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» Learning Rough Set Classifiers from Gene Expressions and Cli...
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JCB
2002
70views more  JCB 2002»
14 years 9 months ago
Strong Feature Sets from Small Samples
For small samples, classi er design algorithms typically suffer from over tting. Given a set of features, a classi er must be designed and its error estimated. For small samples, ...
Seungchan Kim, Edward R. Dougherty, Junior Barrera...
ISMB
2000
14 years 10 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu
BMCBI
2006
143views more  BMCBI 2006»
14 years 9 months ago
Discovering functional gene expression patterns in the metabolic network of Escherichia coli with wavelets transforms
Background: Microarray technology produces gene expression data on a genomic scale for an endless variety of organisms and conditions. However, this vast amount of information nee...
Rainer König, Gunnar Schramm, Marcus Oswald, ...
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BMCBI
2011
14 years 4 months ago
The dChip survival analysis module for microarray data
Background: Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene ex...
Samir B. Amin, Parantu K. Shah, Aimin Yan, Sophia ...
BMCBI
2005
114views more  BMCBI 2005»
14 years 9 months ago
Signal transduction pathway profiling of individual tumor samples
Background: Signal transduction pathways convey information from the outside of the cell to transcription factors, which in turn regulate gene expression. Our objective is to anal...
Thomas Breslin, Morten Krogh, Carsten Peterson, Ca...