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» Classification with reject option in gene expression data
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SAC
2008
ACM
13 years 8 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
BMCBI
2010
76views more  BMCBI 2010»
13 years 9 months ago
Validation and characterization of DNA microarray gene expression data distribution and associated moments
Background: The data from DNA microarrays are increasingly being used in order to understand effects of different conditions, exposures or diseases on the modulation of the expres...
Reuben Thomas, Luis de la Torre, Xiaoqing Chang, S...
APBC
2004
132views Bioinformatics» more  APBC 2004»
13 years 11 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
BMCBI
2007
194views more  BMCBI 2007»
13 years 10 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
BMCBI
2005
112views more  BMCBI 2005»
13 years 9 months ago
Towards precise classification of cancers based on robust gene functional expression profiles
Background: Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. Th...
Zheng Guo, Tianwen Zhang, Xia Li, Qi Wang, Jianzhe...