Multiple Sequence Alignment by Immune Artificial System

In this paper we describe ClonAlign a new iterative approach for the well-known bioinformatics problem: multiple sequence alignment (MSA). It is a significant task which is used to solve other problems like construction of phylogenetic trees and structural and functional prediction of proteins, etc. In this work, MSA is viewed as an optimization problem for which a new framework relying on Natural Computing is proposed. The originality in our approach consists in using an artificial immune system (AIS) to deal with the MSA problem, the general motivation is the ability to optimise any objective function that one can invent. Using the BAUBASE benchmark database, the experimental results have shown the effectiveness of the proposed framework and its ability to achieve good quality solutions comparing to other existing packages.