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BMCBI
2006
170views more  BMCBI 2006»
13 years 5 months ago
Biclustering of gene expression data by non-smooth non-negative matrix factorization
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
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
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang
BMCBI
2008
157views more  BMCBI 2008»
13 years 5 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...
IJBRA
2007
97views more  IJBRA 2007»
13 years 5 months ago
Structural Risk Minimisation based gene expression profiling analysis
: For microarray based cancer classification, feature selection is a common method for improving classifier generalisation. Most wrapper methods use cross validation methods to eva...
Xue-wen Chen, Byron Gerlach, Dechang Chen, ZhenQiu...