Modelling in Systems Biology

The main goal of Systems Biology is to obtain a deeper understanding of biological systems and their behaviour. This is achieved by combining mathematical modelling, scientific programming, and experiments. From adaptation to oscillations, biological systems produce a wide range of phenomena which vary over time. As (wet lab) experiments provide us with the quantitative measurements of these dynamic systems, mathematical models provide rigorous methods to summarise, describe and interpret our (biological) knowledge of a system, test whether we understand what causes particular behaviour, and hypothesise future experimental conditions to verify our understanding. Using experimental and mathematical methods in combination deepens our understanding of nature and provides us with knowledge of the design principles underlying complex biological networks.

In the first weeks you will be presented with different biological phenomena and new mathematical analysis methods to uncover why these specific phenomena occur. You will learn about modelling methods and how to apply them in a biological context, for instance, to describe networks across different time-scales, cellular switch mechanisms, and why we observe adaptation and oscillations. You will then practice how to use computational methods to directly match models with relevant datasets and create experimental hypotheses for the future. As well as learning the theory behind useful and important scientific mathematical tools, you will learn how to code these with modern and adaptable programming languages and how to apply them to more complex research problems typically encountered in science and engineering. To complete the course you will then build and analyse your own mathematical model describing some exemplar biological system.

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

• interpret and construct mathematical models of biological systems;
• recognise which mathematical tools can be appropriately utilised for a given problem;
• apply computer packages and tools to predict system behaviour;
• assess model accuracy & quality in relation to experimental data;
• collaborate in small groups;
• communicate results in written and verbal form.

Assumed Knowledge:
Introduction to Systems & Synthetic Biology (SSB50806), Modelling Biological Systems (EZO23306), Mathematics 2 (MAT14903), Mathematics 3 (MAT15003), or equivalent.