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» GroupAdaBoost for Selecting Important Genes
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CEC
2007
IEEE
13 years 11 months ago
Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...
Enrique Alba, José García-Nieto, Lae...
BMCBI
2006
72views more  BMCBI 2006»
13 years 7 months ago
Selecting effective siRNA sequences by using radial basis function network and decision tree learning
Background: Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are o...
Shigeru Takasaki, Yoshihiro Kawamura, Akihiko Kona...
BMCBI
2006
126views more  BMCBI 2006»
13 years 7 months ago
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass ge
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
BMCBI
2005
89views more  BMCBI 2005»
13 years 7 months ago
Theme discovery from gene lists for identification and viewing of multiple functional groups
Background: High throughput methods of the genome era produce vast amounts of data in the form of gene lists. These lists are large and difficult to interpret without advanced com...
Petri Pehkonen, Garry Wong, Petri Töröne...
BMCBI
2006
116views more  BMCBI 2006»
13 years 7 months ago
ROKU: a novel method for identification of tissue-specific genes
Background: One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We wo...
Koji Kadota, Jiazhen Ye, Yuji Nakai, Tohru Terada,...