Multiple sequence alignment using enhanced bird swarm align algorithm-Reference-Cited by-同舟云学术

Multiple sequence alignment using enhanced bird swarm align algorithm

Published:2021-08-11 Issue:1 Volume:41 Page:1097-1114
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Rehman Hafiz Asadul¹,Zafar Kashif¹,Khan Ayesha²,Imtiaz Abdullah³

Affiliation:

1. Department of Computer Science, NationalUniversity of Computer and Emerging Science Lahore, Pakistan

2. University of Management & Technology, Lahore, Pakistan

3. Fordham University, New York, USA

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.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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