• DocumentCode
    3230214
  • Title

    Identifying the combination of genetic factors that determine susceptibility to cervical cancer

  • Author

    Horng, Jorng-Tzong ; Hu, Kai-Chih ; Wu, Li-Cheng ; Huang, Hsien-Da ; Lai, Horn-Cheng ; Chu, Ton-Yuen

  • Author_Institution
    Dept. of Comput. Sci. & Information Eng., Nat. Central Univ., Chung-li, Taiwan
  • fYear
    2004
  • fDate
    19-21 May 2004
  • Firstpage
    325
  • Lastpage
    330
  • Abstract
    Cervical cancer is common among women all over the world. Although infection with high-risk types of human papillomavirus (HPV) has been identified as the primary cause of cervical cancer, only some of those infected go on to develop cervical cancer. Obviously, the progression from HPV infection to cancer involves other environmental and host factors. Recent population-based twin and family studies have demonstrated the importance of the hereditary component of cervical cancer, associated with genetic susceptibility. Consequently, SNP markers and microsatellites should be considered genetic factors for determining what combinations of genetic factors are involved in precancerous changes to cervical cancer. This study employs a Bayesian network and four different decision tree algorithms, and compares the performance of these learning algorithms. The results of this study raise the possibility of investigations that could identify combinations of genetic factors, such as SNPs and microsatellites, that influence the risk associated with common complex multifactorial diseases, such as cervical cancer. The web site associated with this study is http://dblab8.csie.ncu.edu.tw/FactorAnalysis/.
  • Keywords
    Bayes methods; biology computing; cancer; decision trees; genetics; gynaecology; medical computing; Bayesian network; SNP; cervical cancer; decision tree algorithms; genetic factors; genetic susceptibility; hereditary component; human papillomavirus; microsatellites; single nucleotide polymorphism; Amino acids; Bayesian methods; Bioinformatics; Cervical cancer; Decision trees; Genetics; Genomics; Humans; Lesions; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Bioengineering, 2004. BIBE 2004. Proceedings. Fourth IEEE Symposium on
  • Print_ISBN
    0-7695-2173-8
  • Type

    conf

  • DOI
    10.1109/BIBE.2004.1317361
  • Filename
    1317361