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» The Combining Classifier: To Train or Not to Train
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BMCBI
2006
200views more  BMCBI 2006»
13 years 8 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 8 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
BMCBI
2007
144views more  BMCBI 2007»
13 years 8 months ago
Motif kernel generated by genetic programming improves remote homology and fold detection
Background: Protein remote homology detection is a central problem in computational biology. Most recent methods train support vector machines to discriminate between related and ...
Tony Håndstad, Arne J. H. Hestnes, Pål...
BMCBI
2007
114views more  BMCBI 2007»
13 years 8 months ago
Gene models from ESTs (GeneModelEST): an application on the Solanum lycopersicum genome
Background: The structure annotation of a genome is based either on ab initio methodologies or on similaritiy searches versus molecules that have been already annotated. Ab initio...
Nunzio D'Agostino, Alessandra Traini, Luigi Frusci...
BMCBI
2007
93views more  BMCBI 2007»
13 years 8 months ago
SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition
Background: Predicting a protein’s structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing ne...
Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, W...