Transforming Food Systems
General description of the content This course will focus on the dynamics in food systems globally from a governance and transition studies perspective. We will identify the different actors involved, their roles and interests, and their relationships and interactions. Next, we will focus on processes of transformations towards more sustainable and healthy food systems (at
Data Science and Biology
This course focuses on applying data science methods to biological data. With the rise of high-throughput techniques in biology, massive datasets are now common, including genomes, metagenomes, transcriptomes, and more. The course equips students with the theoretical and practical skills to extract insights from such data. Students learn to work with the command-line interface, write
Modelling biological systems
Biological systems are arguably the most complex systems science tries to understand. We make observations, and try to obtain useful insight in the systems. This requires hypotheses; ideas of how we believe the world around us is structured and operates. Models translate our hypotheses into concrete predictions about our objects of study that can be
Breeding for Stress Tolerance and Quality
In current agriculture, abiotic and biotic stress are the main reasons that yield potential and quality aspects are difficult to realize for many crops. Resistance breeding focuses on the use of genetic resources for improving plant defence against stress factors. Breeding for biotic stress resistance addresses with defence mechanisms and strategies that protect host plants
Controlled Environment Agriculture
Life-long learning:6 courses on image analysis, greenhouse horticulture (summer school)
Ecogenomics
The field of ecological genomics strives to uncover the genetic and molecular mechanisms influencing responses and adaptations of organisms to their environment. Achieving this aim requires insight in evolution and selection pressure and how that results in natural variation. Using this natural variation to study mechanisms requires a good understanding of both ecologically important phenotypes
Modelling and Problem Solving
The course covers major (combinatorial) solving approaches, namely constraint programming, integer programming, boolean satisfiability, dynamic programming and decision diagrams, and local search. The course focuses on modelling practical problems, expressing them in the surveyed paradigms; algorithms for solving such problems are covered in the follow-up “Constraint Solving” course. The topic of genetic algorithms is reserved
Sustainable food systems
Our current globalized food system is often at the core of the pressure on sustainable development goals such as life on land, life below water, and water and sanitation, while failing to meet goals such as zero hunger and no poverty. Understanding the causes of the current unsustainable situation and developing solutions to stimulate a
Master Level Computational Biology
During the course, the emphasis will be on composing and analysing exact computational models based on specific biological hypotheses. These models are used to gain insight into the dynamics of biological systems across various fields. Topics include multi-level evolution, such as pre-biotic evolution, eco-evolutionary dynamics, spatial pattern formation, and genome evolution—for instance, the interaction between
Plant Breeding and Biotechnology
This course provides knowledge on recent developments in plant breeding and future prospects in plant biotechnology. A thorough understanding of genetics, plant breeding and biotechnology tools including genetic modification and gene editing is linked to applications in various fields (crop improvement, biofortification, soil remediation and biofuel production). After a general introduction into a field, recent