Generalized Hidden Markov Models for Protein Sequence Analysis

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9408579 Haussler This award will support research in the development of statistical methods, algorithms and software for the analysis of protein and RNA sequence data based on generalization of the hidden Markov model. Specifically the investigators will use and develop Hidden Markov Models, Stochastic Graph Grammars, and Markov Random Fields. These methods would have applications to inverse folding, multiple alignment and database searching in molecular and structural biology. This award is supported by programs in Computational Biology and the Theory of Computing.