Affiliations: [a] Department of Computer Science, NationalUniversity of Computer and Emerging Science Lahore, Pakistan
| [b]
University of Management & Technology, Lahore, Pakistan
| [c]
Fordham University, New York, USA
Correspondence:
[*]
Corresponding author. Hafiz Asadul Rehman, Department of Computer Science, National University of Computer and Emerging Science Lahore, Pakistan. E-mail: [email protected].
Abstract: Discovering structural, functional and evolutionary information in biological sequences have been considered as a core research area in Bioinformatics. Multiple Sequence Alignment (MSA) tries to align all sequences in a given query set to provide us ease in annotation of new sequences. Traditional methods to find the optimal alignment are computationally expensive in real time. This research presents an enhanced version of Bird Swarm Algorithm (BSA), based on bio inspired optimization. Enhanced Bird Swarm Align Algorithm (EBSAA) is proposed for multiple sequence alignment problem to determine the optimal alignment among different sequences. Twenty-one different datasets have been used in order to compare performance of EBSAA with Genetic Algorithm (GA) and Particle Swarm Align Algorithm (PSAA). The proposed technique results in better alignment as compared to GA and PSAA in most of the cases.
