A major challenge in microarray classification and biomarker discovery is dealing with small-sample high-dimensional data where the number of genes used as features is typically o...
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...
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...