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BMCBI
2005
112views more  BMCBI 2005»
13 years 7 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
BMCBI
2007
166views more  BMCBI 2007»
13 years 7 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
RECOMB
2002
Springer
14 years 8 months ago
Phase-independent rhythmic analysis of genome-wide expression patterns
We introduce a model-based analysis technique for extracting and characterizing rhythmic expression pro les from genome-wide DNA microarray hybridization data. These patterns are ...
Christopher James Langmead, Anthony K. Yan, C. Rob...
BMCBI
2010
193views more  BMCBI 2010»
13 years 2 months ago
Mayday - integrative analytics for expression data
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...
Florian Battke, Stephan Symons, Kay Nieselt
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