DocumentCode :
2089007
Title :
Web–Enabled Classification of SNPs for Genome–Wide Association Studies
Author :
Tendulkar, Abhijit R. ; Stojanovic, Nikola ; Barber, Robert
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Texas at Arlington, Arlington, TX, USA
fYear :
2008
fDate :
17-20 Dec. 2008
Firstpage :
112
Lastpage :
117
Abstract :
Whole genome association studies of the genetic underpinnings of complex phenotypes, and human diseases in particular, have been steadily gaining momentum over the past several years. Yet, the number of polymorphic sites in the human genome, including, but not limited to, single nucleotide polymorphisms (SNPs) is so large that identifying the combination of these few that have a significant effect on the condition of interest remains an overwhelming task. In this manuscript we present a new networked solution, and a program GeneNAB implementing it, to the computational identification and ranking of SNPs likely to be relevant for the phenotype of interest, genome-wide. We expect that the output of this program will be useful to guide further laboratory and clinical studies of these SNPs.
Keywords :
Internet; biology computing; classification; diseases; genetics; Web-enabled classification; complex phenotypes; genetic underpinnings; genome association studies; human diseases; human genome; polymorphic sites; program GeneNAB; single nucleotide polymorphism; Bioinformatics; Biology computing; Biomedical engineering; Cardiac disease; Computer networks; Computer science; Databases; Genetic engineering; Genomics; Humans; GWAS; Genetic variation; Internet; KEGG; SNP; XML; database; dbSNP; polymorphism;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology, 2008. ICIT '08. International Conference on
Conference_Location :
Bhubaneswar
Print_ISBN :
978-1-4244-3745-0
Type :
conf
DOI :
10.1109/ICIT.2008.65
Filename :
4731309
Link To Document :
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