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» Error margin analysis for feature gene extraction
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BMCBI
2006
146views more  BMCBI 2006»
13 years 4 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
BMCBI
2007
207views more  BMCBI 2007»
13 years 4 months ago
Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering
Background: Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular lev...
Manjunatha Jagalur, Chris Pal, Erik G. Learned-Mil...
BMCBI
2008
119views more  BMCBI 2008»
13 years 4 months ago
Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction
Background: This paper describes and evaluates a sentence selection engine that extracts a GeneRiF (Gene Reference into Functions) as defined in ENTREZ-Gene based on a MEDLINE rec...
Julien Gobeill, Imad Tbahriti, Frédé...
BIBM
2008
IEEE
212views Bioinformatics» more  BIBM 2008»
13 years 11 months ago
Analysis of Multiplex Gene Expression Maps Obtained by Voxelation
Background: Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelatio...
Li An, Hongbo Xie, Mark H. Chin, Zoran Obradovic, ...
TNN
2008
182views more  TNN 2008»
13 years 4 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...