Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics
Open Access
- 13 February 2013
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 29 (7), 910-916
- https://doi.org/10.1093/bioinformatics/btt069
Abstract
Motivation: Computational modelling of the dynamics of gene regulatory networks is a central task of systems biology. For networks of small/medium scale, the dominant paradigm is represented by systems of coupled non-linear ordinary differential equations (ODEs). ODEs afford great mechanistic detail and flexibility, but calibrating these models to data is often an extremely difficult statistical problem. Results: Here, we develop a general statistical inference framework for stochastic transcription–translation networks. We use a coarse-grained approach, which represents the system as a network of stochastic (binary) promoter and (continuous) protein variables. We derive an exact inference algorithm and an efficient variational approximation that allows scalable inference and learning of the model parameters. We demonstrate the power of the approach on two biological case studies, showing that the method allows a high degree of flexibility and is capable of testable novel biological predictions. Availability and implementation:http://homepages.inf.ed.ac.uk/gsanguin/software.html. Supplementary information: Supplementary data are available at Bioinformatics online. Contact:G.Sanguinetti@ed.ac.ukKeywords
This publication has 25 references indexed in Scilit:
- Mapping the Core of the Arabidopsis Circadian Clock Defines the Network Structure of the OscillatorScience, 2012
- Arabidopsis circadian clock protein, TOC1, is a DNA-binding transcription factorProceedings of the National Academy of Sciences of the United States of America, 2012
- The clock gene circuit in Arabidopsis includes a repressilator with additional feedback loopsMolecular Systems Biology, 2012
- Multiple light inputs to a simple clock circuit allow complex biological rhythmsThe Plant Journal, 2011
- Circadian rhythms persist without transcription in a eukaryoteNature, 2011
- Delay in Feedback Repression by Cryptochrome 1 Is Required for Circadian Clock FunctionCell, 2011
- Robustness of Circadian Clocks to Daylight Fluctuations: Hints from the Picoeucaryote Ostreococcus tauriPLoS Computational Biology, 2010
- ABC-SysBio—approximate Bayesian computation in Python with GPU supportBioinformatics, 2010
- Molecular level stochastic model for competence cycles in Bacillus subtilisProceedings of the National Academy of Sciences, 2007
- COPASI—a COmplex PAthway SImulatorBioinformatics, 2006