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» Combined Gene Selection Methods for Microarray Data Analysis
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2006
Springer
13 years 5 months ago
Combined Gene Selection Methods for Microarray Data Analysis
In recent years, the rapid development of DNA Microarray technology has made it possible for scientists to monitor the expression level of thousands of genes in a single experiment...
Hong Hu, Jiuyong Li, Hua Wang, Grant Daggard
BMCBI
2004
205views more  BMCBI 2004»
13 years 4 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
BMCBI
2006
201views more  BMCBI 2006»
13 years 5 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
BMCBI
2005
121views more  BMCBI 2005»
13 years 5 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
CIBCB
2006
IEEE
13 years 11 months ago
A Model-Free Greedy Gene Selection for Microarray Sample Class Prediction
— Microarray data analysis is notoriously challenging as it involves a huge number of genes compared to only a limited number of samples. Gene selection, to detect the most signi...
Yi Shi, Zhipeng Cai, Lizhe Xu, Wei Ren, Randy Goeb...