Reaction-Based Models of Biochemical Networks

Mathematical modeling and computational analyses of biological systems generally pose to modelers questions like: "Which modeling approach is suitable to describe the system we are interested in? Which computational tools do we need to simulate and analyze this system? What kind of predictions the model is expected to give?". To answer these questions, some general tips are here suggested to choose the proper modeling approach according to the size of the system, the desired level of detail for the system description, the availability of experimental data and the computational costs of the analyses that the model will require. The attention is then focused on the numerous advantages of reaction-based modeling, such as its high level of detail and easy under-standability, or the possibility to run both deterministic and stochastic simulations exploiting the same model. Some notes on the computational methods required to analyze reaction-based models, as well as their parallelization on Graphics Processing Units, are finally provided.