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» Classification of microarray data using gene networks
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164
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BMCBI
2004
169views more  BMCBI 2004»
15 years 2 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
BMCBI
2010
76views more  BMCBI 2010»
15 years 2 months ago
Validation and characterization of DNA microarray gene expression data distribution and associated moments
Background: The data from DNA microarrays are increasingly being used in order to understand effects of different conditions, exposures or diseases on the modulation of the expres...
Reuben Thomas, Luis de la Torre, Xiaoqing Chang, S...
CIBCB
2005
IEEE
15 years 8 months ago
Two-Phase EA/k-NN for Feature Selection and Classification in Cancer Microarray Datasets
Efficient and reliable methods that can find a small sample of informative genes amongst thousands are of great importance. In this area, much research is investigating the combina...
Thorhildur Juliusdottir, David Corne, Ed Keedwell,...
125
Voted
ICCS
2009
Springer
15 years 9 days ago
Gene Specific Co-regulation Discovery: An Improved Approach
Abstract. Discovering gene co-regulatory relationships is a new but important research problem in DNA microarray data analysis. The problem of gene specific co-regulation discovery...
Ji Zhang, Qing Liu, Kai Xu 0003
158
Voted
CIBCB
2008
IEEE
15 years 9 months ago
Classification of mouse fRNA genes using evolved neural networks
Functional RNAs (fRNAs) play a key role in gene regulation, at both the transcriptional and translational levels. Identification of fRNA genes can be difficult, given that some cla...
Mars Cheung, Gary B. Fogel