DocumentCode
2089007
Title
WebEnabled Classification of SNPs for GenomeWide 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
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