Authors: Gürkan Üstünkar Süreyya ÖzöğürAkyüz Gerhard W Weber Christoph M Friedrich Yeşim Aydın Son
Publish Date: 2011/11/01
Volume: 6, Issue: 6, Pages: 1207-1218
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 featureselection 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 personalizedmedicine approaches and targeted drug discoveriesFor the Alzheimer’s Disease Neuroimaging Initiative Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative ADNI database adniloniuclaedu As such the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report A complete listing of ADNI investigators can be found at http//adniloniuclaedu/wpcontent/uploads/how to apply/ADNI Acknowledgement Listpdf
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