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Abstract
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Article Information:
A Refined MSAPSO Algorithm for Improving Alignment Score
K. Arulmani, M. Guru Prasad, R. Hariharan and N. Sivasankaran
Corresponding Author: K. Arulmani
Submitted: April 18, 2012
Accepted: May 14, 2012
Published: November 01, 2012 |
Abstract:
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Multiple Sequence Alignment (MSA) is an important part of bioinformatics domain in which two
or more biological sequences, such as proteins, DNA or RNA are aligned sequentially. This Multiple Sequence
Alignment plays a vital role in the generation of phylogenetic tree as well as predicting the protein structure.
The protein sequences are generally used to generate the Phylogenetic tree. To attain this, we have transformed
the protein sequences into numerical values using a substitution matrix and optimized those numerical values
using Particle Swarm Optimization (PSO) method. The PSO is a meta-heuristic computational approach for
performing optimization. The PSO uses the random values for pair-wise sequence alignment, resulting in
decrease in the rate of the residues matched. This study presents how the rate of matching process can be
improved by replacing the random values with the substitution matrix values if there is a positive value in the
matrix. As result of this, we have also found that the score of the alignment sequence has been improved.
Key words: BLOSUM50 substitution matrix , MSAPSO algorithm, multiple sequence alignment, particle swarm optimization , phylogenetic tree, protein sequence, velocity matrix
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Cite this Reference:
K. Arulmani, M. Guru Prasad, R. Hariharan and N. Sivasankaran, . A Refined MSAPSO Algorithm for Improving Alignment Score. Research Journal of Applied Sciences, Engineering and Technology, (21): 4404-4407.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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