NDLI: Combining phylogenetic and hidden Markov models in biosequence analysis

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Combining phylogenetic and hidden Markov models in biosequence analysis

Content Provider	ACM Digital Library
Author	Haussler, David Siepel, Adam
Abstract	A few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process changes from one site to the next. These models combine phylogenetic models of molecular evolution, which apply to individual sites, and hidden Markov models, which allow for changes from site to site. Besides improving the realism of ordinary phylogenetic models, they are potentially very powerful tools for inference and prediction---for gene finding, for example, or prediction of secondary structure. In this paper, we review progress on combined phylogenetic and hidden Markov models and present some extensions to previous work. Our main result is a simple and efficient method for accommodating higher-order states in the HMM, which allows for context-sensitive models of substitution---that is, models that consider the effects of neighboring bases on the pattern of substitution. We present experimental results indicating that higher-order states, autocorrelated rates, and multiple functional categories all lead to significant improvements in the fit of a combined phylogenetic and hidden Markov model, with the effect of higher-order states being particularly pronounced.
Starting Page	277
Ending Page	286
Page Count	10
File Format	PDF
ISBN	1581136358
DOI	10.1145/640075.640111
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-04-10
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Context-sensitive substitution Maximum likelihood
Content Type	Text
Resource Type	Article

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