Font Size: 

Approximate Bayesian computation (ABC) provides us a rigorous tool to perform parameter inference for models without an easily accessible likelihood function. Here we give a short introduction to ABC, focusing on applications in biological science: estimation of parameters of an epidemiological spreading process on a network and a numerical platelets deposition model. Furthermore, we introduce users to a Python suite implementing ABC algorithms, with optimal use of high-performance computing (HPC) facilities.