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» Clustering gene expression patterns
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BMCBI
2008
121views more  BMCBI 2008»
14 years 10 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...
BMCBI
2007
166views more  BMCBI 2007»
14 years 10 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
2008
135views more  BMCBI 2008»
14 years 10 months ago
Knowledge-guided multi-scale independent component analysis for biomarker identification
Background: Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical...
Li Chen, Jianhua Xuan, Chen Wang, Ie-Ming Shih, Yu...
BMCBI
2010
87views more  BMCBI 2010»
14 years 10 months ago
Epigenetic domains found in mouse embryonic stem cells via a hidden Markov model
Background: Epigenetics is an important layer of transcriptional control necessary for cell-type specific gene regulation. Recent studies have shown significant epigenetic pattern...
Jessica L. Larson, Guo-Cheng Yuan
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
15 years 4 months ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester