Mateo Torres

Integrating structural homology with deep learning to achieve highly accurate protein-protein interface prediction for the human interactome

The paper introduces PIONEER2, a method that improves protein-protein interface prediction by integrating structural homology and deep learning, outperforming AlphaFold3 in certain scenarios.

Structurally-informed human interactome reveals proteome-wide perturbations by disease mutations

The paper introduces PIONEER, a deep learning framework for predicting protein-protein interfaces, and shows disease mutations are enriched in these interfaces, identifying oncoPPIs linked to cancer survival and drug responses.

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

The paper reports results from the CAFA3 challenge, showing improved computational protein function prediction and new annotations for over 1000 genes through experimental screens in C. albicans, P. aureginosa, and Drosophila.