Expressive Statistical Model Checking of Genetic Networks with Delayed Stochastic Dynamics

Abstract

Abstract. The recently introduced Hybrid Automata Stochastic Logic (HASL) [8] establishes a powerful framework for the analysis of a broad class of stochastic processes, namely Discrete Event Stochastic Processes (DESPs). Here we demonstrate the potential of HASL based verification in the context of genetic circuits. To this aim we consider the analysis of a model of gene expression with delayed stochastic dynamics, a class of systems whose dynamics includes both Markovian and non-Markovian events. We identify a number of relevant properties related to this model, formally express them in HASL terms and, assess them with COSMOS, a statistical model checker for HASL model checking. We demonstrate that this allows assessing the "performances" of a biological system beyond the capability of other stochastic logics.

Statistical model checking for biological applications

“…In a 2012 paper, Ballarini et al [3] have proposed a SMC approach in which properties are expressed in Hybrid Automata Stochastic Logic (HASL) instead of one of the usual variants of temporal logic. Basically, a HASL property is made of a linear hybrid automaton and an arithmetic expression over the so-called data variables of the automaton.…”