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» A stable gene selection in microarray data analysis
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BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
Background: Computational methods for characterizing novel transcription factor binding sites search for sequence patterns or "motifs" that appear repeatedly in genomic ...
Katerina Kechris, Hao Li
EVOW
2005
Springer
14 years 1 months ago
Order Preserving Clustering over Multiple Time Course Experiments
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Stefan Bleuler, Eckart Zitzler
KDD
2001
ACM
169views Data Mining» more  KDD 2001»
14 years 8 months ago
Hierarchical cluster analysis of SAGE data for cancer profiling
In this paper we present a method for clustering SAGE (Serial Analysis of Gene Expression) data to detect similarities and dissimilarities between different types of cancer on the...
Jörg Sander, Monica C. Sleumer, Raymond T. Ng
BMCBI
2010
120views more  BMCBI 2010»
13 years 7 months ago
Modeling expression quantitative trait loci in data combining ethnic populations
Background: Combining data from different ethnic populations in a study can increase efficacy of methods designed to identify expression quantitative trait loci (eQTL) compared to...
Ching-Lin Hsiao, Ie-Bin Lian, Ai-Ru Hsieh, Cathy S...
BMCBI
2006
143views more  BMCBI 2006»
13 years 7 months ago
Discovering functional gene expression patterns in the metabolic network of Escherichia coli with wavelets transforms
Background: Microarray technology produces gene expression data on a genomic scale for an endless variety of organisms and conditions. However, this vast amount of information nee...
Rainer König, Gunnar Schramm, Marcus Oswald, ...