Department of Biomedical Engineering

Computational Biology

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

[Translate to English:]

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 systems biology modeling methods, data analysis techniques,  machine learning, and parameter estimation algorithms. Topics of research are, amongst others, complex biochemical networks, diseases like metabolic syndrome, diabetes mellitus and cancer, and applied clinical data science. Next to data obtained through collaborations and partnerships with other university groups, companies and hospitals, within the Systems Biology for Oncology theme data is also achieved by own experiments. 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 Systems Biology and Metabolic Disease, Systems Biology for Oncology, Immuno Systems Biology, and Data Science and Bioinformatics.

Research Lines

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

Data Science and Bioinformatics

We use data science techniques, including machine learning and artificial intelligence, to analyse molecular and clinical data.

Synthetic Biology

We develop living technologies based on synthetic biology to tackle important societal problems including the development of DNA data…

Research Line of Computational Biology

Machine learning for drug discovery

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

Immuno Systems Biology

The innate immune system forms our first line of defense against infection. Impairments in immune function in aging and obesity can give rise to chronic low-grade inflammation, contributing to the development of cardiometabolic diseases.

Research Line

Molecular Modelling

The aim is to elucidate molecular-level self-assembly and self-organization in biologically relevant systems through the use and advancement…

Meet some of our Researchers

Full Professor

Natal van Riel

Associate Professor

Federica Eduati

Assistant Professor

Dragan Bosnacki

Full Professor

Tom de Greef

Assistant Professor

Bart Markvoort

Assistant Professor

Shauna O'Donovan

University Researcher

Peter Hilbers

Recent Publications

Our most recent peer reviewed publications

Student opportunities

Our job opportunities

Building a better future for our global society?

Join our research team and be part of the thriving community at Eindhoven University of Technology.  

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