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BMCBI
2008
98views more  BMCBI 2008»
13 years 8 months ago
Empirical Bayes models for multiple probe type microarrays at the probe level
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Magnus Åstrand, Petter Mostad, Mats Rudemo
BMCBI
2006
169views more  BMCBI 2006»
13 years 8 months ago
Beyond microarrays: Finding key transcription factors controlling signal transduction pathways
Background: Massive gene expression changes in different cellular states measured by microarrays, in fact, reflect just an "echo" of real molecular processes in the cell...
Alexander E. Kel, Nico Voss, Ruy Jauregui, Olga V....
BMCBI
2007
130views more  BMCBI 2007»
13 years 8 months ago
A robust measure of correlation between two genes on a microarray
Background: The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particula...
Johanna S. Hardin, Aya Mitani, Leanne Hicks, Brian...
BMCBI
2010
132views more  BMCBI 2010»
13 years 8 months ago
Parallel multiplicity and error discovery rate (EDR) in microarray experiments
Background: In microarray gene expression profiling experiments, differentially expressed genes (DEGs) are detected from among tens of thousands of genes on an array using statist...
Wayne Wenzhong Xu, Clay J. Carter
BMCBI
2004
149views more  BMCBI 2004»
13 years 7 months ago
MiCoViTo: a tool for gene-centric comparison and visualization of yeast transcriptome states
Background: Information obtained by DNA microarray technology gives a rough snapshot of the transcriptome state, i.e., the expression level of all the genes expressed in a cell po...
Gaëlle Lelandais, Philippe Marc, Pierre Vince...