Computational Thinking is an essential skill for the 21st-century. It is a method for problem solving, a prerequisite for learning to write computer scripts and to conduct computational drug research.
In this course, we will explore examples of computational thinking in drug research. We will start with a computational view on mathematical equations, limits, partial derivatives and graphs of functions. We will then explore the structure and use of databases, including data-analysis procedures. Furthermore, we will have a look at algorithms and applications in pharmacology, toxicology, bio- and cheminformatics. A substantial part of the course will be hands-on-training in scripting your own computer programs in R.
The student is able to:
Solve mathematical equations, calculate limits and partial derivatives and draw graphs of functions
Program an R-script to format and analyze a dataset and visualize the data
Evaluate and apply good practices of data-management
Set up a basic structure and usage for databases in MySQL
Select and apply the optimal approach from an array of computational methods, for a given biomedical use case
Literature will be provided during the course.
Dhr. Dr. S. Wink
Mode of instruction
Practical course, consisting of: lectures, demonstrations, computer exercises, literature research and a group assignment.
Students will be assessed on the following modalities:
Weekly scripting tests (20%)
Group data-analysis assignment (20%)
Total grade = 100%
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 Minor ‘Modern Drug Discovery’ (MDD) and the Elective Module ‘DSDT’. The same admission criteria apply to this course as for the respective afore mentioned programs.