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» Inferring Genetic Networks from Microarray Data
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BMCBI
2005
98views more  BMCBI 2005»
14 years 11 months ago
The effects of normalization on the correlation structure of microarray data
Background: Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test-...
Xing Qiu, Andrew I. Brooks, Lev Klebanov, Andrei Y...
91
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RECOMB
2005
Springer
16 years 2 days ago
Causal Inference of Regulator-Target Pairs by Gene Mapping of Expression Phenotypes
Background: Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, ...
David Kulp, Manjunatha Jagalur
BMCBI
2008
160views more  BMCBI 2008»
14 years 12 months ago
A comparison of four clustering methods for brain expression microarray data
Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...
Alexander L. Richards, Peter Holmans, Michael C. O...
BMCBI
2007
182views more  BMCBI 2007»
14 years 11 months ago
Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data
Background: ChIP-chip data, which indicate binding of transcription factors (TFs) to DNA regions in vivo, are widely used to reconstruct transcriptional regulatory networks. Howev...
Wei-Sheng Wu, Wen-Hsiung Li, Bor-Sen Chen
BMCBI
2004
106views more  BMCBI 2004»
14 years 11 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...