Cellular Automata-Based PSO Algorithm for Aligning Multiple Molecular Sequences | IGI Global Scientific Publishing
Welcome to the InfoSci Platform
Reference Hub1
Cellular Automata-Based PSO Algorithm for Aligning Multiple Molecular Sequences

Cellular Automata-Based PSO Algorithm for Aligning Multiple Molecular Sequences

Jayapriya Jayakumar, Michael Arock
Copyright: © 2016 |Volume: 7 |Issue: 1 |Pages: 15
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781466690806|DOI: 10.4018/IJAEC.2016010101
Cite Article Cite Article

MLA

Jayakumar, Jayapriya, and Michael Arock. "Cellular Automata-Based PSO Algorithm for Aligning Multiple Molecular Sequences." IJAEC vol.7, no.1 2016: pp.1-15. https://doi.org/10.4018/IJAEC.2016010101

APA

Jayakumar, J. & Arock, M. (2016). Cellular Automata-Based PSO Algorithm for Aligning Multiple Molecular Sequences. International Journal of Applied Evolutionary Computation (IJAEC), 7(1), 1-15. https://doi.org/10.4018/IJAEC.2016010101

Chicago

Jayakumar, Jayapriya, and Michael Arock. "Cellular Automata-Based PSO Algorithm for Aligning Multiple Molecular Sequences," International Journal of Applied Evolutionary Computation (IJAEC) 7, no.1: 1-15. https://doi.org/10.4018/IJAEC.2016010101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

In Bioinformatics, sequence analysis is the basic important concept that provides information for structural and functional analysis. Multiple Sequence Alignment (MSA) is a keystone problem in the sequence analysis that is used for constructing phylogenetic tree, finding motif, gene expression, etc. Basically, all biological computation issues are NP-complete problems. In this paper, a novel approach using Cellular Automata (CA) and Particle Swarm Optimization (PSO) techniques are proposed for MSA problem. Both of these techniques handle NP-complete problems very skillfully. For experimental analysis, the BaliBASE benchmark dataset and two scoring functions Sum of Pairs (SP) and Total Column (TC) are considered in this paper for calculating the similarity among the sequences. Using the Wilcoxon matched pair signed rank test the significance of the proposed algorithm (PSOCA) is explained. This algorithm is compared with PSO, genetic algorithm and the state-of-the-art techniques. The results show that the PSOCA approach yields better performance than other state-of-the-art algorithms.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global Scientific Publishing bookstore.