Within the bachelor program of the department of biology we give five 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. Courses typically involve lectures in the morning and paper-and-pen and/or computer practicals in the afternoon. As a preparation for a master track in our group you should have completed at least the Bioinformatic processes course, but we recommend that you attend all of our bachelor courses. Courses can be attended by students from all over the world, and will be given in English whenever required. Students preparing for a master in Theoretical Biology and Bioinformatics are advised to attend the bachelor courses listed here and supplement that with biological courses in their field of interest.
Because modern biology is accumulating enormous amounts of information about complex regulatory systems in very rich data bases, we aim to introduce at least the basics of bioinformatic pattern recognition and the basic of mathematical modeling to all students in biology. The first part of this course is 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 second part 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. The third part of the course is an introduction in bioinformatic methods (like clustering, phylogeny, sequence alignment and blast). We aim to explain how these methods work and how they have contributed to biological research. This is a level-1 course given to a large (>200) group of students. For practical information (in Dutch) please read more.
Mathematical modeling plays an important role in biological research. This course is about 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 reseach 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 Systems 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). Practical information is provided in Dutch and English.
Computational Biology (Bioinformatic processes)
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.
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.
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.