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Scoring hidden Markov models


Author(s) : Kevin Karplus Richard Hughey Christian Barrett, 
Publisher : N/A
Publication Date : 1997
ISSN : N/A
Abstract : 1.1 Motivation Statistical sequence comparison techniques, such as hidden Markov models and generalized profiles, calculate the probability that a sequence was generated by a given model. Log-odds scoring is a means of evaluating this probability by comparing it to a null hypothesis, usually a simpler statistical model intended to represent the universe of sequences as a whole, rather than the group of interest. Such scoring leads to two immediate questions: what should the null model be, and what threshold of log-odds score should be deemed a match to the model.,