Explore a thought-provoking lecture on the predictive capabilities of living systems, focusing on the adaptive immune system as a dynamic Bayesian machinery. Delve into how complex biological systems, particularly the immune system, attempt to calculate and predict future environmental states despite their stochastic nature. Discover the reproducible observables in the immune system and learn how it updates its memory repertoire by balancing new pathogen encounters with past infection experiences. Examine the process of weighing trust in new observations against prior experiences in predicting and preparing for future threats. Follow the lecture's structure, covering topics such as diversity, selection, prediction, timescales, and recognition space in immune repertoires. Gain valuable insights into the intersection of biology, immunology, and predictive modeling from Aleksandra Walczak of Ecolé Normale Supérieure in this 54-minute Santa Fe Institute presentation.
Overview
Syllabus
Introduction
All living systems predict
Adaptive immune system
Data
Diversity
Selection
Prediction
Results
Timescale
Recognition space
Conclusion
Taught by
Santa Fe Institute