title: Identifying the combination of genetic factors that determine susceptibility to cervical cancer.
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, single-nucleotide polymorphism (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.
authors.affiliation: Department of Life Science, National Central University, Jhongli City 320, Taiwan, ROC. horng@db.csie.ncu.edu.tw
authors.forename: Jorng-Tzong
authors.initials: JT
authors.lastname: Horng
authors.forename: K C
authors.initials: KC
authors.lastname: Hu
authors.forename: Li-Cheng
authors.initials: LC
authors.lastname: Wu
authors.forename: Hsien-Da
authors.initials: HD
authors.lastname: Huang
authors.forename: Feng-Mao
authors.initials: FM
authors.lastname: Lin
authors.forename: S L
authors.initials: SL
authors.lastname: Huang
authors.forename: H C
authors.initials: HC
authors.lastname: Lai
authors.forename: T Y
authors.initials: TY
authors.lastname: Chu
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016022:Case-Control Studies; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005820:Genetic Testing / Q000379:methods*; D006801:Humans; D020407:Internet; D018895:Microsatellite Repeats / Q000235:genetics; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012680:Sensitivity and Specificity; D002583:Uterine Cervical Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000235:genetics*