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Support Vector Machines with L-1 penalty for detecting gene-gene interactions
Shen, Yuanyuan2; Liu, Zhe3; Ott, Jurg1
2012
Source PublicationINTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
ISSN1748-5673
SubtypeArticle
Volume6Issue:5Pages:463-470
AbstractInteractions among genetic variants are likely to affect risk for human complex diseases, and their identification should increase the power to detect disease-associated variants and elucidate biological pathways underlying diseases. We propose a two-stage approach:
Keywordgenome-wide association study human complex disease gene-gene interaction SVM support vector machine model selection L-1 penalty two-stage method data mining bioinformatics
Indexed BySCI
Language英语
WOS IDWOS:000309610700001
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/13423
Collection中国科学院心理健康重点实验室
Affiliation1.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Beijing 100101, Peoples R China
2.Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
3.Univ Chicago, Dept Stat, Chicago, IL 60637 USA
Recommended Citation
GB/T 7714
Shen, Yuanyuan,Liu, Zhe,Ott, Jurg. Support Vector Machines with L-1 penalty for detecting gene-gene interactions[J]. INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS,2012,6(5):463-470.
APA Shen, Yuanyuan,Liu, Zhe,&Ott, Jurg.(2012).Support Vector Machines with L-1 penalty for detecting gene-gene interactions.INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS,6(5),463-470.
MLA Shen, Yuanyuan,et al."Support Vector Machines with L-1 penalty for detecting gene-gene interactions".INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS 6.5(2012):463-470.
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