Model-Checking Algorithms for Continuous-Time Markov Chains
IEEE Transactions on Software Engineering
Theoretical Computer Science - Special issue: Computational systems biology
Stochastic Semantics of Signaling as a Composition of Agent-view Automata
Electronic Notes in Theoretical Computer Science (ENTCS)
Reconstructing species-based dynamics from reduced stochastic rule-based models
Proceedings of the Winter Simulation Conference
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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.