Stochastic/Deterministic Simulations for Modelling Circadian-Rhythm Genetic Oscillators

A collection of scientific computing experiments (view repo), held as part of the course “Scientific Computing for Data Analysis - 1TD352” at Uppsala University.

Reproduced from original study “Mechanisms of noise-resistance in genetic oscillators”: Stochastic and Deterministic simulations conducted, to model circadian rhythms, and creation/binding processes of different involved proteins, in mammals and organisms.

• An ODE model was used for the deterministic experiment, with the rates of change of all involved variables.
• A Random Walk (Monte Carlo Markov Process) was done for the stochastic experiment, given initial values of the parameters involved, state-change values and propensity functions per reaction type.

The simulations were conducted in Python, and NumPy as the numerical computation library.