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BMCBI
2006
198views more  BMCBI 2006»
13 years 10 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...
BMCBI
2006
95views more  BMCBI 2006»
13 years 10 months ago
A quantitative analysis of secondary RNA structure using domination based parameters on trees
Background: It has become increasingly apparent that a comprehensive database of RNA motifs is essential in order to achieve new goals in genomic and proteomic research. Secondary...
Teresa W. Haynes, Debra J. Knisley, Edith Seier, Y...
BMCBI
2006
165views more  BMCBI 2006»
13 years 10 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin
BMCBI
2006
173views more  BMCBI 2006»
13 years 10 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
IJCV
2008
192views more  IJCV 2008»
13 years 9 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...