  Markov population models (MPMs) are a widely used modelling formalism in the
area of computational biology and related areas. The semantics of a MPM is an
infinite-state continuous-time Markov chain. In this paper, we use the
established continuous stochastic logic (CSL) to express properties of Markov
population models. This allows us to express important measures of biological
systems, such as probabilistic reachability, survivability, oscillations,
switching times between attractor regions, and various others. Because of the
infinite state space, available analysis techniques only apply to a very
restricted subset of CSL properties. We present a full algorithm for model
checking CSL for MPMs, and provide experimental evidence showing that our
method is effective.
