Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
In studies that use DNA arrays to assess changes in gene expression, it is preferable to measure the significance of treatment effects on a group of genes from a pathway or functi...
Taewon Lee, Varsha G. Desai, Cruz Velasco, Robert ...
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...