Department of Biomedical Engineering

Computational Biology

Constructing computational models to improve the knowledge of diseases, biomedical processes and structures.

DESCRIBING, UNDERSTANDING AND ULTIMATELY CONTROLLING LIFE'S PROCESSES

The research group Computational Biology develops computational models that help to obtain qualitative and quantitative knowledge of diseases, biomedical processes and structures. The computational models are developed based on a thorough understanding of molecular modeling methods, data analysis techniques, machine learning, systems biology, and parameter estimation techniques. Next to data obtained through collaborations and partnerships with other university groups, companies and hospitals, within the Synthetic Biology arena data is also achieved by own experiments. Topics of research are, amongst others, biomembranes, protein interactions, complex biochemical networks, and diseases like metabolic syndrome, diabetes mellitus and cancer. The group also puts efforts in enhancing the shift from ‘describing’ life’s processes to ‘understanding’ them and ‘capturing’ them in validated predictive models, and even ‘managing’ or ‘controlling’ them in real life. Research themes of the group are Molecular Simulations, Systems Biology and Metabolic Disease, Systems Biology for Oncology, Synthetic Biology, Data Science and Bioinformatics.

Research Lines

Research Line of Computational Biology

Machine learning for drug discovery

Using machine learning and chemoinformatics approaches to discover novel molecules with desired biological activity

Research Line of Computational Biology

Synthetic Biology

Using a forward engineering approach to design and control biological systems.

Research Line of Computational Biology

Systems Biology and Metabolic Disease

Using mathematical models to enhance understanding and treatment of disease. 

Research line of Computational Biology

Systems Biology for Oncology

Systems biology is applied to (immuno-)oncology with the ultimate goal of gaining insights in cancer deregulations and drugs mode of action,…

Research Line of Computational Biology

Molecular Modelling

Application and development of molecular simulations to elucidate self-assembly and self-organization processes in biologically relevant…

Research Line of Computational Biology

Data Science and Bioinformatics

In our Bioinformatics and Mathematical Modelling research we apply methods from computer science and mathematics in medicine and biology.

Meet some of our Researchers

Assistant Professor

Bart Markvoort

Full Professor

Tom de Greef

Audio-Visual Technician (direction)

Koen Pieterse

Assistant Professor

Dragan Bosnacki

Full Professor

Peter Hilbers

Assistant Professor

Federica Eduati

Full Professor

Natal van Riel

Recent Publications

Our most recent peer reviewed publications

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