
handle: 11368/3070450
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.
cell signaling; continuous-time Markov chain; lumpability, cell signaling, continuous-time Markov chain, lumpability, cell signaling, continuous-time Markov chain, info:eu-repo/classification/ddc/004, lumpability, Theoretical Computer Science, Computer Science(all)
cell signaling; continuous-time Markov chain; lumpability, cell signaling, continuous-time Markov chain, lumpability, cell signaling, continuous-time Markov chain, info:eu-repo/classification/ddc/004, lumpability, Theoretical Computer Science, Computer Science(all)
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