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» Robust estimators for expression analysis
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123
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BMCBI
2006
134views more  BMCBI 2006»
15 years 3 months ago
An approach for clustering gene expression data with error information
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...
Brian Tjaden
127
Voted
BMCBI
2010
120views more  BMCBI 2010»
15 years 3 months ago
Modeling expression quantitative trait loci in data combining ethnic populations
Background: Combining data from different ethnic populations in a study can increase efficacy of methods designed to identify expression quantitative trait loci (eQTL) compared to...
Ching-Lin Hsiao, Ie-Bin Lian, Ai-Ru Hsieh, Cathy S...
128
Voted
BMCBI
2006
131views more  BMCBI 2006»
15 years 3 months ago
SIMAGE: simulation of DNA-microarray gene expression data
Background: Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-proce...
Casper J. Albers, Ritsert C. Jansen, Jan Kok, Osca...
176
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BMCBI
2004
169views more  BMCBI 2004»
15 years 3 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
139
Voted
BMCBI
2007
159views more  BMCBI 2007»
15 years 3 months ago
Detecting differential expression in microarray data: comparison of optimal procedures
Background: Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, ...
Elena Perelman, Alexander Ploner, Stefano Calza, Y...