• DocumentCode
    1652691
  • Title

    A Haplotype Based Method for Genetic Disease Susceptibility Prediction

  • Author

    Mao, Weidong

  • Author_Institution
    Dept. of Math. & Comput. Sci., Virginia State Univ., Petersburg, VA
  • fYear
    2008
  • Firstpage
    478
  • Lastpage
    481
  • Abstract
    High-throughput single nucleotide polymorphism (SNP) genotyping technologies make massive genotype data, with a large number of individuals, publicly available. Accessibility of genetic data makes genome-wide association studies for complex diseases possible. The susceptibility to complex diseases can be predicted through the analysis of the genetic data and prospective patients can be helped to make informed decisions. With the development of DNA microarray technique, it is possible to access the human genetic information related to specific diseases, but most disease association studies are based on genotypes. This paper uses a combinatorial method to analyze the haplotype data for Crohn´s disease and search disease-associated factors for given case/control samples. A Linear programming based method has been applied to publicly available genotype data on Crohn´s disease for association study and achieved a promising result.
  • Keywords
    DNA; diseases; genetics; graph theory; greedy algorithms; linear programming; molecular biophysics; Crohn´s disease; DNA microarray technique; SNP genotyping technology; combinatorial method; complex disease; genetic data analysis; genetic disease susceptibility prediction; haplotype based method; human genetic information; linear programming; publicly available genotype data; single nucleotide polymorphism; Bioinformatics; DNA; Data analysis; Diseases; Genetics; Genomics; Humans; Linear programming; Mathematics; Proteins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1747-6
  • Electronic_ISBN
    978-1-4244-1748-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2008.116
  • Filename
    4534996