An improved algorithm for Multiple Sequence Alignment using Particle Swarm Optimization

P. Jagadamba, M. S. Prasad Babu, A. A. Rao, P. Krishna Subba Rao
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引用次数: 9

Abstract

Sequence alignment is one of the challenging problems in the analysis of biological data for identifying the diseases. Numbers of Sequence alignment algorithms are developed to identify highly scoring alignment between the sequences. Many of these sequence alignment algorithms use Dynamic Programming technique. In this paper a new algorithm, namely, Multiple Sequence Alignment using Particle Swarm Optimization (MSAPSO) is proposed to multiple sequence alignment. This algorithm is developed using Particle Swarm Optimization technique instead of Dynamic Programming technique. This algorithm works on both nucleotide sequences and protein sequences. The proposed approach tries to improve the sequence alignment proposed by Needleman Wunsch algorithm.
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基于粒子群优化的多序列比对改进算法
序列比对是识别疾病的生物学数据分析中具有挑战性的问题之一。开发了许多序列比对算法来识别序列之间的高评分比对。许多序列比对算法使用动态规划技术。本文提出了一种基于粒子群优化的多序列比对算法(MSAPSO)。该算法采用粒子群优化技术代替动态规划技术。该算法适用于核苷酸序列和蛋白质序列。该方法对Needleman - Wunsch算法提出的序列比对方法进行了改进。
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