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» Improving gene set analysis of microarray data by SAM-GS
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BMCBI
2007
157views more  BMCBI 2007»
13 years 4 months ago
Improving gene set analysis of microarray data by SAM-GS
Background: Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary ph...
Irina Dinu, John D. Potter, Thomas Mueller, Qi Liu...
BMCBI
2006
147views more  BMCBI 2006»
13 years 4 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve
BMCBI
2005
167views more  BMCBI 2005»
13 years 4 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
AIME
2007
Springer
13 years 10 months ago
Interpreting Gene Expression Data by Searching for Enriched Gene Sets
This paper presents a novel method integrating gene-gene interaction information and Gene Ontology for the construction of new gene sets that are potentially enriched. Enrichment o...
Igor Trajkovski, Nada Lavrac
GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
13 years 9 months ago
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data
Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...