|Course coordinator(s)||dr. RW Smith|
|Lecturer(s)||prof. dr. J Molenaar|
|dr. GAK van Voorn|
|dr. RW Smith|
|Examiner(s)||dr. M Suarez Diez|
Language of instruction:
Assumed knowledge on:
Modelling Biological Systems (EZO-23306) or equivalent.
Biological systems are characterized by connections between different components that together may lead to complex and highly dynamic behaviour. A main goal of systems biology is to translate these connections into models that describe and predict the activity of living organisms in their ecosystems. Systems biology depends on mathematical modelling approaches, in order to generate models that help to understand living systems, as well as to predict their future dynamics. Irrespective whether one considers molecular interaction networks or ecosystem level networks, the mathematical tools which are applied can be conceptualized with only small extensions of basic mathematical knowledge and are very similar - systems biology is independent of the level of biological organisation. In this course we will discuss elegant case-studies covering a careful selection of biological systems, showing how mathematical modeling has been applied to biological problems across very different scales, and how modeling is combined with experiments in the systems biology research cycle. The course builds on basic knowledge of students in both mathematics and modeling of biological systems, with emphasis on the integrated perspective of systems biology. From the discussed examples, we will show that the same modeling approach can be used to investigate diverse biological problems at different organization levels, such as predator-prey interactions, multicellular pattern formation and microbial chemotaxis. During the course, students will apply different types of models to describe and predict processes at cellular, organism and ecosystems level.
After successful completion of this course students are expected to be able to:
- explain the basic concepts of systems biology;
- explain with examples that similar networks can describe multiple biological phenomena;
- recall mathematical methods to describe biological systems;
- analyse mathematical models describing the dynamical behaviour of a biological system;
- apply computational tools to describe and analyze the behaviour of dynamical networks.
- computer assisted practicals;
- self-study exercises (20%);
- presentations (10%);
- written exam with open questions (70%).
Will be supplied in Brightspace prior to and during the course.