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» Gene set analysis for longitudinal gene expression data
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KDD
2002
ACM
183views Data Mining» more  KDD 2002»
14 years 8 months ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
BMCBI
2008
129views more  BMCBI 2008»
13 years 7 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, ...
BMCBI
2006
131views more  BMCBI 2006»
13 years 7 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
KDD
2004
ACM
142views Data Mining» more  KDD 2004»
14 years 8 months ago
Meta-classification of Multi-type Cancer Gene Expression Data
Massive publicly available gene expression data consisting of different experimental conditions and microarray platforms introduce new challenges in data mining when integrating m...
Benny Y. M. Fung, Vincent T. Y. Ng
BMCBI
2010
112views more  BMCBI 2010»
13 years 7 months ago
PhenoFam-gene set enrichment analysis through protein structural information
Background: With the current technological advances in high-throughput biology, the necessity to develop tools that help to analyse the massive amount of data being generated is e...
Maciej Paszkowski-Rogacz, Mikolaj Slabicki, M. Ter...