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» Bayesian Networks Learning for Gene Expression Datasets
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BMCBI
2007
198views more  BMCBI 2007»
14 years 9 months ago
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation
Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measu...
Nicola Neretti, Daniel Remondini, Marc Tatar, John...
72
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BMCBI
2010
109views more  BMCBI 2010»
14 years 9 months ago
Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
Background: In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a comple...
Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan...
ICASSP
2009
IEEE
15 years 4 months ago
Robust cross-race gene expression analysis
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...
Hsun-Hsien Chang, Marco Ramoni
BMCBI
2008
146views more  BMCBI 2008»
14 years 9 months ago
Rank-based edge reconstruction for scale-free genetic regulatory networks
Background: The reconstruction of genetic regulatory networks from microarray gene expression data has been a challenging task in bioinformatics. Various approaches to this proble...
Guanrao Chen, Peter Larsen, Eyad Almasri, Yang Dai
PRL
2006
129views more  PRL 2006»
14 years 9 months ago
Learning spatial relations in object recognition
This paper studies two types of spatial relationships that can be learned from training examples for object recognition. The first one employs deformable relationships between obj...
Thang V. Pham, Arnold W. M. Smeulders