This course contains multiple exercises that address different aspects of chemical reaction networks. These are:

• Stochastic Cells: a very simple chemical reaction network, introducing the Gillespie algorithm, and comparison of stochastic and deterministic algorithms
• Simple Repressilator: introduces the Repressilator synthetic gene regulatory network, and examines the dynamics of a simple deterministic model
• Stochastic and Deterministic Repressilators: introduces a more complex model of the Repressilator, which is used as the basis of both stochastic and deterministic simulation algorithms, allowing for examining of the effects of noise on system dynamics
• There are finally some more open ended exercises involving gene regulatory networks

The Stochastic Cells exercise is a useful prerequisite for the remainder of the exercises. The Simple Repressilator exercise is straightforward, builds upon techniques introduced in other course modules (e.g., integration of coupled ODEs), and introduces the phenomenology of the Repressilator. The Stochastic and Deterministic Repressilators exercise is somewhat more complicated, although it can be done without having worked on the Simple Repressilator previously.