一种求解MSA问题的自适应遗传算法

多序列比对(MSA)在生物信息学研究中占有重要地位，MSA问题是一个典型的NP问题，遗传算法是求解NP完全问题的一种有效方法。文章针对MSA问题，提出了一种新型自适应遗传算法，根据群体的多样性自适应调节变异概率，有效消除了算法中的欺骗性条件，使用突变算子来确保算法的搜索能力。整个算法模拟了自然界进化的周期性，较好的解决了群体的多样性和收敛深度的矛盾。算法的分析和测试表明，该算法是有效的。

An Adaptive Genetic Algorithm for Multiple Sequence Alignment

Multiple sequence alignment (MSA) has great importance in the field of Bioinformatics, MSA is a typical NP-Complete problem, and geneti algorithms (GAs) is the effective method for solving NP-Complete. In this paper, an adaptive algorithm has been presented to solve MSA, which can chang the possibility of the mutation operators. In this way, algorithms can eliminate effectively the deceptive conditions. In addition, a specific cataclysm operato is designed to ensure its capability of searching. The algorithm simulates the recurrence of nature evolution process, and solve the contradiction between th diversity of population and the convergence speed .As it has been proved by analysis and test; a better result is obtained by the adaptive genetic algorithm.