Modelling Biological Systems

Biological systems are arguably the most complex systems science tries to understand. We make observations, and try to obtain useful insight in the systems. This requires hypotheses; ideas of how we believe the world around us is structured and operates. Models translate our hypotheses into concrete predictions about our objects of study that can be tested by targeted experiments.

The more complex the systems we study, the more crucial the use of models. The SARS-CoV2 outbreak in 2019 is an example of a highly complex biological system. Models of how this virus spreads are crucial because they provide predictions that in turn can be used to take appropriate measures. Without models, we would not be able to focus the measures to combat this virus. There is a key role for one of the strongest tools in our scientific toolkit: mathematics. Mathematics are able to capture complexity in a form that makes it manageable. Mathematical models allow a full exploration of the consequences of our hypotheses and provide quantitative, and therefore precisely testable, predictions. Nowadays, this modelling toolkit is vastly extended by the wide availability of computers, which allow us to implement and test mathematical models, or even directly simulate the behaviour of complex systems.

In this course we attempt to convey the fascination for biological systems and introduce the tools to model them.

After successful completion of this course students are expected to be able to:

• Identify the key components of a relatively complex biological system
• Describe the interrelationships between the key components of a complex biological system
• Formulate a mathematical description of the system
• Analyse the system of governing equations to make predictions about the biological system
• Write a simple computer program in Python to simulate the simplified biological system
• Interpret the predictions and simulations of biological systems

Assumed Knowledge:
Modelling biological systems builds on first year biology courses, especially ecology, mathematics, statistics and physics. This basic knowledge is needed to adequately handle the models in the current course.