Rune Lyngsø, Christian N. S. Pedersen and Henrik Nielsen,
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 left-right models, e.g. profile hidden Markov models,
and briefly 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.