We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe networks of biochemical reactions and play an important role in the ...
Thomas A. Henzinger, Maria Mateescu, Linar Mikeev,...
Abstract—This paper presents a stochastic modelling framework for complex biochemical reaction networks from a component-based perspective. Our approach takes into account the di...
Mila E. Majster-Cederbaum, Nils Semmelrock, Verena...
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation...
Many models have been defined in order to describe the evolution of a disease in a population. The modelling of diseases is helpful to understand the mechanisms for their spread a...
We propose a new multiscale method to incorporate active transport of cargo particles in biological cells in stochastic, mesoscopic models of reaction-transport processes. Given a...