IEICE TRANSACTIONS on Information
Multiple DNA Sequences Alignment Using Heuristic-Based Genetic Algorithm
Summary :
The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. A wide variety of approaches has been proposed for multiple sequence alignment problem; however, some of them need prerequisites to help find the best alignment or some of them may suffer from the drawbacks of complexity and memory requirement so they can be only applied to cases with a limited number of sequences. In this paper, we view the multiple sequence alignment problem as an optimization problem and propose a heuristic-based genetic algorithm (GA) approach to solve it. The heuristic/GA hybrid yields better results than other well-known packages do. Experimental results are presented to illustrate the feasibility of the proposed approach.
- Publication
- IEICE TRANSACTIONS on Information Vol.E87-D No.7 pp.1910-1916
- Publication Date
- 2004/07/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence and Cognitive Science
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Chih-Chin LAI, Shih-Wei CHUNG, "Multiple DNA Sequences Alignment Using Heuristic-Based Genetic Algorithm" in IEICE TRANSACTIONS on Information,
vol. E87-D, no. 7, pp. 1910-1916, July 2004, doi: .
Abstract: The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. A wide variety of approaches has been proposed for multiple sequence alignment problem; however, some of them need prerequisites to help find the best alignment or some of them may suffer from the drawbacks of complexity and memory requirement so they can be only applied to cases with a limited number of sequences. In this paper, we view the multiple sequence alignment problem as an optimization problem and propose a heuristic-based genetic algorithm (GA) approach to solve it. The heuristic/GA hybrid yields better results than other well-known packages do. Experimental results are presented to illustrate the feasibility of the proposed approach.
URL: https://global.ieice.org/en_transactions/information/10.1587/e87-d_7_1910/_p
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@ARTICLE{e87-d_7_1910,
author={Chih-Chin LAI, Shih-Wei CHUNG, },
journal={IEICE TRANSACTIONS on Information},
title={Multiple DNA Sequences Alignment Using Heuristic-Based Genetic Algorithm},
year={2004},
volume={E87-D},
number={7},
pages={1910-1916},
abstract={The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. A wide variety of approaches has been proposed for multiple sequence alignment problem; however, some of them need prerequisites to help find the best alignment or some of them may suffer from the drawbacks of complexity and memory requirement so they can be only applied to cases with a limited number of sequences. In this paper, we view the multiple sequence alignment problem as an optimization problem and propose a heuristic-based genetic algorithm (GA) approach to solve it. The heuristic/GA hybrid yields better results than other well-known packages do. Experimental results are presented to illustrate the feasibility of the proposed approach.},
keywords={},
doi={},
ISSN={},
month={July},}
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TY - JOUR
TI - Multiple DNA Sequences Alignment Using Heuristic-Based Genetic Algorithm
T2 - IEICE TRANSACTIONS on Information
SP - 1910
EP - 1916
AU - Chih-Chin LAI
AU - Shih-Wei CHUNG
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E87-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2004
AB - The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. A wide variety of approaches has been proposed for multiple sequence alignment problem; however, some of them need prerequisites to help find the best alignment or some of them may suffer from the drawbacks of complexity and memory requirement so they can be only applied to cases with a limited number of sequences. In this paper, we view the multiple sequence alignment problem as an optimization problem and propose a heuristic-based genetic algorithm (GA) approach to solve it. The heuristic/GA hybrid yields better results than other well-known packages do. Experimental results are presented to illustrate the feasibility of the proposed approach.
ER -
English
