Stochastic Models and Numerical Algorithms for a Class of Regulatory Gene Networks
- Fournier, Thomas Department of Mathematics, University of Fribourg, Switzerland
- Gabriel, Jean-Pierre Department of Mathematics, University of Fribourg, Switzerland
- Mazza, Christian Department of Mathematics, University of Fribourg, Switzerland
- Pasquier, Jérôme Department of Mathematics, University of Fribourg, Switzerland
- Galbete, José Institute of Biotechnology, University of Lausanne, Switzerland
- Mermod, Nicolas Institute of Biotechnology, University of Lausanne, Switzerland
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22.04.2009
Published in:
- Bulletin of Mathematical Biology. - 2009, vol. 71, no. 6, p. 1394-1431
English
Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856–860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time- nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Mathématiques
- Language
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- English
- Classification
- Biological sciences
- License
- License undefined
- Identifiers
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- RERO DOC 11885
- DOI 10.1007/s11538-009-9407-9
- Persistent URL
- https://folia.unifr.ch/unifr/documents/301091
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