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: A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two co...
James J. Chen, Chen-An Tsai, ShengLi Tzeng, Chun-H...
Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed ...
Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...