Manjima Dhar

The paper develops MHC Attention, a deep learning model, and combines it with high-throughput screening to identify novel HLA-E presented cancer peptides.

IMMREP25 evaluates TCR:pMHC binding prediction for unseen peptides, showing improved performance with structural modeling but still below random guessing.

TAPIR predicts TCR-target interactions, including novel targets, using a deep CNN model trained on diverse TCR sequences and targets.