Cargando…
Permutation-validated principal components analysis of microarray data
BACKGROUND: In microarray data analysis, the comparison of gene-expression profiles with respect to different conditions and the selection of biologically interesting genes are crucial tasks. Multivariate statistical methods have been applied to analyze these large datasets. Less work has been publi...
Autores principales: | Landgrebe, Jobst, Wurst, Wolfgang, Welzl, Gerhard |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2002
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC115254/ https://www.ncbi.nlm.nih.gov/pubmed/11983060 |
Ejemplares similares
-
Component retention in principal component analysis with application to cDNA microarray data
por: Cangelosi, Richard, et al.
Publicado: (2007) -
Validation in Principal Components Analysis Applied to EEG Data
por: Costa, João Carlos G. D., et al.
Publicado: (2014) -
Identification of differentially expressed genes in microarray data in a principal component space
por: Ospina, Luis, et al.
Publicado: (2013) -
Two-part permutation tests for DNA methylation and microarray data
por: Neuhäuser, Markus, et al.
Publicado: (2005) -
Principal components analysis and the reported low intrinsic dimensionality of gene expression microarray data
por: Lenz, Michael, et al.
Publicado: (2016)