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» Using Bayesian networks to analyze expression data
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BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
14 years 11 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
CMSB
2004
Springer
15 years 1 months ago
Residual Bootstrapping and Median Filtering for Robust Estimation of Gene Networks from Microarray Data
We propose a robust estimation method of gene networks based on microarray gene expression data. It is well-known that microarray data contain a large amount of noise and some outl...
Seiya Imoto, Tomoyuki Higuchi, SunYong Kim, Euna J...
SDM
2009
SIAM
204views Data Mining» more  SDM 2009»
15 years 6 months ago
Application of Bayesian Partition Models in Warranty Data Analysis.
Automotive companies are forced to continuously extend and improve their product line-up. However, increasing diversity, higher design complexity, and shorter development cycles c...
Axel Blumenstock, Christoph Schlieder, Markus M&uu...
BMCBI
2005
94views more  BMCBI 2005»
14 years 9 months ago
YANA - a software tool for analyzing flux modes, gene-expression and enzyme activities
Background: A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA) has proven especial...
Roland Schwarz, Patrick Musch, Axel von Kamp, Bern...
IDA
2005
Springer
15 years 3 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...