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BMCBI
2004
124views more  BMCBI 2004»
13 years 5 months ago
Tests for finding complex patterns of differential expression in cancers: towards individualized medicine
Background: Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g....
James Lyons-Weiler, Satish Patel, Michael J. Becic...
BMCBI
2011
12 years 9 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
BMCBI
2006
200views more  BMCBI 2006»
13 years 5 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
BMCBI
2008
167views more  BMCBI 2008»
13 years 5 months ago
Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments
Background: Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to enviro...
Stefano Parodi, Vito Pistoia, Marco Muselli
BMCBI
2004
169views more  BMCBI 2004»
13 years 5 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...