A combination of PSO and K-means methods to solve haplotype reconstruction problem

Authors:
Sarah Sharifian-R;Ardeshir Baharian;Ehsan Asgarian;Ammar Rasooli
Affiliations:
School of Mathematics, Statistics and Computer Science, Tarbiat Modares University, Tehran, Iran;Department of Computer Engineering, Ferdowsi University of Mashhad, Iran;Department of Computer engineering, Sharif University of Technology, Tehran, Iran;Department of applied mathematics, Iran University of Science and Technology
Venue:
IIT'09 Proceedings of the 6th international conference on Innovations in information technology
Year:
2009

Citing 5
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Abstract

Disease association study is of great importance among various fields of study in bioinformatics. Computational methods happen to be advantageous specifically when experimental approaches fail to obtain accurate results. Haplotypes are believed to be the most responsible biological data for genetic diseases. In this paper, the problem ofreconstructing haplotypes from error-containing SNP fragments is discussed For this purpose, two new methods have been proposed by a combination of k-means clustering and particle swarm optimization algorithm. The methods and their implementation results on real biological and simulation datasets are represented which shows that they outperform the methods used alone.