Evolving the Structure of Hidden Markov Models
Evolving the Structure of Hidden Markov Models
A Genetic Algorithm (GA) is proposed for finding the structure of Hidden Markov Models (HMMs) used for biological sequence analysis. The GA is designed to preserve biologically meaningful building blocks. The search through the space of HMM structures is combined with optimisation of the emission and transition probabilities using the classic Baum-Welch algorithm. The system is tested on the problem of finding the promoter and coding region of C. jejuni. The resulting HMM has a superior discrimination ability to a hand-crafted model that has been published in the literature.
39-49
Won, Kyoung-Jae
3b5c7d9a-e6bd-4624-9825-338e795b9945
Prügel-Bennett, Adam
b107a151-1751-4d8b-b8db-2c395ac4e14e
Krogh, Anders
4a5cfccf-5403-45fb-96c5-61f60bef7d79
2006
Won, Kyoung-Jae
3b5c7d9a-e6bd-4624-9825-338e795b9945
Prügel-Bennett, Adam
b107a151-1751-4d8b-b8db-2c395ac4e14e
Krogh, Anders
4a5cfccf-5403-45fb-96c5-61f60bef7d79
Won, Kyoung-Jae, Prügel-Bennett, Adam and Krogh, Anders
(2006)
Evolving the Structure of Hidden Markov Models.
IEEE Transactions on Evolutionary Computation, 10 (1), .
Abstract
A Genetic Algorithm (GA) is proposed for finding the structure of Hidden Markov Models (HMMs) used for biological sequence analysis. The GA is designed to preserve biologically meaningful building blocks. The search through the space of HMM structures is combined with optimisation of the emission and transition probabilities using the classic Baum-Welch algorithm. The system is tested on the problem of finding the promoter and coding region of C. jejuni. The resulting HMM has a superior discrimination ability to a hand-crafted model that has been published in the literature.
More information
Published date: 2006
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 263992
URI: http://eprints.soton.ac.uk/id/eprint/263992
PURE UUID: a8159243-0169-4aa3-9e13-f61a124f380a
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Date deposited: 08 May 2007
Last modified: 14 Mar 2024 07:40
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Contributors
Author:
Kyoung-Jae Won
Author:
Adam Prügel-Bennett
Author:
Anders Krogh
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