Supervised learning-based tagSNP selection for genome-wide disease classifications

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dc.contributor.authorLiu, Qingzhong
dc.contributor.authorSung, Andrew H.
dc.contributor.authorChen, Zhongxue
dc.contributor.authorYang, Mary Qu
dc.contributor.authorHuang, Xudong
dc.contributor.authorYang, Jack
dc.date.accessioned2022-01-25T17:08:14Z
dc.date.available2022-01-25T17:08:14Z
dc.date.issued2007-07-25
dc.descriptionThe article was originally published by BMC Genomics. doi:10.1186/1471-2164-9-S1-S6
dc.description.abstractComprehensive evaluation of common genetic variations through association of single nucleotide polymorphisms (SNPs) with complex human diseases on the genome-wide scale is an active area in human genome research. One of the fundamental questions in a SNP-disease association study is to find an optimal subset of SNPs with predicting power for disease status. To find that subset while reducing study burden in terms of time and costs, one can potentially reconcile information redundancy from associations between SNP markers
dc.description.sponsorshipResearch supports received from ICASA (Institute for Complex Additive Systems Analysis, a division of New Mexico Tech) and the Radiology Department of Brigham and Women's Hospital (BWH) are gratefully acknowledged. The authors highly appreciate Dr. Liang at SUNY-Buffalo for her invaluable help and insightful discussion during this study and Ms. Kim Lawson at BWH Radiology Department for her manuscript editing and very constructive comments.
dc.description.subjectSupervised Recursive Feature Additions
dc.description.subjectSupport Vector bases Recursive Feature Addition
dc.description.subjectcomplex disease
dc.description.subjectgenetics
dc.description.subjectdisease predictions
dc.identifier.citationLiu Q, Yang J, Chen Z, Yang M, Sung AH, Huang X (2008). Supervised-learning based TagSNPs for genome-wide disease classification, BMC Genomics 9 (Suppl 1): S6. doi:10.1186/1471-2164-9-S1-S6
dc.identifier.urihttps://hdl.handle.net/20.500.11875/3263
dc.language.isoen_US
dc.publisherBIomed Central
dc.subjectassociation of single nucleotide polymorphisms (SNPs)
dc.subjectpredicting power
dc.subjectactive area
dc.titleSupervised learning-based tagSNP selection for genome-wide disease classifications
dc.typeArticle

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