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» Additive risk survival model with microarray data
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JCB
2000
103views more  JCB 2000»
14 years 9 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
2004
139views more  BMCBI 2004»
14 years 9 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
BMCBI
2010
208views more  BMCBI 2010»
14 years 9 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
BMCBI
2011
14 years 4 months ago
Empirical Bayesian models for analysing molecular serotyping microarrays
Background: Microarrays offer great potential as a platform for molecular diagnostics, testing clinical samples for the presence of numerous biomarkers in highly multiplexed assay...
Richard Newton, Jason Hinds, Lorenz Wernisch
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BMCBI
2005
93views more  BMCBI 2005»
14 years 9 months ago
Two-part permutation tests for DNA methylation and microarray data
Background: One important application of microarray experiments is to identify differentially expressed genes. Often, small and negative expression levels were clipped-off to be e...
Markus Neuhäuser, Tanja Boes, Karl-Heinz J&ou...