Agenda Mini-symposium

31 March 2025

Pieter Meysman, University of Antwerp

Abstract

The combination of high-throughput immunosequencing technologies and dedicated machine learning models have great potential to advance our understanding of the human immune system and unlock novel diagnostic applications. However underlying biases and a lack of ground truth hinders the development of these novel computational frameworks. In this talk, I will discuss recent public and dedicated efforts to benchmark machine learning efforts for the T-cell receptor epitope prediction problem, and how despite their current limitations, these methods are already providing novel immunological insights.

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