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» Evolution of discrete gene regulatory models
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 5 months ago
Evolution of discrete gene regulatory models
Gene regulatory networks (GRNs) are complex control systems that govern the interaction of genes, which ultimately control cellular processes at the protein level. GRNs can be ted...
Afshin Esmaeili, Christian Jacob
BMCBI
2007
155views more  BMCBI 2007»
13 years 4 months ago
Current approaches to gene regulatory network modelling
Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network part...
Thomas Schlitt, Alvis Brazma
SAC
2008
ACM
13 years 4 months ago
Bayesian inference for a discretely observed stochastic kinetic model
The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observ...
Richard J. Boys, Darren J. Wilkinson, Thomas B. L....
NN
2007
Springer
267views Neural Networks» more  NN 2007»
13 years 4 months ago
Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
BMCBI
2010
152views more  BMCBI 2010»
13 years 4 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...