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» Supervised inference of gene-regulatory networks
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AIME
2005
Springer
15 years 5 hour ago
An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset
In recent years, a few researchers have challenged past dogma and suggested methods (such as the IC algorithm) for inferring causal relationship among variables using steady state ...
Xin Zhang, Chitta Baral, Seungchan Kim
RECOMB
2003
Springer
15 years 10 months ago
Physical network models and multi-source data integration
We develop a new framework for inferring models of transcriptional regulation. The models in this approach, which we call physical models, are constructed on the basis of verifiab...
Chen-Hsiang Yeang, Tommi Jaakkola
BMCBI
2006
101views more  BMCBI 2006»
14 years 10 months ago
SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms
Background: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validatio...
Tim Van den Bulcke, Koen Van Leemput, Bart Naudts,...
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BMCBI
2008
65views more  BMCBI 2008»
14 years 10 months ago
Supervised inference of gene-regulatory networks
Cuong To, Jiri Vohradsky
BIOINFORMATICS
2005
152views more  BIOINFORMATICS 2005»
14 years 10 months ago
Intervention in context-sensitive probabilistic Boolean networks
Motivation: Intervention in a gene regulatory network is used to help it avoid undesirable states, such as those associated with a disease. Several types of intervention have been...
Ranadip Pal, Aniruddha Datta, Michael L. Bittner, ...