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Measures on Hidden Markov Models
Rune B. Lyngsø
February 1999 |
Abstract:
Hidden Markov models were introduced in the beginning of the
1970's as a tool in speech recognition. During the last decade they have been
found useful in addressing problems in computational biology such as
characterising sequence families, gene finding, structure prediction and
phylogenetic analysis. In this paper we propose several measures between
hidden Markov models. We give an efficient algorithm that computes the
measures for profile hidden Markov models and discuss how to extend the
algorithm to other types of models. We present an experiment using the
measures to compare hidden Markov models for three classes of signal
peptides
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