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» Power and sample size estimation in microarray studies
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BMCBI
2007
143views more  BMCBI 2007»
15 years 2 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
IEEEMM
2007
146views more  IEEEMM 2007»
15 years 1 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
WSC
2008
15 years 4 months ago
Implementable MSE-optimal dynamic partial-overlapping batch means estimators for steady-state simulations
Estimating the variance of the sample mean from a stochastic process is essential in assessing the quality of using the sample mean to estimate the population mean which is the fu...
Wheyming Tina Song, Mingchang Chih
111
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BMCBI
2006
154views more  BMCBI 2006»
15 years 1 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
122
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BMCBI
2004
139views more  BMCBI 2004»
15 years 1 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
Jeffrey P. Townsend