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TNN
2010
216views Management» more  TNN 2010»
12 years 12 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
BMCBI
2007
138views more  BMCBI 2007»
13 years 5 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
BIOINFORMATICS
2005
72views more  BIOINFORMATICS 2005»
13 years 5 months ago
Use of within-array replicate spots for assessing differential expression in microarray experiments
Motivation. Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to make full use of the...
Gordon K. Smyth, Joëlle Michaud, Hamish S. Sc...
JCB
2000
103views more  JCB 2000»
13 years 5 months ago
Testing for Differentially-Expressed Genes by Maximum-Likelihood Analysis of Microarray Data
Although two-color uorescent DNA microarrays are now standard equipment in many molecular biology laboratories, methods for identifying differentially expressed genes in microarra...
Trey Ideker, Vesteinn Thorsson, Andrew F. Siegel, ...
BMCBI
2011
13 years 7 days ago
Meta-analysis of gene expression microarrays with missing replicates
Background: Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combin...
Fan Shi, Gad Abraham, Christopher Leckie, Izhak Ha...