This course introduces computational modeling of large (genome-scale) metabolic reaction networks through a scalable framework known as constraint-based modeling. Emphasis will be on the usage in both biotechnology and systems biomedicine. Main topics will be fundamental constraint-based modeling methods, omics data integration, multi-scale modeling and microbial community modeling. The course will combine theoretical lectures with tutorial exercises and computational exercises in Python.
Register for the course by filling out the registration form (early bird until 7 December, 2026).
Course coordinators
- prof. dr. Maria Suarez Diez, Wageningen University
- dr. Marian Breuer, Maastricht University
Course credits
Students receive 1.5 ECTS credits for following the course (five consecutive days).
Course description
Constraint-based modeling is a powerful modeling framework that allows to model reaction fluxes in genome-scale metabolic network models, with uses in fundamental and applied questions relevant to biotechnology, microbiology and biomedicine. These genome-scale metabolic models encompass all metabolic reactions encoded in an organism, possibly contextualized to a particular cell type and condition. Constraint-based modeling provides a scalable framework to analyze these large-scale models, whether they describe microbes, human cells in health and disease or multi-cellular systems like microbiota and the whole body. In this course, you will be introduced to:
- the principles of constraint-based reconstruction and analysis (COBRA)
- the underlying mathematical foundations of constraint-based modeling
- content, structure and reconstruction of genome-scale metabolic models
- basic and advanced methods for interrogating models and interpreting results
- methods for integration of omics data with genome-scale metabolic models
- multi-scale applications, in particular dynamic Flux Balance Analysis
- constraint-based modeling of microbial communities
- open source COBRA software, with a focus on the Python package COBRApy
- standards for reconstruction and model sharing
- example applications to biomedicine and biotechnology
The course is structured into both lectures and practical sessions so that theory can be illustrated with biologically motivated computational examples.
Learning objectives
- Introduction to COBRA
- Proficiency with the COBRApy package in Python
- Familiarity with typical applications of constraint-based modeling in biomedicine and biotechnology
Target audience
Constraint-based modeling is a rapidly growing field that is being used in both fundamental and applied research and biotechnology. It sits at the intersection between quantitative modeling, bioinformatics and cellular physiology, and as such, is an example of systems biology at work.
While participants would benefit from some knowledge of either quantitative modeling, bioinformatics or metabolism this is not required. This includes, for example, scientists working in a laboratory and wanting to learn more about building or using genome-scale metabolic models, as well as those who have used some basic COBRA methodologies, but want to know how else it can be applied to their research.
Lecturers
- Maria Suarez Diez (Wageningen University)
- Marian Breuer (Maastricht University)
- Djordje Bajic (Delft University of Technology)
- Jose Diogo Cruz de Moura (Wageningen University)
- …
Additional information
For practical sessions, participants require their own laptop with Python and the package COBRApy pre-installed (see instructions).
For more information about the course you can contact Maria Suarez Diez or Marian Breuer.
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 21 December 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 7 December 2026):
- € 400 (excl. VAT) for PhD/MSc students
- € 600 (excl. VAT) for academic researchers (non-profit)
- € 900 (excl. VAT) industry participants (for profit)
From 8 December 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.
You can register for the course by filling out the registration form.
Find general enrollment information here.
