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Chunk #2 — Introduction

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Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.
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series of match, insert, and delete states linked together via state transitions. A match state models the position-specific amino acid probabilities (with Dirichlet mixtures [Sjölander et al., 1996]) at each column within the sequence alignment whereas insert/delete states allow for particular residues/states to be inserted and skipped, respectively, throughout the sequence alignment (position-specific insertions/deletions). HMM profiles are similar to PSI-BLAST profiles except they are applied within a more rigorous statistical framework and have been shown to perform considerably better when detecting distant relationships between homologous sequences [Madera and Gough, 2002].