape, Anish Kejariwal, Paul D. Thomas, Michael R. Hayden. 2005. Accurate Prediction of the Functional Significance of Single Nucleotide Polymorphisms and Mutations in the ABCA1 Gene. PLoS Genetics, 1(6): e83.
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Paul D. Thomas and Anish Kejariwal. 2004. Coding single-nucleotide polymorphisms associated with complex vs. Mendelian disease: Evolutionary evidence for differences in molecular effects. Proc. Natl. Acad. Sci., 101(43):15398-403.
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Andrew G. Clark, Stephen Glanowski, Rasmus Nielsen, Paul D. Thomas, Anish Kejariwal, Melissa A. Todd, David M. Tanenbaum, Daniel Civello, Fu Lu, Brian Murphy, Steve Ferriera, Gary Wang, Xianqgun Zheng, Thomas J. White, John J. Sninsky, Mark D. Adams, Michele Cargill. 2003. Inferring nonneutral evolution from human-chimp-mouse orthologous gene trios. Science, 302: 1960-1963.
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R&D Divisions