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BMCBI
2006
153views more  BMCBI 2006»
12 years 3 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
BMCBI
2006
130views more  BMCBI 2006»
12 years 3 months ago
CARMA: A platform for analyzing microarray datasets that incorporate replicate measures
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
BMCBI
2004
135views more  BMCBI 2004»
12 years 3 months ago
Determination of the differentially expressed genes in microarray experiments using local FDR
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
Julie Aubert, Avner Bar-Hen, Jean-Jacques Daudin, ...
CSDA
2007
151views more  CSDA 2007»
12 years 3 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show signi´Čücant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
BMCBI
2006
154views more  BMCBI 2006»
12 years 3 months ago
An improved procedure for gene selection from microarray experiments using false discovery rate criterion
Background: A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are o...
James J. Yang, Mark C. K. Yang
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