Computational Immunology

This course will focus on different computational techniques that are currently used to study the immune system. It will cover a range of biostatistical techniques, computational techniques to handle big data, and mathematical models. With these concepts, you will be able to design a study, analyze and interpret the resulting data, and critically read immunological papers using computational techniques. Each day, introductory lectures on specific topics will be followed by computer practical sessions in which participants will put into practice the introduced techniques.

At the end of the course, participants should:

• be able to choose the appropriate statistical test for different circumstances
• understand the principles underlying hypothesis-driven and hypothesis-generating bioinformatic analysis
• be able to explain which computational techniques should be used in which circumstances
• be able to apply different computational methods for the analysis of biological big data
• be able to make a prediction model and judge its quality
• be able to judge papers using computational techniques
• understand how a biological phenomenon can be translated into a mathematical model
• be able to translate unexpected modelling results into intuitive understanding

3 weeks, fulltime

Exam: 11 December 2026, 13:30 - 16:30

Note: these times might be subject to change. The exact time and place will be announced as soon as possible in the learning environment and any changes announced there will overrule the information here.

If you want to receive the Course Certificate and the credits, it is obligatory to take the exam.

General questions

For general questions, please contact:

Content questions

For specific questions about the course content, please contact:

To enroll in this course, you need:

• Basic knowledge of immunology
  The following two short weblectures are a good representation of the prerequisite knowledge in immunology:
  • The immune system an overview innate immunity
  • The immune system an overview adaptive immunity
• Sufficient proficiency in English reading and writing

Recommended study materials:

• The primary study material will consist of handouts, specifically made for this course
• Immunology:  Abbas, Abdul K., Cellular and Molecular Immunology, 10th edition, Elsevier. Electronically available via University Library.
• (highly recommended) Introduction to R:  even though knowledge of R is not a prerequisite, it is very useful to know the basics of R while attending the course.  

Please note that this course is part of an existing program within the Graduate School of Life Sciences. Tuitition fees may alter during the year.