Breeding for Abiotic Stress Tolerance
Abiotic stress is the stress imposed on plants by the non-living environment. Abiotic stress is responsible for huge yield losses in crops around the world. In this course we will assess the impact that abiotic stresses (like drought, salinity, nutrient deficiency, temperature) have on agricultural production, and provide you with knowledge and tools for successfully
Genome Bioinformatics
Complex biological systems arise from interactions between molecules, cells, organisms, and their environment. The genome serves as the blueprint for these interactions and is shaped by 4 billion years of evolution. With advances in sequencing technologies, researchers can now collect large-scale genomic datasets from species, populations, and environments. In this course, students explore how such
Advanced Bioinformatics (WUR)
This course covers the process of bioinformatics data analysis and the interpretation of the results in a biological context. The following topics will be addressed in the course: command line usage, programming/scripting, current bioinformatics data analysis tools, and automated analysis pipelines. The first part of the course will cover command line usage (linux), bioinformatics script
Plant Development & Environment
Plants are continuously challenged by sometimes life-threatening changes in their environment. These can severely impact their development and even kill plants. Interestingly, plants can flexibly adjust their development to deal with these environmental changes. They can for example adjust root anatomy to resist drought, overall root architecture to forage for nutrients, and shoot architecture to
The Power of Microbes
Theory Microbes play an essential role in sustaining higher life forms on Earth, including marine sponges, plants, fish, and animals. Their significance lies in their vast diversity of physiological traits, allowing them to thrive in various environments by extracting energy from organic resources, minerals, and light. In fact, many microbes depend on other microbes for
Data Driven Discovery in the Life Sciences: Hypothesis Generation from Omics Data
Across the life sciences, scientists utilize omics data to study biological phenomena in humans, plants, animals and microbes. This results in large and heterogeneous data sets that can be analyzed using a variety of algorithms and statistical methods. Making sense of the data, extracting biological knowledge out of the results of these analyses and formulating
Biological Discovery through Computation
Multiple types of -omics data are rapidly changing the face of biological research. In the Bioinformatics minor, students have been exposed to fundamental computational techniques to analyse and visualise omics data. Students enrolled in the Omics minor have also explored technologies and data analysis methods to deal with the “wet” and “dry” components of omics
Seed Science and Technology
Seeds are not only the world’s major source of human and animal nutrition but also provide the basis for improving agricultural practices and managing genetic resources. High-quality seeds are required for successful crop production, propagation and breeding. Seed quality comprises a multitude of processes and events that occur during the successive stages of seed development,
Computational Biology
This course focuses on using computational modelling to explore biological systems and test specific hypotheses. Students learn to construct exact models and analyse their behaviour to gain insight into the original biological system. The course draws on a broad range of biological questions across evolutionary, developmental, ecological, and molecular biology. Topics include evolutionary dynamics such
Markers in Quantitative Genetics and Plant Breeding (online)
In this course, the students will be made familiar with the use of molecular markers in genetic research and plant breeding, the estimation of genetic distance based on marker genotype frequencies in different types of segregating populations, the construction of linkage maps, concepts and applications of quantitative genetics, the analysis of quantitative trait loci (QTLs)