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GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
14 years 2 days ago
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data
Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...
BMCBI
2004
75views more  BMCBI 2004»
13 years 6 months ago
Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...
Hongying Jiang, Youping Deng, Huann-Sheng Chen, Li...
BMCBI
2005
167views more  BMCBI 2005»
13 years 6 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
BMCBI
2006
126views more  BMCBI 2006»
13 years 7 months ago
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass ge
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
BMCBI
2006
92views more  BMCBI 2006»
13 years 7 months ago
Predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays
Background: Genetic markers hold great promise for refining our ability to establish precise prognostic prediction for diseases. The development of comprehensive gene expression m...
Shigeyuki Matsui