DocumentCode :
2737577
Title :
Poster: High-performance computing for mapping disease-related genes
Author :
Valentine-Cooper, William ; Huang, Yungui ; Seok, Sang-Cheol ; Vieland, Veronica
Author_Institution :
Battelle Center for Math. Med., Res. Inst. at Nationwide Children´´s Hosp., Columbus, OH, USA
fYear :
2011
fDate :
3-5 Feb. 2011
Firstpage :
263
Lastpage :
263
Abstract :
Two wide-spread and powerful techniques in human genetic epidemiology are linkage and association analysis. Linkage analysis is used to identify the approximate location of disease-related genes on a map of the human genome, and generally uses pedigree data and large sets of genetic markers. Since the resolution of locality approximations determined using linkage analysis is quite low (spanning millions of base pairs), researchers usually perform additional analyses to improve the accuracy. Association analysis commonly uses large numbers of unrelated individuals or parent-child “trios” rather than pedigree data, but can also be performed based on pedigrees.
Keywords :
cellular biophysics; diseases; genetics; genomics; medical computing; molecular biophysics; association analysis; disease-related gene mapping; genetic markers; high-performance computing; human genetic epidemiology; human genome; linkage analysis; locality approximation; Approximation methods; Bioinformatics; Couplings; Diseases; Genomics; Polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Advances in Bio and Medical Sciences (ICCABS), 2011 IEEE 1st International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-61284-851-8
Type :
conf
DOI :
10.1109/ICCABS.2011.5729917
Filename :
5729917
Link To Document :
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