Simulation of genetic networks modelled by piecewise deterministic Markov processes.
The authors propose piecewise deterministic Markov processes as an alternative approach to model gene regulatory networks. A hybrid simulation algorithm is presented and discussed, and several standard regulatory modules are analysed by numerical means. It is shown that despite of the partial simplification of the mesoscopic nature of regulatory networks such processes are suitable to reveal the intrinsic noise effects because of the low copy numbers of genes.
Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Biomathematics and Biometry, Neuherberg, Germany. zeiser@helmholtz-muenchen.de
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S
Zeiser
U
U
Franz
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O
Wittich
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Liebscher
D000465:Algorithms; D000818:Animals; D002384:Catalysis; D003198:Computer Simulation; D025461:Feedback, Physiological / Q000235:genetics; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D005812:Genes, Switch; D006801:Humans; D008390:Markov Chains; D008954:Models, Biological; D017711:Nonlinear Dynamics; D011401:Promoter Regions, Genetic; D049490:Systems Biology / Q000379:methods*