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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2008
259views more  BMCBI 2008»
15 years 1 months ago
DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcripti
Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted w...
Evert-Jan Blom, Sacha A. F. T. van Hijum, Klaas J....
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
15 years 2 months ago
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
Microarray experiments have been extensively used for simultaneously measuring DNA expression levels of thousands of genes in genome research. A key step in the analysis of gene e...
Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvri...
BMCBI
2007
148views more  BMCBI 2007»
15 years 1 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...
BMCBI
2010
130views more  BMCBI 2010»
15 years 1 months ago
Analysis of DNA strand-specific differential expression with high density tiling microarrays
Background: DNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA) contain probes for annotated open rea...
Luis Quintales, Mar Sánchez, Francisco Ante...
BMCBI
2004
106views more  BMCBI 2004»
15 years 1 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...