Multiple sequence alignment algorithm based on a dispersion graph and ant colony algorithm

In this article, we describe a representation for the processes of multiple sequences alignment (MSA) and used it to solve the problem of MSA. By this representation, we took every possible aligning result into account by defining the representation of gap insertion, the value of heuristic information in every optional path and scoring rule. On the basis of the proposed multidimensional graph, we used the ant colony algorithm to find the better path that denotes a better aligning result. In our article, we proposed the instance of three-dimensional graph and four-dimensional graph and advanced a special ichnographic representation to analyze MSA. It is yet only an experimental software, and we gave an example for finding the best aligning result by three-dimensional graph and ant colony algorithm. Experimental results show that our method can improve the solution quality on MSA benchmarks.