基于多策略人工蜂群的多序列比对算法

多序列比对是生物信息学中最重要和最具挑战性的任务之一.基于多序列比对是NP 完全组合优化问题,引入Tent 混沌初始化种群策略、不同蜂种的邻域搜索策略和锦标赛选择策略等,提出一种基于多策略人工蜂群的多序列比对算法.该算法应用Tent混沌初始化种群策略以使初始个体多样化并获取较好初始解;针对不同蜂种的特性设计不同的邻域搜索策略以平衡算法的全局探索和局部开发能力.同时引入序列比对的蜜源编码方法以适应多序列比对的离散性.实验结果表明,所提出算法的鲁棒性较强,能获取较好的比对性能和生物特性.

Multiple sequence alignment algorithm based on multi-strategy artificial bee colony

Multiple sequence alignment(MSA), known as NP-complete combinatorial optimization problem, is one of the most important and challenging tasks in bioinformatics.A multi-strategy artificial bee colony(MS-ABC) algorithm is proposed for MSA, which is composed of multiple strategies, such as the Tent chaotic initialization population strategy, different neighborhood search strategies and tournament selection strategy.In the MSA-ABC algorithm, the Tent chaotic initialization population strategy is presented to diversify the initial individuals and to obtain good initial solutions.Then, the different neighborhood search strategies for different bee species are designed to balance the global exploration and the local exploitation.Moreover, the food source encoding method is used to adapt discreteness of MSA.The experimental results demonstrate that the proposed algorithm is more robust and can obtain better alignment quality and biological characteristics.