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Optimized application of penalized regression methods to diverse genomic data

Motivation: Penalized regression methods have been adopted widely for high-dimensional feature selection and prediction in many bioinformatic and biostatistical contexts. While their theoretical properties are well-understood, specific methodology for their optimal application to genomic data has no...

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書誌詳細
主要な著者: Waldron, Levi, Pintilie, Melania, Tsao, Ming-Sound, Shepherd, Frances A., Huttenhower, Curtis, Jurisica, Igor
フォーマット: Artigo
言語:Inglês
出版事項: Oxford University Press 2011
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC3232376/
https://ncbi.nlm.nih.gov/pubmed/22156367
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btr591
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