Multiple sequence alignment based on genetic algorithms with reserve selection

Yang Chen; Jinglu Hu; Kotaro Hirasawa; Songnian Yu

doi:10.1109/ICNSC.2008.4525460

Multiple sequence alignment based on genetic algorithms with reserve selection

Yang Chen^*, Jinglu Hu, Kotaro Hirasawa, Songnian Yu

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)

Abstract

This paper presents an approach to the multiple sequence alignment (MSA) problem by applying genetic algorithms with a reserve selection mechanism. MSA is one of the most fundamental operations in bioinformatics, which plays an important part in predicting the structure, function and evolution of biological sequences. In order to solve the MSA problem efficiently, genetic algorithms (GAs) were applied. As the number and length of sequences increase, however, GAs are usually suffered from premature convergence where they are easily trapped into local optima. In this paper, we employ the reserve selection that is a new selection scheme to avoid premature convergence in GAs. Empirical studies demonstrate that genetic algorithms with reserve selection (GARS) could bring about a rise in the quality of multiple sequence alignment when compared with standard GAs.

Original language	English
Title of host publication	Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC
Pages	1511-1516
Number of pages	6
DOIs	https://doi.org/10.1109/ICNSC.2008.4525460
Publication status	Published - 2008 Aug 18
Event	2008 IEEE International Conference on Networking, Sensing and Control, ICNSC - Sanya, China Duration: 2008 Apr 6 → 2008 Apr 8

Publication series

Name	Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC

Conference

Conference	2008 IEEE International Conference on Networking, Sensing and Control, ICNSC
Country/Territory	China
City	Sanya
Period	08/4/6 → 08/4/8

ASJC Scopus subject areas

Computer Networks and Communications
Control and Systems Engineering

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10.1109/ICNSC.2008.4525460

Cite this

Chen, Y., Hu, J., Hirasawa, K., & Yu, S. (2008). Multiple sequence alignment based on genetic algorithms with reserve selection. In Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC (pp. 1511-1516). Article 4525460 (Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC). https://doi.org/10.1109/ICNSC.2008.4525460

Multiple sequence alignment based on genetic algorithms with reserve selection. / Chen, Yang; Hu, Jinglu; Hirasawa, Kotaro et al.
Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC. 2008. p. 1511-1516 4525460 (Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chen, Y, Hu, J, Hirasawa, K & Yu, S 2008, Multiple sequence alignment based on genetic algorithms with reserve selection. in Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC., 4525460, Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC, pp. 1511-1516, 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC, Sanya, China, 08/4/6. https://doi.org/10.1109/ICNSC.2008.4525460

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abstract = "This paper presents an approach to the multiple sequence alignment (MSA) problem by applying genetic algorithms with a reserve selection mechanism. MSA is one of the most fundamental operations in bioinformatics, which plays an important part in predicting the structure, function and evolution of biological sequences. In order to solve the MSA problem efficiently, genetic algorithms (GAs) were applied. As the number and length of sequences increase, however, GAs are usually suffered from premature convergence where they are easily trapped into local optima. In this paper, we employ the reserve selection that is a new selection scheme to avoid premature convergence in GAs. Empirical studies demonstrate that genetic algorithms with reserve selection (GARS) could bring about a rise in the quality of multiple sequence alignment when compared with standard GAs.",

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Multiple sequence alignment based on genetic algorithms with reserve selection

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