Synthetic biology is a rapidly emerging research area, with expected wide-ranging impact in
biology, nanofabrication, and medicine. A key technical challenge lies in embedding …

We describe a tool-supported method for the efficient synthesis of parametric continuous-
time Markov chains (pCTMC) that correspond to robust designs of a system under …

Principles of feedback control have been shown to naturally arise in biological systems and
have been applied with success to build synthetic circuits. Here, we present an …

The construction of models of system behavior is of great importance throughout science
and engineering. In bioengineering and bionanotechnology, these often take the form of …

Probabilistic programs are key to deal with uncertainty in, eg, controller synthesis. They are
typically small but intricate. Their development is complex and error prone requiring …

This paper presents counterexample-guided inductive synthesis (CEGIS) to automatically
synthesise probabilistic models. The starting point is a family of finite-stateMarkov chains …

We consider the problem of synthesizing programs with numerical constants that optimize a
quantitative objective, such as accuracy, over a set of input-output examples. We propose a …

We introduce P eregrine, the first tool for the analysis and parameterized verification of
population protocols. Population protocols are a model of computation very much studied by …

We provide a practical construction to map (slightly modified) GOTO-programs to chemical
reaction systems. While the embedding reveals that a certain small fragment of the …

Methods from stochastic dynamical systems theory have been instrumental in understanding
the behaviours of chemical reaction networks (CRNs) arising in natural systems. However …