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GECCO
2004
Springer
104views Optimization» more  GECCO 2004»
14 years 8 days 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
2006
201views more  BMCBI 2006»
13 years 7 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
ICML
2007
IEEE
14 years 7 months ago
Hybrid huberized support vector machines for microarray classification
The large number of genes and the relatively small number of samples are typical characteristics for microarray data. These characteristics pose challenges for both sample classif...
Li Wang, Ji Zhu, Hui Zou
BMCBI
2005
178views more  BMCBI 2005»
13 years 6 months ago
A quantization method based on threshold optimization for microarray short time series
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
Barbara Di Camillo, Fatima Sanchez-Cabo, Gianna To...
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 4 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...