A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets

BACKGROUND: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifies a relevant subset of genes. Many univariate and multivariate gene selection approaches have been proposed. Frequently...

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Detalles Bibliográficos
Autores principales: Lai, Carmen, Reinders, Marcel JT, van't Veer, Laura J, Wessels, Lodewyk FA
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1569875/
https://www.ncbi.nlm.nih.gov/pubmed/16670007
http://dx.doi.org/10.1186/1471-2105-7-235

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1569875/
https://www.ncbi.nlm.nih.gov/pubmed/16670007
http://dx.doi.org/10.1186/1471-2105-7-235

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