A framework for significance analysis of gene expression data using dimension reduction methods

BACKGROUND: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, identification of features that correlate with continuous dependent variables is more difficult using these methods, and lon...

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Detalles Bibliográficos
Autores principales: Gidskehaug, Lars, Anderssen, Endre, Flatberg, Arnar, Alsberg, Bjørn K
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2194745/
https://www.ncbi.nlm.nih.gov/pubmed/17877799
http://dx.doi.org/10.1186/1471-2105-8-346

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2194745/
https://www.ncbi.nlm.nih.gov/pubmed/17877799
http://dx.doi.org/10.1186/1471-2105-8-346

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