DocumentCode
423682
Title
Aligning multiple protein sequence by an improved genetic algorithm
Author
Zhang, Guang-Zheng ; Huang, De-Shuang
Author_Institution
Hefei Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei, China
Volume
2
fYear
2004
fDate
25-29 July 2004
Firstpage
1179
Abstract
Genetic algorithm (GA) is one of the important and successful approaches in multiple sequences alignment (MSA) problem. In this paper, we propose an improved GA method, multiple small-popsize initialization strategy (MSPIS) and hybrid one-point crossover scheme (HOPCS) based GA, which can search the solution space in a very efficient manner. The experimental results show that our improved approach can obtain a better result compared with traditional GA approach in aligning multiple protein sequences problem.
Keywords
genetic algorithms; proteins; sequences; hybrid one point crossover scheme; improved GA methods; improved genetic algorithm; multiple protein sequences; multiple sequences alignment problem; multiple small popsize initialization strategy; Biological cells; Biological information theory; Costs; Data structures; Evolution (biology); Genetic algorithms; Genetic mutations; Machine intelligence; Protein sequence; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-8359-1
Type
conf
DOI
10.1109/IJCNN.2004.1380106
Filename
1380106
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