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FUIN
2002
123views more  FUIN 2002»
13 years 7 months ago
Learning Rough Set Classifiers from Gene Expressions and Clinical Data
Biological research is currently undergoing a revolution. With the advent of microarray technology the behavior of thousands of genes can be measured simultaneously. This capabilit...
Herman Midelfart, Henryk Jan Komorowski, Kristin N...
JCB
2000
103views more  JCB 2000»
13 years 7 months ago
Testing for Differentially-Expressed Genes by Maximum-Likelihood Analysis of Microarray Data
Although two-color uorescent DNA microarrays are now standard equipment in many molecular biology laboratories, methods for identifying differentially expressed genes in microarra...
Trey Ideker, Vesteinn Thorsson, Andrew F. Siegel, ...
BMCBI
2005
124views more  BMCBI 2005»
13 years 7 months ago
ErmineJ: Tool for functional analysis of gene expression data sets
Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...
BMCBI
2008
160views more  BMCBI 2008»
13 years 7 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
BMCBI
2006
140views more  BMCBI 2006»
13 years 7 months ago
Feature selection using Haar wavelet power spectrum
Background: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical m...
Prabakaran Subramani, Rajendra Sahu, Shekhar Verma