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» Detecting multivariate differentially expressed genes
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BMCBI
2008
122views more  BMCBI 2008»
13 years 7 months ago
Determining gene expression on a single pair of microarrays
Background: In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently fe...
Robert W. Reid, Anthony A. Fodor
BMCBI
2010
178views more  BMCBI 2010»
13 years 7 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
BMCBI
2007
179views more  BMCBI 2007»
13 years 7 months ago
Gene selection with multiple ordering criteria
Background: A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two co...
James J. Chen, Chen-An Tsai, ShengLi Tzeng, Chun-H...
BMCBI
2005
126views more  BMCBI 2005»
13 years 7 months ago
Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models
Background: With the explosion of microarray studies, an enormous amount of data is being produced. Systematic integration of gene expression data from different sources increases...
Pingzhao Hu, Celia M. T. Greenwood, Joseph Beyene
BMCBI
2007
110views more  BMCBI 2007»
13 years 7 months ago
Interpretation of multiple probe sets mapping to the same gene in Affymetrix GeneChips
Background: Affymetrix GeneChip technology enables the parallel observations of tens of thousands of genes. It is important that the probe set annotations are reliable so that bio...
Maria A. Stalteri, Andrew P. Harrison