Our research interests

Object-oriented modelling of biological systems

Biological systems are complex, dynamical and riddled with feedback loops. The human mind is not well equipped to understand such systems without the help of mathematical models.

We use Modelica - a free object-oriented acausal modelling language - to develop biological models that are understandable and extensible over multiple scales of time and space.

Our current focus lies on models of the human heart, with the aim to find objective diagnosis criteria for heart diseases.

Computer-aided drug design

Computer-aided drug design (rational drug design) aims to reduce the number of animal experiments needed in drug discovery deriving new medications from computer simulations of potential drug molecules, receptors and enzymes.

In close collaboration with biotech and pharmaceutical industry, we develop innovative software tools to compare properties of compounds and to predict their potential medical application even before they are synthesised in the laboratory.

Machine learning

Data mining in biology is an extremely challenging task, because datasets are huge, noisy and uncertain.

We develop novel data mining algorithms by combining approaches from artificial intelligence, neural networks, chaos theory and image processing. The methods are applied to biological and clinical data, such as ECG time series, MRI volume data or histopathological slides of cancer tissue, with the aim to improve quality of diagnosis and therapeutic decisions.