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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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/.

Original languageEnglish
Title of host publicationProceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004
Pages325-330
Number of pages6
StatePublished - 2004
EventProceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 - Taichung, Taiwan
Duration: 19 May 200421 May 2004

Publication series

NameProceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004

Conference

ConferenceProceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004
Country/TerritoryTaiwan
CityTaichung
Period19/05/0421/05/04

Keywords

  • Bayesian Network
  • Cervical Cancer
  • Decision tree
  • Genetic Factors

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