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BMCBI
2006
165views more  BMCBI 2006»
13 years 6 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin
BMCBI
2004
150views more  BMCBI 2004»
13 years 6 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...
CIBCB
2005
IEEE
13 years 12 months ago
Two-Phase EA/k-NN for Feature Selection and Classification in Cancer Microarray Datasets
Efficient and reliable methods that can find a small sample of informative genes amongst thousands are of great importance. In this area, much research is investigating the combina...
Thorhildur Juliusdottir, David Corne, Ed Keedwell,...
ICPR
2006
IEEE
14 years 7 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
BMCBI
2008
114views more  BMCBI 2008»
13 years 6 months ago
A visual analytics approach for understanding biclustering results from microarray data
Background: Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from mi...
Rodrigo Santamaría, Roberto Therón, ...