Cargando…
Importance of data structure in comparing two dimension reduction methods for classification of microarray gene expression data
BACKGROUND: With the advance of microarray technology, several methods for gene classification and prognosis have been already designed. However, under various denominations, some of these methods have similar approaches. This study evaluates the influence of gene expression variance structure on th...
Autores principales: | Truntzer, Caroline, Mercier, Catherine, Estève, Jacques, Gautier, Christian, Roy, Pascal |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1831790/ https://www.ncbi.nlm.nih.gov/pubmed/17355634 http://dx.doi.org/10.1186/1471-2105-8-90 |
Ejemplares similares
-
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
por: Bartenhagen, Christoph, et al.
Publicado: (2010) -
Comparative Study of Classification Algorithms for Various DNA Microarray Data
por: Kim, Jingeun, et al.
Publicado: (2022) -
Kernelized partial least squares for feature reduction and classification of gene microarray data
por: Land, Walker H, et al.
Publicado: (2011) -
Dimension reduction with gene expression data using targeted variable importance measurement
por: Wang, Hui, et al.
Publicado: (2011) -
Comparison of classification methods that combine clinical data and high-dimensional mass spectrometry data
por: Truntzer, Caroline, et al.
Publicado: (2014)