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RECOMB
2007
Springer
14 years 6 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans
BMCBI
2008
166views more  BMCBI 2008»
13 years 6 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
BMCBI
2010
176views more  BMCBI 2010»
13 years 6 months ago
Reverse engineering gene regulatory network from microarray data using linear time-variant model
nd: Gene regulatory network is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. Such prediction capability...
Mitra Kabir, Nasimul Noman, Hitoshi Iba
BMCBI
2010
172views more  BMCBI 2010»
13 years 1 months ago
Nonparametric identification of regulatory interactions from spatial and temporal gene expression data
Background: The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but ...
Anil Aswani, Soile V. E. Keränen, James Brown...
BMCBI
2007
155views more  BMCBI 2007»
13 years 6 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