Cargando…
Regularized gene selection in cancer microarray meta-analysis
BACKGROUND: In cancer studies, it is common that multiple microarray experiments are conducted to measure the same clinical outcome and expressions of the same set of genes. An important goal of such experiments is to identify a subset of genes that can potentially serve as predictive markers for ca...
Autores principales: | Ma, Shuangge, Huang, Jian |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2631520/ https://www.ncbi.nlm.nih.gov/pubmed/19118496 http://dx.doi.org/10.1186/1471-2105-10-1 |
Ejemplares similares
-
Regularized binormal ROC method in disease classification using microarray data
por: Ma, Shuangge, et al.
Publicado: (2006) -
Supervised group Lasso with applications to microarray data analysis
por: Ma, Shuangge, et al.
Publicado: (2007) -
Additive risk survival model with microarray data
por: Ma, Shuangge, et al.
Publicado: (2007) -
Identification of genes associated with multiple cancers via integrative analysis
por: Ma, Shuangge, et al.
Publicado: (2009) -
Assessing stability of gene selection in microarray data analysis
por: Qiu, Xing, et al.
Publicado: (2006)