Immunology
Immunology, Oncology & Evolution
Immune recognition is often modeled through narrow proxies such as binding affinity, even though real immunogenicity depends on presentation, recognition, selection, and evolutionary context. This work asks how better representations of antigenicity and counterfactual selection could improve reasoning about tumors, viruses, and immune targets.
This section gathers scientific and modeling work in computational immunology, cancer immunology, and viral evolution.
The emphasis is on biological representation, mechanistic uncertainty, and models that make scientific claims easier to test, criticize, and revise.
Selected documents and links will be added as the work archive is organized.