Both undergraduate and PhD students of physical science are well trained to solve various standard kinds of equations, but it often comes as a shock that biophysical problems generally have a large stochastic element. Moreover, many biophysical problems do not have the “forward” character of elementary Physics (predict the future from the past) but rather demand distributions of first-passage times (satisfy an endpoint condition from generic initial conditions). Life-science students often appreciate such problems but have no background for approaching them quantitatively. For all these reasons, Gillespie simulation of stochastic processes is a general-purpose tool that should be in every student's toolkit, but generally is not. I will outline how I introduce this tool to every Biophysics undergraduate major at my institution, following a recent textbook. As examples, I will give details on two new publicly disseminated course modules involving current topics that I have asked my students to pursue (1) facilitated diffusion (hybrid 1D/3D) for gene transcription factor binding and (2) a first-passage framework that recapitulates experimental data on human aging.
Philip C. Nelson (Sun,) studied this question.