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» Classification of gene expression data using fuzzy logic
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GCB
2005
Springer
74views Biometrics» more  GCB 2005»
14 years 26 days ago
Exploiting scale-free information from expression data for cancer classification
: In most studies concerning expression data analyses information on the variability of gene intensity across samples is usually exploited. This information is sensitive to initial...
Alexey V. Antonov, Igor V. Tetko, Denis Kosykh, Di...
BMCBI
2007
143views more  BMCBI 2007»
13 years 7 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
2006
173views more  BMCBI 2006»
13 years 7 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
SAC
2008
ACM
13 years 5 months ago
Strangeness-based feature weighting and classification of gene expression profiles
Achieving high classification accuracy is a major challenge in the diagnosis of cancer types based on gene expression profiles. These profiles are notoriously noisy in that a larg...
Haifeng Shao, Bei Yu, Joseph H. Nadeau
BMCBI
2005
145views more  BMCBI 2005»
13 years 7 months ago
CAGER: classification analysis of gene expression regulation using multiple information sources
Background: Many classification approaches have been applied to analyzing transcriptional regulation of gene expressions. These methods build models that can explain a gene's...
Jianhua Ruan, Weixiong Zhang