MATE-Pred: Multimodal Attention-based TCR-Epitope interaction Predictor

no code implementations • 5 Dec 2023 • Etienne Goffinet, Raghvendra Mall, Ankita Singh, Rahul Kaushik, Filippo Castiglione

Here, we propose a highly reliable novel method, MATE-Pred, that performs multi-modal attention-based prediction of T-cell receptors and epitopes binding affinity.

Drug Discovery

Forum on immune digital twins: a meeting report

no code implementations • 26 Oct 2023 • Reinhard Laubenbacher, Fred Adler, Gary An, Filippo Castiglione, Stephen Eubank, Luis L. Fonseca, James Glazier, Tomas Helikar, Marti Jett-Tilton, Denise Kirschner, Paul Macklin, Borna Mehrad, Beth Moore, Virginia Pasour, Ilya Shmulevich, Amber Smith, Isabel Voigt, Thomas E. Yankeelov, Tjalf Ziemssen

If medical digital twins are to faithfully capture the characteristics of a patient's immune system, we need to answer many questions, such as: What do we need to know about the immune system to build mathematical models that reflect features of an individual?