Abstract Several studies in Bioinformatics, Computational Biology and Systems Biology rely
on the definition of physico-chemical or mathematical models of biological systems at …

The last few decades have revealed the living cell to be a crowded spatially heterogeneous
space teeming with biomolecules whose concentrations and activities are governed by …

Spatial stochastic simulation is a valuable technique for studying reactions in biological
systems. With the availability of high‐performance computing (HPC), the method is poised to …

Biochemical reactions often occur at low copy numbers but at once in crowded and diverse
environments. Space and stochasticity therefore play an essential role in biochemical …

In the last years, graphics processing units (GPUs) witnessed ever growing applications for
a wide range of computational analyses in the field of life sciences. Despite its large …

Tau-leaping is a stochastic simulation algorithm that efficiently reconstructs the temporal
evolution of biological systems, modeled according to the stochastic formulation of chemical …

Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology
and computational neuroscience. However, the increasing scale and complexity of models …

We present a unified approach to describing certain types of collective decision making in
swarm robotics that bridges from a microscopic individual-based description to aggregate …

Biochemical networks depict the chemical interactions that take place among elements of
living cells. They aim to elucidate how cellular behavior and functional properties of the cell …

In this paper, the model of chemical reactions on grained molecular level is presented. This
model allows simulating simple chemical reactions of first-and second-order using the …