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
Meet some of our Researchers
Recent Publications
Our most recent peer reviewed publications
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Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models
iScience (2024) -
Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism
Scientific Reports (2024) -
Strengths and challenges in current lung cancer care
Lung Cancer (2024) -
Agent-based modeling of the prostate tumor microenvironment uncovers spatial tumor growth constraints and immunomodulatory properties
npj Systems Biology and Applications (2024) -
A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer
Journal of Translational Medicine (2024)
Contact
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Visiting address
Building 15, Gemini South (room 2.106)Groene Loper5612 AZ EindhovenNetherlands -
SecretaryBME.Seccbioimage@ tue.nl