Multiple Sequence Alignment Based on Genetic Algorithms with new Chromosomes representation

被引：0

作者：

Ben Othman, Mohamed Tahar ^{[1
]}

Abdel-Azim, Gamil ^{[1
]}

机构：

[1] Univ Qassim, Coll Comp, Qasim, Saudi Arabia

来源：

2012 16TH IEEE MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (MELECON) | 2012年

关键词：

Genetics algorithms; Combinatorial Optimization; Sequence alignment; DNA; Computational molecular biology;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Multiple sequence alignment is one of the important research topics of bioinformatics. The objective is to maximize the similarities between them by adding and shuffling gaps. We propose a hybrid algorithm based on genetic (GAs) and 2-optimal algorithms. We are using permutation coding corresponding to represent the solution, and we are studying scoring function for multiple alignments, that is used as fitness function. Our GA is implemented with two selections strategies and different crossovers. The probability of crossover and mutation are set as one. Performance and comparison of the proposed GA is analyzed and the obtained solution qualities are reported.

引用

页码：1030 / 1033

页数：4

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