Gabriel Bianchin de Oliveira

BindScreen improves virtual screening by using a protein-centric contrastive learning approach with asymmetric loss and batch design, achieving better performance with fewer computational resources.

ProtEnrich enhances protein sequence embeddings with biophysical properties without disrupting their semantic structure, improving performance on structure-related tasks.

TITAN-BBB predicts BBB permeability using multi-modal deep learning, achieving high accuracy and error reduction compared to existing methods.

MolDeBERTa is a molecular language model pre-trained on SMILES data with novel objectives to improve property prediction and substructure similarity, outperforming existing models on multiple benchmarks.