Multiple DNA sequences alignment by means of genetic algorithm

Authors:
Chih-Chin Lai;Shih-Wei Chung
Affiliations:
Department of Information Management, Shu-Te University, Taiwan, R.O.C.;Department of Information Management, Shu-Te University, Taiwan, R.O.C.
Venue:
Design and application of hybrid intelligent systems
Year:
2003

Citing 2
Cited 1

Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Toward efficient multiple molecular sequence alignment: a system of genetic algorithm and dynamic programming

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

The evolutionary computation approach to motif discovery in biological sequences

GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation

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Abstract

The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. However, finding an optimal multiple sequence alignment takes time and space exponential with the length or number of sequences increases. In this paper, we view the multiple sequence alignment problem as an optimization problem and propose a genetic algorithm based approach to solve it. Genetic algorithms are a set of stochastic algorithms with the ability of exploratory search through the solution space and exploitation of current results. Experimental results are presented to illustrate the feasibility of the proposed approach.