Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
DNA Microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liyin...
Background: In microarray studies researchers are often interested in the comparison of relevant quantities between two or more similar experiments, involving different treatments...
Marta Blangiardo, Alberto Cassese, Sylvia Richards...
Background: A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames) of the yeast Saccharomyces cerevisiae has been systematically constructed....
Chulyun Kim, Sangkyum Kim, Russell Dorer, Dan Xie,...
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...