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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Detalles Bibliográficos
Autores principales: Waldron, Levi, Pintilie, Melania, Tsao, Ming-Sound, Shepherd, Frances A., Huttenhower, Curtis, Jurisica, Igor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3232376/
https://www.ncbi.nlm.nih.gov/pubmed/22156367
http://dx.doi.org/10.1093/bioinformatics/btr591

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3232376/
https://www.ncbi.nlm.nih.gov/pubmed/22156367
http://dx.doi.org/10.1093/bioinformatics/btr591

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