Lecturer: Johannes Textor
Fields: Immunology, Artificial Intelligence, Machine Learning
Content
Our body harbours two complex learning systems: the central nervous system (CNS), and the adaptive immune system (IS). Artificial neural network models of the CNS have contributed substantial insight to neuroscience and CNS-inspired “deep learning” has revolutionized artificial intelligence. In contrast, how the IS processes information is still much less understood. This course will therefore ask: how can we understand information processing, learning and adaptation in the IS through the lens of computer science?
We will dive deep into several fascinating processes in the adaptive immune system such as negative selection, self-foreign discrimination, tolerance, and affinity maturation. I will cover the necessary immunological background to come to an understand of what we do and don’t know about these processes, and discuss how computational and mathematical models have been instrumental in our quest to understand the immune system from a computational perspective. I hope you will leave this course as fascinated and inspired by the marvelous architecture of our immune system as I am, and that this inspiration will transform and broaden your view of fundamental concepts like learning, adaptation, and generalization.
Literature
- Inge M N Wortel, Can Keşmir, Rob J De Boer, Judith N Mandl, Johannes Textor:
- Is T Cell Negative Selection a Learning Algorithm? Cells 9(3): 690, 2020. doi: 10.3390/cells9030690
- Marsland R 3rd, Howell O, Mayer A, Mehta P. Tregs self-organize into a computing ecosystem and implement a sophisticated optimization algorithm for mediating immune response. Proc Natl Acad Sci U S A. 2021 Jan 5;118(1):e2011709118. doi: 10.1073/pnas.2011709118.
- Jürgen Westermann, Tanja Lange, Johannes Textor, Jan Born:
- System Consolidation During Sleep – A Common Principle Underlying Psychological and Immunological Memory Formation.
- Trends in Neurosciences 38: 583-595, 2015.
- Stephanie Forrest, Steven A. Hofmeyr, Anil Somayaji. Computer Immunology. Communications of the ACM 40, 1997, pp 88–96. https://doi.org/10.1145/262793.262811
Lecturer
Johannes Textor is an associate professor in the Data Science and Medical BioScience departments at Radboud University and Radboud University Medical Center in Nijmegen, The Netherlands. His team studies the adaptive immune system through the lens of computation and learning. Building in silico models of the human immune system and combining these with various types of experimental data, they aim to understand the essence of what makes immune systems learn and adapt to changing environments. Johannes Textor holds a Vidi grant from the Dutch Research Council, a program grant from the Human Frontiers Science foundation, and was a visiting scholar at the Simons Institute, UC Berkeley, for the Spring 2022 semester.
Affiliation: Radboud University Nijmegen
Homepage: johannes-textor.name