• 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