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GECCO
2004
Springer
104views Optimization» more  GECCO 2004»
13 years 10 months ago
A Genetic Approach for Gene Selection on Microarray Expression Data
Abstract. Microarrays allow simultaneous measurement of the expression levels of thousands of genes in cells under different physiological or disease states. Because the number of...
Yong-Hyuk Kim, Su-Yeon Lee, Byung Ro Moon
BMCBI
2011
12 years 8 months ago
Cell Subset Prediction for Blood Genomic Studies
Background: Genome-wide transcriptional profiling of patient blood samples offers a powerful tool to investigate underlying disease mechanisms and personalized treatment decisions...
Christopher R. Bolen, Mohamed Uduman, Steven H. Kl...
BMCBI
2007
217views more  BMCBI 2007»
13 years 5 months ago
On consensus biomarker selection
Background: Recent development of mass spectrometry technology enabled the analysis of complex peptide mixtures. A lot of effort is currently devoted to the identification of biom...
Janusz Dutkowski, Anna Gambin
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 3 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
BMCBI
2005
118views more  BMCBI 2005»
13 years 5 months ago
Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
Background: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be us...
Thanyaluk Jirapech-Umpai, J. Stuart Aitken