We study the problem of optimal syntax-guided synthesis of stochastic Chemical Reaction
Networks (CRNs) that plays a fundamental role in design automation of molecular devices …

An important problem when modelling gene networks lies in the identification of parameters,
even when using a discrete framework such as the one of René Thomas. We present in this …

Boolean networks offer an elegant way to model the behaviour of complex systems with
positive and negative feedback. The long-term behaviour of a Boolean network is …

We propose a novel scalable parallel algorithm for synthesis of interdependent parameters
from CTL specifications for non-linear dynamical systems. The method employs a symbolic …

Abstract Analysis of large continuous-time stochastic systems is a computationally intensive
task. In this work we focus on population models arising from chemical reaction networks …

Formal methods have enabled breakthroughs in many fields, such as in hardware
verification, machine learning and biological systems. The key object of interest in systems …

The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-
based statistical testing-like methods. In this paper, we demonstrate that we can replace this …

The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-
based statistical testing-like methods. In this paper, we demonstrate that we can replace this …

A eukaryotic cell contains multiple membrane-bound compartments. Transport vesicles
move cargo between these compartments, just as trucks move cargo between warehouses …

Parametrised models of dynamical systems arise in various areas of science. In this work,
we focus on models described as parametrised Kripke structures with properties formulated …