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BMCBI
2006
173views more  BMCBI 2006»
13 years 7 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
BIOINFORMATICS
2006
96views more  BIOINFORMATICS 2006»
13 years 7 months ago
Joint estimation of calibration and expression for high-density oligonucleotide arrays
Motivation: The need for normalization in microarray experiments has been well documented in the literature. Currently, most analysis methods treat normalization and analysis as a...
Ann L. Oberg, Douglas W. Mahoney, Karla V. Ballman...
BMCBI
2002
188views more  BMCBI 2002»
13 years 7 months ago
The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
David M. Mutch, Alvin Berger, Robert Mansourian, A...
BMCBI
2004
106views more  BMCBI 2004»
13 years 7 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...
CLEIEJ
2007
152views more  CLEIEJ 2007»
13 years 7 months ago
Gene Expression Analysis using Markov Chains extracted from RNNs
Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
Igor Lorenzato Almeida, Denise Regina Pechmann Sim...