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BMCBI
2008
167views more  BMCBI 2008»
13 years 7 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
2005
212views more  BMCBI 2005»
13 years 7 months ago
PAGE: Parametric Analysis of Gene Set Enrichment
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes i...
Seon-Young Kim, David J. Volsky
BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
ICMLA
2010
13 years 5 months ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
BMCBI
2005
151views more  BMCBI 2005»
13 years 7 months ago
stam - a Bioconductor compliant R package for structured analysis of microarray data
Background: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles...
Claudio Lottaz, Rainer Spang