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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2006
154views more  BMCBI 2006»
14 years 11 months ago
An improved procedure for gene selection from microarray experiments using false discovery rate criterion
Background: A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are o...
James J. Yang, Mark C. K. Yang
87
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BMCBI
2008
132views more  BMCBI 2008»
14 years 11 months ago
Very Important Pool (VIP) genes - an application for microarray-based molecular signatures
Background: Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicin...
Zhenqiang Su, Huixiao Hong, Hong Fang, Leming M. S...
97
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BMCBI
2007
127views more  BMCBI 2007»
14 years 11 months ago
A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments
Background: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across...
Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, D...
100
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BMCBI
2010
152views more  BMCBI 2010»
14 years 11 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...
BMCBI
2004
146views more  BMCBI 2004»
14 years 11 months ago
Multivariate search for differentially expressed gene combinations
Background: To identify differentially expressed genes, it is standard practice to test a twosample hypothesis for each gene with a proper adjustment for multiple testing. Such te...
Yuanhui Xiao, Robert D. Frisina, Alexander Gordon,...