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FLAIRS
2004
13 years 7 months ago
Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ZhenQiu Liu, Dechang Chen
EVOW
2004
Springer
13 years 11 months ago
Evolutionary Search of Thresholds for Robust Feature Set Selection: Application to the Analysis of Microarray Data
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Carlos Cotta, Christian Sloper, Pablo Moscato
TCBB
2010
176views more  TCBB 2010»
13 years 4 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
BMCBI
2007
143views more  BMCBI 2007»
13 years 6 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
BMCBI
2007
140views more  BMCBI 2007»
13 years 6 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...