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» Improved Gene Selection for Classification of Microarrays
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IDEAL
2005
Springer
14 years 29 days ago
A Comparative Study of Two Novel Predictor Set Scoring Methods
Due to the large number of genes measured in a typical microarray dataset, feature selection plays an essential role in tumor classification. In turn, relevance and redundancy are ...
Chia Huey Ooi, Madhu Chetty
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
BMCBI
2008
167views more  BMCBI 2008»
13 years 7 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren
GECCO
2003
Springer
191views Optimization» more  GECCO 2003»
14 years 21 days ago
Artificial Immune System for Classification of Gene Expression Data
DNA microarray experiments generate thousands of gene expression measurement simultaneously. Analyzing the difference of gene expression in cell and tissue samples is useful in dia...
Shin Ando, Hitoshi Iba
BMCBI
2008
169views more  BMCBI 2008»
13 years 7 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...