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» Classification with reject option in gene expression data
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BMCBI
2004
252views more  BMCBI 2004»
14 years 9 months ago
Applying Support Vector Machines for Gene ontology based gene function prediction
Background: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to ann...
Arunachalam Vinayagam, Rainer König, Jutta Mo...
PRL
2006
130views more  PRL 2006»
14 years 9 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho
JMLR
2006
79views more  JMLR 2006»
14 years 9 months ago
Estimation of Gradients and Coordinate Covariation in Classification
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...
Sayan Mukherjee, Qiang Wu
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
14 years 7 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
BMCBI
2006
107views more  BMCBI 2006»
14 years 9 months ago
Simplifying gene trees for easier comprehension
Background: In the genomic age, gene trees may contain large amounts of data making them hard to read and understand. Therefore, an automated simplification is important. Results:...
Paul-Ludwig Lott, Marvin Mundry, Christoph Sassenb...