Computational intelligence in multiple sequence alignment
International Journal of Intelligent Computing and Cybernetics
ISSN: 1756-378X
Article publication date: 28 March 2008
Abstract
Purpose
Multiple sequence alignment (MSA) is one of essential bioinformatics methods for decoding cis‐regulatory elements in gene regulation, predicting structure and function of proteins and RNAs, reconstructing phylogenetic tree, and other common tasks in biomolecular sequence analysis. The purpose of this paper is to describe briefly the basic concepts and formulations of gapped MSA and un‐gapped motif discovery approaches, and then review computational intelligence (CI) applications in MSA and motif‐finding problems.
Design/methodology/approach
This paper performs exhaustive literature review on the MSA and motif discovery using CI techniques.
Findings
Although CI‐based MSA algorithms were developed nearly a decade ago, most recent CI effort seems attempted to tackle the NP‐complete motif discovery problem. Applications of various CI techniques to solve motif discovery problem, including neural networks, self‐organizing map, genetic algorithms, swarm intelligence and combinations thereof, are surveyed. Finally, the paper concludes with discussion and perspective.
Practical implications
The algorithms and software discussed in this paper can be used to align DNA, RNA and protein sequences, discover motifs, predict functions and structures of protein and RNA sequences, and estimate phylogenetic tree.
Originality/value
The paper contributes to the first comprehensive survey of CI techniques that are applied to MSA and motif discovery.
Keywords
Citation
Bi, C. (2008), "Computational intelligence in multiple sequence alignment", International Journal of Intelligent Computing and Cybernetics, Vol. 1 No. 1, pp. 8-24. https://doi.org/10.1108/17563780810857103
Publisher
:Emerald Group Publishing Limited
Copyright © 2008, Emerald Group Publishing Limited