In order to get a grip on the enormous complexity of biological systems, mathematical and computational methods are becoming increasingly popular. This is relevant for the understanding of biological systems and to predict how drugs can influence these systems. In this course, students will get acquainted with such mathematical and computational methods and how they can be applied to data from various applications (including networks of molecular interactions within cells; behavior of cell populations; migration of cells; interactions between living organisms and drugs). Moreover, there is a bio- and cheminformatic component. Herein students learn to computationally analyze protein sequences as well as ‘small molecules’, and ultimately model interactions between them.
Learn how to formulate and analyse differential equation models, how to apply them to biological networks, cell populations, and organisms and how to exploit them in drug discovery
Learn how spatial effects can be modeled and to apply these techniques to biological systems, e.g., to describe tumor growth or cell migration
Learn how to apply bio- and cheminformatic tools from publicly available resources
Learn to use structure-activity relationships and structure-based computational chemistry
Learn how population models can be used to optimize and individualize drug treatment for patients.
Literature will be provided during the course.
Dr. J.B. Beltman
Mode of instruction
The course will use a combination of lectures (1-2 hours per day, usually in the morning) and pen & paper or computer exercises (3-4 hours per day, usually in the afternoon).
For the hands-on part of the course covering bio- and cheminformatics, the students write a report and give an oral presentation. The report needs to be of sufficient quality to pass the course, which means that it is complete (all parts of the practical should be covered) and is of scientific quality (i.e., references when needed , figure / table number and captions, presence of abstract / intro / methods / results / discussion / conclusion sections). The grade for the presentation will make up 10% of the final grade. Moreover, a written exam will make up 90% of the grade. Presence and active participation during the working groups (mainly computer assignments) is mandatory.
Admission requirements & Registration
This course is mandatory for and restricted to students who do the Minor ‘Computational approach to Disease Signaling and Drug Targets’ (CADSDT; the entire Minor or only Part 1). The same admission criteria apply to this course as for the Minor CADSDT (see Appendix 3 of the Education and Exam regulation BSc Programmes (OER)).