標題: Identifying the combination of genetic factors that determine susceptibility to cervical cancer
作者: Horng, JT
Hu, KC
Wu, LC
Huang, HD
Lin, FM
Huang, SL
Lai, HC
Chu, TY
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
關鍵字: bayesian network;cervical cancer;decision tree;genetic factors
公開日期: 1-三月-2004
摘要: 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.
URI: http://dx.doi.org/10.1109/TITB.2004.824738
http://hdl.handle.net/11536/26963
ISSN: 1089-7771
DOI: 10.1109/TITB.2004.824738
期刊: IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE
Volume: 8
Issue: 1
起始頁: 59
結束頁: 66
顯示於類別:期刊論文


文件中的檔案:

  1. 000220158000007.pdf