A Method for Multiple Sequence Alignment Based on Particle Swarm Optimization

Sequence Alignment is a basic information disposal method in Bioinformatics. However, it is difficult to deal with multiple sequence alignment problem(MSA). In this paper, an improved particle swarm optimization is designed to solve MSA. In the algorithm, each particle represents an alignment and flies to the particle which has the best solution by some rules. Moreover, in order to expand the diversity of the algorithm and enhance the possibility of finding the optimal solution, three operators are designed, that is, gaps deletion, gaps insertion, and local search operator. Simulation results show that for MSA proposed algorithm is superior to Clustal X.

• Type: Conference
• Year: 2009
• Where: ICIC
• Authors: Fasheng Xu, Yuehui Chen
• Keywords: Applied Computing, ICIC 2009, Multiple Sequence Alignment, Particle Swarm Optimization, Sequence Alignment