Control Engineering
Besides a correct design or layout, good control systems are essential to guarantee that production systems operate and produce according the desired specifications. This course gives an introduction to classical control engineering approaches and discusses the standard methods and tools that are usually applied. The methods discussed in the course have a very wide application
Biology of Plants
In this introductory course on Plant biology, the focus is on understanding the development, structure and functioning of plants. Emphasis is placed on the relations between cellular and molecular processes at one side and the functioning of the whole plant in its environment at the other side. The course consists of a cell biological/structural part
Exploratory Data Analysis in R
lant scientists use a wide range of experimental tools. Be it a simple weight measurement or an advanced imaging analysis, every experiment generates data that must be analyzed. Modern approaches for reproducible data analysis are mostly based on writing scripts in (statistical) programming languages. As such, working in the plant sciences and broader life sciences
Data Analysis & Visualization
Much data is quantitative, and there is a wide range of methods available for the analysis of such data. After a brief introduction to data types and normalisation, a number of visualisation methods will be discussed. Next, methods will be introduced to find groups (clustering), dependencies (regression), significant differences between conditions (hypothesis testing) and to
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
Programming in Python
Programming plays an important role in many domains. In business and science writing or adapting computer programs to process, analyse and visualize data in a suitable format has become common practice. This course aims to help students to understand the underlying principles of programming and equip them with basic skills to create computer programs. The
Introduction to Bioinformatics
Over the last decades, a number of technologies to study DNA, RNA, proteins, metabolites and their interactions has been developed. To understand life at the molecular level, they have been applied in numerous biological and biomedical experiments. Much of the resulting data, as well as the knowledge gained in these experiments, are freely available 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,