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» A Multi-metric Similarity Based Analysis of Microarray Data
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CSB
2005
IEEE
146views Bioinformatics» more  CSB 2005»
13 years 10 months ago
Multi-Metric and Multi-Substructure Biclustering Analysis for Gene Expression Data
A good number of biclustering algorithms have been proposed for grouping gene expression data. Many of them have adopted matrix norms to define the similarity score of a bicluste...
Sun-Yuan Kung, Man-Wai Mak, Ilias Tagkopoulos
BMCBI
2005
167views more  BMCBI 2005»
13 years 4 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
BMCBI
2004
150views more  BMCBI 2004»
13 years 4 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...
BMCBI
2008
173views more  BMCBI 2008»
13 years 5 months ago
Gene Vector Analysis (Geneva): A unified method to detect differentially-regulated gene sets and similar microarray experiments
Background: Microarray experiments measure changes in the expression of thousands of genes. The resulting lists of genes with changes in expression are then searched for biologica...
Stephen W. Tanner, Pankaj Agarwal
BMCBI
2005
163views more  BMCBI 2005»
13 years 4 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...