Title :
Chaos-differential Evolution for Multiple Sequence Alignment
Author_Institution :
Sch. of Math. & Comput. Sci., Guangdong Univ. of Bus. Studies, Guangzhou, China
Abstract :
Multiple sequence alignment is one of the most important and challenging problem in bioinformatics, which is known as NP-hard problem. In this paper, a chaos-differential evolution (CDE) is proposed to solve MSA. In the proposed CDE algorithm, DE and chaos are hybridized to combine the evolutionary searching ability of DE and overcoming local optima of chaotic local search. Simulation shows that novel algorithm has superior performance compared to other existing algorithms.
Keywords :
bioinformatics; chaos; computational complexity; evolutionary computation; search problems; NP-hard problem; bioinformatics; chaos-differential evolution; chaotic local search; evolutionary searching ability; multiple sequence alignment; Bioinformatics; Chaos; Computational intelligence; Evolution (biology); Information technology; Mathematics; NP-hard problem; Optimization methods; Particle swarm optimization; Sequences; Multiple Sequence Alignment; chaos; differential evolution; local optima;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.511
