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» A stable gene selection in microarray data analysis
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BMCBI
2002
195views more  BMCBI 2002»
13 years 7 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
BMCBI
2008
99views more  BMCBI 2008»
13 years 7 months ago
Ranking analysis of F-statistics for microarray data
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
Yuan-De Tan, Myriam Fornage, Hongyan Xu
BMCBI
2007
171views more  BMCBI 2007»
13 years 7 months ago
Classification of microarray data using gene networks
Background: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) a...
Franck Rapaport, Andrei Zinovyev, Marie Dutreix, E...
BIBM
2008
IEEE
145views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Meta Analysis of Microarray Data Using Gene Regulation Pathways
Using microarray technology for genetic analysis in biological experiments requires computationally intensive tools to interpret results. The main objective here is to develop a â...
Saira Ali Kazmi, Yoo-Ah Kim, Baikang Pei, Ravi Nor...
CSB
2005
IEEE
137views Bioinformatics» more  CSB 2005»
14 years 1 months ago
A Learned Comparative Expression Measure for Affymetrix GeneChip DNA Microarrays
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...