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» Classification of microarray data using gene networks
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IDA
2005
Springer
15 years 9 months ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
157
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BMCBI
2005
86views more  BMCBI 2005»
15 years 4 months ago
Confirmation of human protein interaction data by human expression data
Background: With microarray technology the expression of thousands of genes can be measured simultaneously. It is well known that the expression levels of genes of interacting pro...
Andreas Hahn, Jörg Rahnenführer, Priti T...
BMCBI
2007
139views more  BMCBI 2007»
15 years 4 months ago
Significance analysis of microarray transcript levels in time series experiments
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...
Barbara Di Camillo, Gianna Toffolo, Sreekumaran K....
BMCBI
2005
145views more  BMCBI 2005»
15 years 4 months ago
CAGER: classification analysis of gene expression regulation using multiple information sources
Background: Many classification approaches have been applied to analyzing transcriptional regulation of gene expressions. These methods build models that can explain a gene's...
Jianhua Ruan, Weixiong Zhang
BMCBI
2004
94views more  BMCBI 2004»
15 years 3 months ago
The tissue microarray data exchange specification: implementation by the Cooperative Prostate Cancer Tissue Resource
Background: Tissue Microarrays (TMAs) have emerged as a powerful tool for examining the distribution of marker molecules in hundreds of different tissues displayed on a single sli...
Jules J. Berman, Milton Datta, Andre Kajdacsy-Ball...