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» Redundancy based feature selection for microarray data
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BMCBI
2007
114views more  BMCBI 2007»
14 years 9 months ago
Large scale statistical inference of signaling pathways from RNAi and microarray data
Background: The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray tec...
Holger Fröhlich, Mark Fellmann, Holger Sü...
BMCBI
2006
200views more  BMCBI 2006»
14 years 9 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...
ISMIS
2003
Springer
15 years 2 months ago
Evolutionary Computation for Optimal Ensemble Classifier in Lymphoma Cancer Classification
Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with ...
Chanho Park, Sung-Bae Cho
93
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CSB
2005
IEEE
165views Bioinformatics» more  CSB 2005»
14 years 11 months ago
Sequential Diagonal Linear Discriminant Analysis (SeqDLDA) for Microarray Classification and Gene Identification
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
EVOW
2006
Springer
15 years 1 months ago
A Hybrid GA/SVM Approach for Gene Selection and Classification of Microarray Data
We propose a Genetic Algorithm (GA) approach combined with Support Vector Machines (SVM) for the classification of high dimensional Microarray data. This approach is associated to ...
Edmundo Bonilla Huerta, Béatrice Duval, Jin...