Hybrid Particle Swarm Optimization with Iterative Local Search for DNA Sequence Assembly

作     者：Rajagopal, Indumathy Sankareswaran, Uma Maheswari 

作者机构：Sri Krishna Arts & Sci Coll Dept Comp Technol Coimbatore 641008 Tamil Nadu India 

出 版 物：《CURRENT BIOINFORMATICS》 (生物信息学最新进展)

年 卷 期：2015年第10卷第4期

页      面：393-400页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 09[农学] 

基　　金：Coimbatore Institute of Technology  Coimbatore 

主　　题：Evolutionary algorithms genome sequence assembly inertia weight local search metaheuristics optimization particle swarm optimization smallest position value rule semi-global alignment 

摘      要：This paper proposes a novel hybrid approach to solve the DNA sequence assembly problem by combining particle swarm optimization and iterative local search algorithms. One of the vital challenges in DNA sequence assembly is to arrange a long genome sequence that consists of millions of fragments in accurate order. This is an NP- hard combinatorial optimization problem. The prominence of this paper is to demonstrate how this hybrid algorithms scheme can improve the performance of fragment assembly process. Incorporating iterative local search heuristics in particle swarm optimization algorithm efficiently assembles the fragments by maximizing the overlap score. The performances of the proposed hybrid algorithm were compared with the variants of Particle Swarm Optimization algorithms and other known methodologies. The experimental results show that the proposed hybrid approach produces better results than the other techniques when tested with different sized well-known benchmark instances.