Computational synthetic biology
As an engineering discipline, synthetic biology can benefit from quantitative modeling. Modeling dynamic biological phenotypes is of course challenging because they cannot be accurately simulated with simple deterministic reaction kinetic models. Multiple time and length scales pose additional difficulties. The statistical mechanics community has found answers for physicochemical systems that may be applicable to biological systems. Kinetic Monte Carlo simulations can model networks of reactions away from the thermodynamic limit and the community has produced a considerable volume of work on multiscale simulation methods.