Publikation:

Model Decomposition and Stochastic Fragments

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Petrov_2-1va61wz4cxq498.pdf
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2012

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Ganguly, Arnab
Koeppl, Heinz

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http://nbn-resolving.de/urn:nbn:de:bsz:352-2-1va61wz4cxq498
DOI (zitierfähiger Link)
https://doi.org/10.1016/j.entcs.2012.05.018
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Attribution-NonCommercial-NoDerivs 3.0 Unported

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Open Access Gold

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Electronic Notes in Theoretical Computer Science. 2012, 284, pp. 105-124. ISSN 1571-0661. Available under: doi: 10.1016/j.entcs.2012.05.018

Zusammenfassung

In this paper, we discuss a method for decomposition, abstraction and reconstruction of the stochastic semantics of rule-based systems with conserved number of agents. Abstraction is induced by counting fragments instead of the species, which are the standard entities of information in molecular signaling. The rule-set can be decomposed to smaller rule-sets, so that the fragment-based dynamics of the whole rule-set is exactly a composition of species-based dynamics of smaller rule-sets. The reconstruction of the transient species-based dynamics is possible for certain initial distributions. We show that, if all the rules in a rule set are reversible, the reconstruction of the species-based dynamics is always possible at the stationary distribution. We use a case study of colloidal aggregation to demonstrate that the method can reduce the state space exponentially with respect to the standard, species-based description.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

cell signaling, continuous-time Markov chain, lumpability

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ISO 690PETROV, Tatjana, Arnab GANGULY, Heinz KOEPPL, 2012. Model Decomposition and Stochastic Fragments. In: Electronic Notes in Theoretical Computer Science. 2012, 284, pp. 105-124. ISSN 1571-0661. Available under: doi: 10.1016/j.entcs.2012.05.018
BibTex
@article{Petrov2012-06Model-42135,
  year={2012},
  doi={10.1016/j.entcs.2012.05.018},
  title={Model Decomposition and Stochastic Fragments},
  volume={284},
  issn={1571-0661},
  journal={Electronic Notes in Theoretical Computer Science},
  pages={105--124},
  author={Petrov, Tatjana and Ganguly, Arnab and Koeppl, Heinz}
}
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