Do you want to better understand the underlying mechanisms of life? Would you like to contribute to integrating the scientific fields of biology and mathematics in order to open new perspectives for a deeper insight into biology, development of diseases and possibly the development of new therapies? Then Systems Biology is the right programme for you!
Systems Biology will become mainstream in biological sciences this century. It can be used to systematically gather knowledge at all levels, from molecules to entire systems and its integration into quantitative (computer) models. These models make accurate simulation of biological processes possible.
This programme will give you the knowledge and practical skills necessary to unravel the complexity of these systems and use it for academic, industrial and societal progress. After you’ve graduated, your ability to unify life sciences and mathematics will make you a great candidate for a career in medical research, drug development and biotechnology. Read more
Find out more about our staff and their courses/research.
Get to know all about Systems Biology and life in Maastricht. Follow our students on Facebook and Instagram to get all the inside information you are looking for and don’t hesitate to ask questions!
What's it like to study Systems Biology at Maastricht University? Find out through the online tour, featuring in-depth information about our teaching method, student experiences, the opportunity to talk to students and more.
Launched in 2015, the Maastricht Centre for Systems Biology (MaCSBio) strives to perform cutting edge research in the interdisciplinary field of Systems Biology to create a “virtual physiological human”, a set of computational and mathematical models based on biological evidence that will help to understand and predict human systems.
Research projects at MaCSBio focus on multi-scale modelling within two complementary research lines tackling areas that are highly relevant for society:
Learning with others is a beautiful experience
In her thesis: 'Modelling the Dynamics in Time Series of Metabolomics and Transcriptomics Data' O'Donovan focused on a range of computational approaches that allow multivariate time series of biological data to be integrated, analysed, and interpreted.
The framework of this research allows tissue cell type composition to emerge as a potential marker measuring homeostasis that can be utilized in prospective studies in regenerative medicine.
In the support section, you can find out more about practical matters and UM regulations, such as: