Statistical Insights into the Immune Receptor Code Biological systems explore vast spaces of possibility, yet their function is often robust to certain variations while remaining exquisitely sensitive to others. A striking example is the hypervariable repertoire of T cell receptors, which underlies the specificity of the cellular immune response. Can we construct principled coarse-grained descriptions of this diversity that retain functionally relevant variation? In this talk, I will discuss our recent progress on this question. First, I will show how we can quantify, in bits, the information that different receptor regions provide about antigen specificity. Second, I will describe our initial attempts to train protein language models to predict which receptors recognise common targets. Finally, I will reflect on how principled coarse-graining approaches might help us find statistical structure in biological complexity across scales. This article was published on 2025-04-22
