Abstract: Multiple sequence alignment is an unsolved NP-complete combinatorial optimization problem. This paper described a new exhaustive genetic algorithm based on Gap Crossover and Gap Mutation (GC-GM) for multiple sequence alignment by genetic operation on gap matrixes reassembled. The approach was examined by using a set of standard instances taken from the benchmark alignment database BAliBASE. Numerical simulation results were compared with those obtained by using the Clustal W algorithm and showed the effectiveness of the new approach.

Key words: bioinformatics, Multiple Sequence Alignment (MSA), gap, crossover

摘要： 多序列比对问题是生物信息学中尚未解决的一个NP完全的组合优化问题。通过对重新组装的空位矩阵进行遗传操作来实现最优比对，设计了一个新型的基于GC-GM的多序列比对穷举遗传算法。从BAliBASE 比对数据库中选取了一些比对例子进行了模拟计算,并与Clustal-W算法进行了比较，实验表明该算法是有效的。

关键词: 生物信息学, 多序列比对, 空位, 交叉