Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
This paper presents two approaches based on metabolic and stochastic P systems, together with their associated analysis methods, for modelling biological systems and illustrates th...
Marian Gheorghe, Vincenzo Manca, Francisco Jos&eac...
Abstract— For stochastic hybrid systems, stochastic reachability is very little supported mainly because of complexity and difficulty of the associated mathematical problems. In...
We propose new techniques to simplify the computation of the cycle times and the absorption times for a large class of PEPA models. These techniques allow us to simplify the model ...
Abstract. Biological systems involving genetic reactions are large discrete event systems, and often contain certain species that occur in small quantities, and others that occur i...