4.6 Article

Tag SNP selection via a genetic algorithm

期刊

JOURNAL OF BIOMEDICAL INFORMATICS
卷 43, 期 5, 页码 800-804

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jbi.2010.05.011

关键词

Single nucleotide polymorphisms; Tag SNP selection problem; Genetic algorithm

资金

  1. University of Tehran

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Single Nucleotide Polymorphisms (SNPs) provide valuable information on human evolutionary history and may lead us to identify genetic variants responsible for human complex diseases. Unfortunately, molecular haplotyping methods are costly, laborious, and time consuming; therefore, algorithms for constructing full haplotype patterns from small available data through computational methods, Tag SNP selection problem, are convenient and attractive. This problem is proved to be an NP-hard problem, so heuristic methods may be useful. In this paper we present a heuristic method based on genetic algorithm to find reasonable solution within acceptable time. The algorithm was tested on a variety of simulated and experimental data. In comparison with the exact algorithm, based on brute force approach, results show that our method can obtain optimal solutions in almost all cases and runs much faster than exact algorithm when the number of SNP sites is large. Our software is available upon request to the corresponding author. (c) 2010 Elsevier Inc. All rights reserved.

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