A cascaded pairwise biomolecular sequence alignment technique using evolutionary algorithm

In computational biology, biological sequence alignment is an important and challenging task for sequence analysis. In this paper, we propose a new sequence alignment technique based on a genetic algorithm (GA) for determining the optimal alignment score for a pair of sequences that could be either DNA or protein sequences. The search space requirement of the proposed genetic-based method, named Cascaded Pairwise Alignment with Genetic Algorithm (CPAGA), is reduced by breaking a large space into smaller subspaces. This is performed by decomposing the sequence pair into multiple segments before starting the alignment procedure. Such decomposition enhances the ability of the search process to reach the global or a near-global optimal solution even for the longer sequences. The method was tested using several DNA/protein sequence pairs. We also compared the alignment score of the CPAGA with that of some well-known and relevant alignment techniques. The performance of the CPAGA method and other relevant techniques was assessed by a set of non-parametric statistical approaches, which suggest a superior performance of CPAGA over the other alignment procedures.