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» Unfolding of Microarray Data
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TEC
2008
146views more  TEC 2008»
13 years 8 months ago
An Evolutionary Algorithm Approach to Optimal Ensemble Classifiers for DNA Microarray Data Analysis
In general, the analysis of microarray data requires two steps: feature selection and classification. From a variety of feature selection methods and classifiers, it is difficult t...
Kyung-Joong Kim, Sung-Bae Cho
BMCBI
2005
189views more  BMCBI 2005»
13 years 8 months ago
Quantitative inference of dynamic regulatory pathways via microarray data
Background: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway ar...
Wen-Chieh Chang, Chang-Wei Li, Bor-Sen Chen
BMCBI
2005
151views more  BMCBI 2005»
13 years 8 months ago
stam - a Bioconductor compliant R package for structured analysis of microarray data
Background: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles...
Claudio Lottaz, Rainer Spang
BMCBI
2007
157views more  BMCBI 2007»
13 years 8 months ago
Improving gene set analysis of microarray data by SAM-GS
Background: Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary ph...
Irina Dinu, John D. Potter, Thomas Mueller, Qi Liu...
BMCBI
2006
173views more  BMCBI 2006»
13 years 8 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen