Modern methods of microarray data analysis are biased towards selecting those genes that display the most pronounced … criteria are needed to supplement the information on differential expression. Three large sets of microarray data on childhood …

Statistical analysis of microarray gene expression data has recently attracted a great deal of attention. One problem … approach to conduct the Cox survival analysis of microarray gene expression data with the focus on models' predictive ability …

microarray gene expression profiles. A compendium is an interactive document that bundles primary data, statistical processing … microarray data set that first has been studied by Huang et al. (2003). …

. One of the most common types of microarray experiments is simply an exploratory study to compare two samples (e.g. tumor … rates than t-statistic-based methods. However, their method was designed mainly for the two-channel microarray, which …

In microarray experiments, several steps may cause sub-optimal quality and the need for quality control is strong …. Often the experiments are complex, with several conditions studied simultaneously. A linear model for paired microarray …

Microarray applications for the study of gene expression are becoming accessible for researchers in more and more … microarray within a level of the subplot treatment. Design B has crossed levels paired on the same microarray. Design C has … levels of the treatment applied to subplots paired on the same microarray within a whole plot. Designs A and B have lower …

We describe the use of a statistical model in a genome-wide microarray-based yeast genetic screen performed by imposing …

A number of microarray studies assume gene expression data to be independent of one another. In this report, we provide … evidence of correlation in cDNA microarray gene expression data using classical power spectral analysis and the sophisticated … assessment of microarray gene expression data prior to inferring differential gene expression. …

In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables …