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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2007
171views more  BMCBI 2007»
15 years 2 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...
BMCBI
2005
131views more  BMCBI 2005»
15 years 2 months ago
Regularized Least Squares Cancer Classifiers from DNA microarray data
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
Nicola Ancona, Rosalia Maglietta, Annarita D'Addab...
BMCBI
2008
138views more  BMCBI 2008»
15 years 2 months ago
M-BISON: Microarray-based integration of data sources using networks
Background: The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variabi...
Bernie J. Daigle Jr., Russ B. Altman
IDEAL
2005
Springer
15 years 8 months ago
A Comparative Study of Two Novel Predictor Set Scoring Methods
Due to the large number of genes measured in a typical microarray dataset, feature selection plays an essential role in tumor classification. In turn, relevance and redundancy are ...
Chia Huey Ooi, Madhu Chetty
BMCBI
2005
113views more  BMCBI 2005»
15 years 2 months ago
Normal uniform mixture differential gene expression detection for cDNA microarrays
Background: One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the ...
Nema Dean, Adrian E. Raftery