An Improved Ant Colony Algorithm for DNA Sequence Alignment

Abstract

DNA sequence alignment forms an important basis for bioinformatics. Developing accurate sequence alignment algorithms remains to be a very challenging computational problem. When applied to sequence alignment, the traditional ant colony algorithm is limited to aligning sequences of similar length and may cause a local optimum. An improved sequence alignment method based on the ant colony algorithm was brought forward in this paper. The new method could avoid a local optimum and remove especially the paths' scores of great difference by regulating the initial and final positions of ants and by modifying pheromones in different times. Consequently, our method has the ability of aligning sequences with very different lengths and avoiding the local optimum caused by the traditional algorithm. The sequence alignment results suggest that our improved ant colony algorithm is efficient and feasible in DNA sequence alignment.