Writing Stochastic Simulations

In Systems Biology 200, a graduate level class with some undergraduates enrolled, one of the skills that students learn is how to simulate molecular processes in biology by writing Monte Carlo simulations (the Doob-Gillespie algorithm).Students are introduced to writing stochastic simulations in different languages (Matlab, Kappa) during guided sections. Problem sets describe simulations that they are to produce. Some of the simulations are to view the general impact of stochasticity in biology, others are specific genetic circuits that rely upon noise for proper function. By the end of the problem sets, students produce simulation outcomes that demonstrate functions of genetic circuits and the impact on function of changing certain biological parameters. The goal of the activity is practical and theoretical: to develop skills in writing simulations and to understand the importance of molecular stochasticity in biology.

Teaching fellow Adam Palmer says that instructors must be very accessible to students encountering difficulties in the course of the exercise. Students must be advised to start early on the problem sets, and seek out the assistance of teaching fellows if difficulty is encountered. Attempting this alone on the last day is inadvisable. Teaching fellows should appreciate this and be generous with assistance to guide students through the development of these advanced skills.