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BMCBI
2008
179views more  BMCBI 2008»
13 years 4 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao
ACIIDS
2010
IEEE
170views Database» more  ACIIDS 2010»
13 years 2 months ago
On the Effectiveness of Gene Selection for Microarray Classification Methods
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
Zhongwei Zhang, Jiuyong Li, Hong Hu, Hong Zhou
BMCBI
2005
167views more  BMCBI 2005»
13 years 4 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
BMCBI
2006
129views more  BMCBI 2006»
13 years 4 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer
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