Technische Universiteit Eindhoven (TU/e) – NL

technische universiteit eindhoven

General description:

TU/e is a research university specializing in engineering science and technology. The Computational Biology (CBio) group of the Dept. of Biomedical Engineering at TU/e, aims to improve by modelling the qualitative and quantitative knowledge of biomedical processes and to educate in this field.

The interdisciplinary research programme integrates aspects of mathematics, computer science, system and control theory, engineering and biomedical sciences. The emphasis is on computational modelling methods and techniques especially at the molecular and cellular levels to enhance the fundamental understanding of cell metabolism and transport mechanisms in and between cells. Central themes are biomedical systems biology models, the translation of these models into algorithms, large-scale computer simulations, and quantitative analysis and interpretation of data from the modelling experiments.



TU/e is highly experienced in development, simulation and analysis of large-scale mechanistic models of metabolism and metabolic pathways at multiple temporal and spatial scales. Team members have expertise in dissemination and valorisation of systems biology research. Specifically: modelling and analysis of the dynamics of metabolic networks and regulatory pathways; parameter estimation, identifiability analysis, model-based experimental design; high-performance computing (parallelization, distributed computing, grid computing, GPU); state-of-the-art computational model of lipoprotein metabolism; experimental models (murine) of diet-induced obesity, insulin resistance, metabolic syndrome and type 2 diabetes; clinical research on type 2 diabetes; in vivo metabolomics (in collaboration with the Biomedical NMR group in the same department).


High-performance-computing, computational systems biology tools. Facilities for biological and physiological measurement to study metabolism and related regulatory pathways in cell models, murine models and humans, including in vivo imaging and metabolomics.

Other EU Projects:

ESIGNET (Evolving Cell Signalling Networks in Silico – FP6-NEST – Project ref: 12789)