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Model Decomposition and Stochastic Fragments

Petrov, Tatjana ; Ganguly, Arnab ; Koeppl, Heinz (2024)
Model Decomposition and Stochastic Fragments.
In: Electronic Notes in Theoretical Computer Science, 2012, 284
doi: 10.26083/tuprints-00026720
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Item Type: Article
Type of entry: Secondary publication
Title: Model Decomposition and Stochastic Fragments
Language: English
Date: 30 April 2024
Place of Publication: Darmstadt
Year of primary publication: 20 June 2012
Place of primary publication: Amsterdam
Publisher: Elsevier
Journal or Publication Title: Electronic Notes in Theoretical Computer Science
Volume of the journal: 284
DOI: 10.26083/tuprints-00026720
Corresponding Links:
Origin: Secondary publication service

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.

Uncontrolled Keywords: cell signaling, continuous-time Markov chain, lumpability
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-267207
Classification DDC: 500 Science and mathematics > 570 Life sciences, biology
600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Date Deposited: 30 Apr 2024 09:12
Last Modified: 30 Apr 2024 09:13
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/26720
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