Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Background: To identify differentially expressed genes across experimental conditions in oligonucleotide microarray experiments, existing statistical methods commonly use a summar...
Leah Barrera, Chris Benner, Yong-Chuan Tao, Elizab...
Background: The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and ...
Dominik Lutter, Peter Ugocsai, Margot Grandl, Evel...
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
Background: Used alone, the MAS5.0 algorithm for generating expression summaries has been criticized for high False Positive rates resulting from exaggerated variance at low inten...
Stuart D. Pepper, Emma K. Saunders, Laura E. Edwar...