An Intelligent System for Multiple Sequences Alignment

This paper provides an intelligent system, a fuzzy-genetic algorithm (FGA) with local search, for multiple sequences alignment. The general multiple sequence alignment, known as NP-hard problem, refers to search for maximal similarity in three or more sequences. The proposed algorithm is to enhance the performance of genetic algorithm by incorporating local search and fuzzy set theory for multiple sequence alignment. In the proposed algorithm, genetic algorithms perform a multiple directional search by maintaining a set of solutions. Local search operators are performed to explore the neighborhood in an attempt to enhance the fitness of the solution in a local manner. Moreover, fuzzy set theory is designed to dynamically adjust the probability of crossover, mutation and local search during evolutionary process. Results from our experiments indicate that our approach can obtain good performance in the majority of data sets with both low similarity and high diversity