Paper Info
Title
Selection of representative SNP sets for genome-wide association studies: a metaheuristic approach
Abstract
After the completion of Human Genome Project in 2003, it is now possible to associate genetic variations in the human genome with common and complex diseases. The current challenge now is to utilize the genomic data efficiently and to develop tools to improve our understanding of etiology of complex diseases. Many of the algorithms needed to deal with this task were originally developed in management science and operations research (OR). One application is to select a subset of the Single Nucleotide Polymorphism (SNP) biomarkers from the whole SNP set that is informative and small enough for subsequent association studies. In this paper, we present an OR application for representative SNP selection that implements our novel Simulated Annealing (SA) based feature-selection algorithm. We hope that our work will facilitate reliable identification of SNPs that are involved in the etiology of complex diseases and ultimately support timely identification of genomic disease biomarkers and the development of personalized-medicine approaches and targeted drug discoveries.
Year
DOI
Venue
2012
10.1007/s11590-011-0419-7
Optimization Letters
Keywords
Field
DocType
Simulated annealing, Feature selection, Representative SNP selection, SNP-complex disease association, Bioinformatics, OR in computational biology
Data mining,Disease,Mathematical optimization,Feature selection,Genome-wide association study,Genetic association,Single-nucleotide polymorphism,Human genome,Computational biology,SNP,Mathematics,Metaheuristic
Journal
Volume
Issue
ISSN
6
6
1862-4480
Citations 
PageRank 
References 
3
0.42
14
Authors
5
Name
Order
Citations
PageRank
Gürkan Üstünkar171.56
Süreyya Özöğür-Akyüz2334.04
Gerhard-wilhelm Weber321036.23
Christoph M. Friedrich418625.44
Yesim Aydin Son552.23