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BMCBI
2007
166views more  BMCBI 2007»
12 years 1 months ago
How to decide which are the most pertinent overly-represented features during gene set enrichment analysis
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
Roland Barriot, David J. Sherman, Isabelle Dutour
BMCBI
2006
183views more  BMCBI 2006»
12 years 2 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
BMCBI
2008
160views more  BMCBI 2008»
12 years 2 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
186views more  BMCBI 2007»
12 years 2 months ago
GeneBins: a database for classifying gene expression data, with application to plant genome arrays
Background: To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms. Results: We deve...
Nicolas Goffard, Georg Weiller
BMCBI
2005
212views more  BMCBI 2005»
12 years 1 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
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