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KDD
2004
ACM
302views Data Mining» more  KDD 2004»
14 years 5 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
BMCBI
2005
190views more  BMCBI 2005»
13 years 4 months ago
An Entropy-based gene selection method for cancer classification using microarray data
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Xiaoxing Liu, Arun Krishnan, Adrian Mondry
APBC
2004
107views Bioinformatics» more  APBC 2004»
13 years 6 months ago
An Empirical Bayes Adjustment to Multiple p-values for the Detection of Differentially Expressed Genes in Microarray Experiments
In recent microarray experiments thousands of gene expressions are simultaneously tested in comparing samples (e.g., tissue types or experimental conditions). Application of a sta...
Somnath Datta, Susmita Datta
CATA
2008
13 years 6 months ago
Investigation of Random Forest Performance with Cancer Microarray Data
The diagnosis of cancer type based on microarray data offers hope that cancer classification can be highly accurate for clinicians to choose the most appropriate forms of treatmen...
Myungsook Klassen, Matt Cummings, Griselda Saldana
BMCBI
2006
198views more  BMCBI 2006»
13 years 5 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...