Mathematical modelling and stochastic simulations are nowadays gaining more and more
interest in multidisciplinary investigations of biochemical systems. These systems are
usually characterised by a complex structure consisting of several reaction volumes,
where a large number of distinct molecular components can interact, all governed by
specific chemical parameters (i.e. kinetic constants, molecule concentrations, etc.) that
depend on the environmental and physical conditions of the systems. The complexity of
these systems, ranging from the molecular level to the spatial level, therefore requires
the development of efficient methods for their description and simulation.
In this talk, I will firstly present a recent modelling approach, called tau-DPP, that
integrates the features of membrane systems with stochastic simulation algorithms, and
allows both the modelling of topological structures and the simulation of the dynamics of
multi-volume biochemical systems.
Afterwards, I will describe a parameter estimation method based on optimisation
techniques, which is needed for determining those chemical parameters that are usually
unknown or that cannot be measured experimentally, but which are indispensable to perform
accurate simulations and analysis of the system's behaviour under different conditions.