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» Bayesian meta-analysis models for microarray data: a compara...
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BMCBI
2008
125views more  BMCBI 2008»
13 years 6 months ago
MAID : An effect size based model for microarray data integration across laboratories and platforms
Background: Gene expression profiling has the potential to unravel molecular mechanisms behind gene regulation and identify gene targets for therapeutic interventions. As microarr...
Ivan Borozan, Limin Chen, Bryan Paeper, Jenny E. H...
BMCBI
2005
135views more  BMCBI 2005»
13 years 6 months ago
A robust two-way semi-linear model for normalization of cDNA microarray data
Background: Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative e...
Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzel...
BMCBI
2006
150views more  BMCBI 2006»
13 years 6 months ago
Instance-based concept learning from multiclass DNA microarray data
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Daniel P. Berrar, Ian Bradbury, Werner Dubitzky
BMCBI
2004
169views more  BMCBI 2004»
13 years 6 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...
BMCBI
2006
153views more  BMCBI 2006»
13 years 6 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...