3 papers
q-bio.BM2026
AI Developments for T and B Cell Receptor Modeling and Therapeutic Design
Linhui Xie, Aurelien Pelissier, Yanjun Shao +1
Artificial intelligence (AI) is accelerating progress in modeling T and B cell receptors by enabling predictive and generative frameworks grounded in sequence data and immune conte…
q-bio.BM2025
AbRank: A Benchmark Dataset and Metric-Learning Framework for Antibody-Antigen Affinity Ranking
Chunan Liu, Aurelien Pelissier, Yanjun Shao +4
Accurate prediction of antibody-antigen (Ab-Ag) binding affinity is essential for therapeutic design and vaccine development, yet the performance of current models is limited by no…
q-bio.QM2023
T cell receptor binding prediction: A machine learning revolution
Anna Weber, Aurélien Pélissier, María Rodríguez Martínez
Recent advancements in immune sequencing and experimental techniques are generating extensive T cell receptor (TCR) repertoire data, enabling the development of models to predict T…