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ICPR
2006
IEEE
14 years 8 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
BIOCOMP
2007
13 years 9 months ago
Biomarker Discovery Across Annotated and Unannotated Microarray Datasets Using Semi-Supervised Learning
The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically us...
Cole Harris, Noushin Ghaffari
BMCBI
2004
128views more  BMCBI 2004»
13 years 7 months ago
Comparing transformation methods for DNA microarray data
Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed ...
Helene H. Thygesen, Aeilko H. Zwinderman
BMCBI
2010
164views more  BMCBI 2010»
13 years 5 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
CVPR
2004
IEEE
14 years 9 months ago
Feature Selection for Classifying High-Dimensional Numerical Data
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
Yimin Wu, Aidong Zhang