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BMCBI
2011
14 years 1 months ago
Evaluating methods for ranking differentially expressed genes applied to MicroArray Quality Control data
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Koji Kadota, Kentaro Shimizu
WCE
2007
14 years 11 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
BMCBI
2008
97views more  BMCBI 2008»
14 years 10 months ago
A Population Proportion approach for ranking differentially expressed genes
Background: DNA microarrays are used to investigate differences in gene expression between two or more classes of samples. Most currently used approaches compare mean expression l...
Mugdha Gadgil
BMCBI
2008
167views more  BMCBI 2008»
14 years 10 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren
BMCBI
2004
169views more  BMCBI 2004»
14 years 9 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...