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BMCBI
2010
147views more  BMCBI 2010»
13 years 4 months ago
Indirect two-sided relative ranking: a robust similarity measure for gene expression data
Background: There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunatel...
Louis Licamele, Lise Getoor
BMCBI
2004
205views more  BMCBI 2004»
13 years 4 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
BMCBI
2006
198views more  BMCBI 2006»
13 years 4 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 ...
BMCBI
2005
118views more  BMCBI 2005»
13 years 4 months ago
Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
Background: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be us...
Thanyaluk Jirapech-Umpai, J. Stuart Aitken
SAC
2008
ACM
13 years 3 months ago
Strangeness-based feature weighting and classification of gene expression profiles
Achieving high classification accuracy is a major challenge in the diagnosis of cancer types based on gene expression profiles. These profiles are notoriously noisy in that a larg...
Haifeng Shao, Bei Yu, Joseph H. Nadeau