A Review on Application of Particle Swarm Optimization in Bioinformatics

ISSN: 2212-392X (Online)
ISSN: 1574-8936 (Print)

Volume 10, 5 Issues, 2015

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Current Bioinformatics

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Alessandro Giuliani
Istituto Superiore di Sanit√° (Italian NIH) Environment and Health Dept

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A Review on Application of Particle Swarm Optimization in Bioinformatics

Current Bioinformatics, Volume 9 (E-pub ahead of print)

Author(s): Shikha Agrawal and Sanjay Silakari.

Affiliation: Department of Computer Science and Engineering, University Institute of Technology, Rajiv Gandhi Proudyogiki Vishwavidhyalaya, Bhopal (M.P.), India.


Bioinformatics is an emerging interdisciplinary research area which holds great promise for the advancement of research and development in complex area such as medicine, biology, agriculture, environment, public health, drug design and so on. It is a blend of computer science and molecular biology. Most of the problems in bioinformatics are NP hard in nature so researchers have used soft computing and artificial intelligence techniques to solve these problems. Recently the use of Swarm Intelligence techniques for solving bioinformatics problems has been gaining the attention of researchers because of their ability to generate low cost, approximate, good solutions. Among various algorithms of Swarm Intelligence, Particle Swarm Optimization is used in many applications and has proved to be very effective. This paper reviews and discusses some representative methods to provide inspiring examples to illustrate basic concept of PSO and how PSO had been applied to solve bioinformatics problems. These representative examples include RNA Secondary Structure Prediction, Gene Clustering, Phylogenetic Tree Construction, Energy Minimization and Protein Modeling. The aim of this paper is to provide an overall understanding of PSO and its place in bioinformatics so as to motivate researchers to develop new applications and new concepts.

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Article Details

Volume: 9
First Page: 1
Page Count: 1
DOI: 10.2174/1574893609666140515003132

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