Living organisms exhibit remarkable hierarchical complexity that cannot be understood through data collection alone. Mathematical modeling provides a powerful and cost-effective approach to generating and testing hypotheses about biological mechanisms. In this course, taught by expert instructors from WUR, TU/e, and UvA, students will develop skills in building mathematical models of biological systems, running simulations, and connecting findings to real biological questions.
Register for the course by filling out the registration form (early bird till 12 October).
Course coordinator
Dr. Dragan Bosnacki, Eindhoven University of Technology
Course credits
Students receive 1.5 ECTS credits for completing the course. An additional 1.5 ECTS credits are awarded for successfully completing the supplementary assignment.
Course description
Living organisms are characterized by an amazing degree of hierarchical complexity. Although our ability to collect measurements at different spatial levels and time-scales has grown dramatically, data alone cannot help us unravel biological complexity and understand how a system functions. This is because the dynamical behavior of complex systems cannot be reduced to the linear sum of the functions of their parts. Hence, computational modelling is an absolute requisite to gain understanding of the mechanisms underlying patterns observed in experimental data, in particular when studying dynamic phenomena. Mathematical models allow us to relatively cheaply generate and test hypotheses about these mechanisms. However, given the huge complexity and peculiar features of biological systems, modellers need to make carefully considered choices along the way to creating useful models. In this way one could say that modelling is a craft that can only be learned via intense exercising and ‘learning by doing’. In this course we offer the participants the possibility to learn and exercise the modeling process.
To determine the usefulness of our models, modellers always need to fit and validate their models in comparison with data. As such, a model’s structure is chosen based on comparison of model predictions with data. Optimization techniques are indispensable in this matching process. That’s why a considerable part of this course is spent on getting you acquainted with the optimization techniques that are nowadays available and widely used. With an optimal model to hand, we will then consider how to design experiments to learn more about our biological system of interest and use our model to assess a system’s behaviour.
The course is a mixture of theory sessions and computer practicals.
Learning objectives
The students will be provided with a theoretical basis, a variety of methods, and a computational hands-on experience to set-up systems biology models and handle numerical optimization.
In the course the students will learn:
- To understand the use of models in metabolic, regulatory, signaling, and multi-scale biological processes
- How to set-up a dynamic model to represent biological networks using different interaction mechanisms
- To implement, simulate and analyze dynamic network models
- To understand the wide variety of problems in modelling that can be solved with optimization
- To apply different types of numerical optimization methods
- The combination of dynamic modeling and optimization to integrate experimental data in modelling, estimate model parameters and design experiments.
- To understand how numerical optimization (linear programming) works in flux balance analysis to simulate metabolic network models.
Techniques include:
- Nonlinear differential equations, numerical simulation, parameter sensitivity analysis.
- Parameter estimation, identifiability, uncertainty quantification, experimental design, regularization.
- Global and local search methods: steepest descent, Levenberg-Marquardt, genetic algorithms, linear programming.
Target audience
The course is aimed at PhD students with a background in bioinformatics, systems biology, computer science or a related field, and life sciences. Participants from the private sector are also welcome. A working knowledge of mathematics, especially differential equations, is recommendable, but we will distribute preparation material to be studied by students missing the required background. Furthermore, at the start we offer a math refresher to help those participants who are not (yet) involved in modelling on a daily basis.
Teaching staff
- Dr. Robert Smith, Wageningen University & Research, robert1.smith@wur.nl
- Prof. dr. Aalt-Jan van Dijk, University of Amsterdam, a.d.j.vandijk@uva.nl
- Dr. Hans Stigter, Wageningen University & Research, hans.stigter@wur.nl
- Prof. dr. Natal van Riel, Eindhoven University of Technology, n.a.w.v.riel@tue.nl
- Dr. Dragan Bošnački, Eindhoven University of Technology, d.bosnacki@tue.nl (course coordinator)
Additional information
Examples and computer practical make use of Matlab (toolboxes: Optimization toolbox, Statistics toolbox). A computer with a working version of Matlab is needed and some programming experience and knowledge of Matlab are required to take the course. A short introductory training in Matlab will be made available (online) for those without Matlab skills.
For more information about the course you can contact dr. Dragan Bošnački.
Wildcards
If you would like to join this course using a wildcard, please contact the BioSB community manager. You can register with a wildcard until 26 October 2026, or until the maximum number of wildcard spots is reached, whichever comes first. Please always state in your application which academic group issued the wildcard and attach the wildcard certificate. Your registration is only valid after confirmation from the community manager.
Registration
Early bird registration (until 12 October 2026):
- € 400 (excl. VAT) for PhD/MSc students
- € 600 (excl. VAT) for academic researchers (non-profit)
- € 900 (excl. VAT) industry participants (for profit)
From 13 October 2026 onwards:
- € 480 (excl. VAT) for PhD/MSc students
- € 720 (excl. VAT) for academic researchers (non-profit)
- € 1080 (excl. VAT) industry participants (for profit)
The course fee includes course materials and catering (coffee, tea and lunch).
You can register for the course by filling out the registration form.
Find general enrollment information here.
