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BMCBI
2006
122views more  BMCBI 2006»
13 years 4 months ago
A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets
Background: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifi...
Carmen Lai, Marcel J. T. Reinders, Laura J. van't ...
APBC
2004
121views Bioinformatics» more  APBC 2004»
13 years 6 months ago
Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection
Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early...
Larry T. H. Yu, Fu-Lai Chung, Stephen Chi-fai Chan...
BMCBI
2006
173views more  BMCBI 2006»
13 years 4 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
2010
147views more  BMCBI 2010»
13 years 4 months ago
Indirect two-sided relative ranking: a robust similarity measure for gene expression data
Background: There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunatel...
Louis Licamele, Lise Getoor
BMCBI
2005
131views more  BMCBI 2005»
13 years 4 months ago
Regularized Least Squares Cancer Classifiers from DNA microarray data
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
Nicola Ancona, Rosalia Maglietta, Annarita D'Addab...