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» Combined Gene Selection Methods for Microarray Data Analysis
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CSB
2005
IEEE
156views Bioinformatics» more  CSB 2005»
15 years 5 months ago
A Robust Meta-classification Strategy for Cancer Diagnosis from Gene Expression Data
One of the major challenges in cancer diagnosis from microarray data is to develop robust classification models which are independent of the analysis techniques used and can combi...
Gabriela Alexe, Gyan Bhanot, Babu Venkataraghavan,...
CSB
2005
IEEE
121views Bioinformatics» more  CSB 2005»
15 years 5 months ago
K-means+ Method for Improving Gene Selection for Classification of Microarray Data
Heng Huang, Rong Zhang, Fei Xiong, Fillia Makedon,...
JIB
2006
110views more  JIB 2006»
14 years 11 months ago
Combining biomedical knowledge and transcriptomic data to extract new knowledge on genes
In biomedical research, interpretation of microarray data requires confrontation of data and knowledge from heterogeneous resources, either in the biomedical domain or in genomics...
Emilie Guérin, Gwenaëlle Marquet, Juli...
ICPR
2004
IEEE
16 years 24 days ago
Missing Microarray Data Estimation Based on Projection onto Convex Sets Method
DNA microarrays have gained widespread uses in biological studies. Missing values in a microarray experiment must be estimated before further analysis. In this paper, we propose a...
Alan Wee-Chung Liew, Hong Yan, Xiangchao Gan
GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
15 years 4 months ago
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data
Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...