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» Analysis of variance components in gene expression data
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BMCBI
2010
216views more  BMCBI 2010»
14 years 4 months ago
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
BMCBI
2010
144views more  BMCBI 2010»
14 years 9 months ago
Super-sparse principal component analyses for high-throughput genomic data
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
Donghwan Lee, Woojoo Lee, Youngjo Lee, Yudi Pawita...
BMCBI
2008
170views more  BMCBI 2008»
14 years 9 months ago
Evaluation of GO-based functional similarity measures using S. cerevisiae protein interaction and expression profile data
Background: Researchers interested in analysing the expression patterns of functionally related genes usually hope to improve the accuracy of their results beyond the boundaries o...
Tao Xu, LinFang Du, Yan Zhou
CSB
2004
IEEE
106views Bioinformatics» more  CSB 2004»
15 years 1 months ago
A Theoretical Analysis of Gene Selection
A great deal of recent research has focused on the challenging task of selecting differentially expressed genes from microarray data (`gene selection'). Numerous gene selecti...
Sach Mukherjee, Stephen J. Roberts
IEEEMM
2007
146views more  IEEEMM 2007»
14 years 9 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...