Bachelor program

Within the bachelor program of the Department of Biology we teach eight courses introducing modeling and bioinformatics to students in biology and the sciences in general. These courses run for 10 weeks, half-time, and each course is 7.5 EC-points. A subset of these courses can be attended by students from all over the world and will be given in English whenever required. Students preparing for the master Bioinformatics and Biocomplexity are advised to attend the bachelor courses listed below and supplement that with biological courses in their field of interest.

Level 1 courses:

Modern biology is accumulating enormous amounts of information resulting in very rich data bases. Additionally, modern biology increasingly involves a systems approach, aiming to understand biological processes from the interactions of its constituent parts Therefore, we aim to introduce at least the basics of bioinformatic pattern recognition, essential to deal with biology’s big data, and the basics of mathematical modeling, crucial for a systems approach, to all students in biology. These topics will be covered as part of the courses Quantitative Biology and Genomics, respectively. These level-1 courses are given to a large (>200) group of students.

Quantitative Biology (Kwantitatieve Biologie)

In the first half of this course, you will be introduced to the programming language R and learn the basics of statistics. The second part of the course starts with an introduction to mathematics of non-linear differential equations (ODEs). Students learn to analyze models by phase plane methods (i.e., nullclines and local stability analysis). After mastering these mathematical skills, the remainder of the course focuses on interpreting results from mathematical models in biological terms. Reviewing classical modeling examples from a variety of biological disciplines, students learn to translate between mathematical models and biological insight.

For this course basic knowledge of working with fractions, logarithms, exponentials, differentiation, drawing of functions, solving equations, etc. is essential. Students will brush up their knowledge of these mathematical subjects during the first part of the course using the electronic mathematics environment DWO. For students wanting to further brush up these we have compiled the following site (in Dutch).

Genomics (Genomica)

In the first part of the course, you will gain insight into the principles and concepts of classical and systems genetics, genetic techniques, genotype-phenotype interactions and how genes can be identified and investigated. The second part of the course gives an introduction in bioinformatics methods (like clustering, building phylogenies, sequence alignment and blast). We aim to explain how these methods work and how they have contributed to biological research.

Level 2 courses:

Biological modeling (Biologische modellering)

Mathematical modeling plays an important role in biological research. This course covers modeling biological populations, e.g., populations of bacteria and phages, cells, epidemics, and ecological populations. We derive these models from biological principles, such that students learn how to develop models themselves. In the first part of the course, we devise models for population growth, consumption of resources, and competition. This leads to models resembling the Lotka-Volterra model, predator-prey models with various functional responses, and various models for competitive exclusion and co-existence. Students learn to compute steady states and perform phase plane analysis to study the properties of their models, and to interpret these mathematical properties biologically. We work with paper-and-pencil exercises and a R-script called Grind to perform phase plane analysis, stability analysis, and simulation. In the second part of the course, we read several papers, and students work on their own research project that typically starts with a recent paper. Results are reported in a symposium and a written report. This is a level-2 course for motivated groups of 30-40 students. We require participants to have a basic knowledge of differential equations (i.e., the material taught in our level-1 Quantitative biology course), and/or have a sufficient background in math or modeling such that they can catch up. The home page provides general information about the course content (in English).

Data science and biology (Data science en biologie)

This time is characterized by the enormous amount of available data. These so-called ‘big data’ are especially abundant in biology since affordable high-throughput DNA sequencing technologies exist, by which an enormous number of genomes, metagenomes, transcriptomes, epigenomes, and variations thereof are generated. Also in other biological disciplines big data files are no longer rare. In this course you learn the theory and skills to obtain novel biological insights from big data files. In the Quantitive Biology and Genomics courses, you have already become familiar with programming and these skills will be sharpened in this course. You will learn to use the Unix terminal and to write scripts in Python. The focus will be on how to go from a big table with numbers to a visualization that gets the data structure clearly across. Moreover, an introduction to machine learning will be given: how to cluster or classify data and how to make predictions for new data points based on existing data?

Level 3 courses:

Computational Biology (Computationele Biologie)

The emphasis of this course is on composing exact models, based on specific hypotheses, in different formalisms (ODEs, cellular automata, agent based models). The models are analyzed, the results yielding insights in the original biological system. The models that are studied address fundamental questions from a variety of biological fields like evolution, development, and behavior. This is a level-3 course given at two levels for bachelor and master students. For practical information please read more.

ImmunoBiology (Immunobiologie)

The immune system comprises innate and acquired defense mechanisms against (pathogenic) microorganisms. Immunology has traditionally been a qualitative science describing the cellular and molecular components of the immune system and their functions. In the last twenty years this traditional approach is being replaced by a systems biology approach, where theoretical studies helps to interpret experimental data, to resolve controversies, and --most importantly-- to suggest novel experiments allowing for more conclusive and more quantitative interpretations. This course is planned to give an overview of wet and theoretical immunological research. We aim to provide insight into the function of the immune system in health and disease and to give an introduction to the use of mathematical models and bioinformatics in immunological research. For practical information please read more.

Genome Biology (Genoombiologie)

Biology is increasingly being performed at the genome-wide level and this level 3 course deals with various aspects of this research. The first three weeks of this course are focusing on genome-organisation, the second three weeks centre around genome evolution, and the third week deals with the steps from the genome to the phenotype. Altough this course is coordinated by Guido van den Ackerveken, our department is heavily involved in this course because of the importance of bioinformatics in genome-wide analyses and our knowledge of genome evolution.