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» Comparative evaluation of gene-set analysis methods
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BMCBI
2008
95views more  BMCBI 2008»
13 years 5 months ago
Gene set analyses for interpreting microarray experiments on prokaryotic organisms
Background: Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Rece...
Nathan L. Tintle, Aaron A. Best, Matthew DeJongh, ...
BMCBI
2005
212views more  BMCBI 2005»
13 years 5 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
AIME
2007
Springer
13 years 11 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
BMCBI
2011
12 years 9 months ago
Gene set analysis for longitudinal gene expression data
Background: Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. ...
Ke Zhang, Haiyan Wang, Arne C. Bathke, Solomon W. ...
BMCBI
2008
129views more  BMCBI 2008»
13 years 5 months ago
Gene set enrichment analysis for non-monotone association and multiple experimental categories
Background: Recently, microarray data analyses using functional pathway information, e.g., gene set enrichment analysis (GSEA) and significance analysis of function and expression...
Rongheng Lin, Shuangshuang Dai, Richard D. Irwin, ...