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Identifying the combination of genetic factors that determine susceptibility to cervical cancer
- Source :
- IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society. 8(1)
- Publication Year :
- 2004
-
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. The web site associated with this study is http://140.115.155.8/FactorAnalysis/.
- Subjects :
- Population
Uterine Cervical Neoplasms
Single-nucleotide polymorphism
Bioinformatics
Polymorphism, Single Nucleotide
Risk Assessment
Sensitivity and Specificity
medicine
Genetic predisposition
SNP
Humans
Genetic Predisposition to Disease
Diagnosis, Computer-Assisted
Genetic Testing
Electrical and Electronic Engineering
education
Phylogeny
Retrospective Studies
Cervical cancer
education.field_of_study
Internet
Gene Expression Profiling
HPV infection
Case-control study
Reproducibility of Results
Retrospective cohort study
Bayes Theorem
General Medicine
medicine.disease
Computer Science Applications
Case-Control Studies
Female
Algorithms
Biotechnology
Microsatellite Repeats
Subjects
Details
- ISSN :
- 10897771
- Volume :
- 8
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society
- Accession number :
- edsair.doi.dedup.....8795af7778de5424a8e4a188af4685a8