Abstract

Abstract. This paper presents an immune inspired algorithm, to tackle and optimize the multiple sequence alignment (MSA) problem. MSA is one of the most important tasks in biological sequence analysis. Although this paper focuses on protein alignments, most of the discussion and methodology may be also applied to DNA alignments. The presented algorithm, called IMSA, incorporates two new strategies to create the initial population, and specific ad-hoc mutation operators. It is based on the classical weighted sum of pairs as objective function, to evaluate a given candidate alignments. IMSA was tested using both classical benchmarks of BAliBASE (versions 1.0 and 2.0.), and experimental results indicate that it is comparable with state-of-art MSA, in terms of quality of alignments, SP and CS score values. The main novelty of IMSA is the ability of generating more than a single sub-optimal alignment, for every MSA instance; this behaviour is due to the stochastic nature of the algorithm and of the populations evolved during the convergence process. This feature will help the decision maker to assess and select the biologically relevant multiple sequence alignment.

Citations