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NIPS
2003
13 years 6 months ago
Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms
New feature selection algorithms for linear threshold functions are described which combine backward elimination with an adaptive regularization method. This makes them particular...
Claudio Gentile
BMCBI
2011
13 years 9 days ago
AnyExpress: Integrated toolkit for analysis of cross-platform gene expression data using a fast interval matching algorithm
Background: Cross-platform analysis of gene express data requires multiple, intricate processes at different layers with various platforms. However, existing tools handle only a s...
Jihoon Kim, Kiltesh Patel, Hyunchul Jung, Winston ...
CANDC
2005
ACM
13 years 5 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
BMCBI
2007
140views more  BMCBI 2007»
13 years 5 months ago
Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
BMCBI
2006
146views more  BMCBI 2006»
13 years 5 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara