3 papers
q-bio.QM2025
Integrating protein sequence embeddings with structure via graph-based deep learning for single-residue property prediction
Kevin Michalewicz, Mauricio Barahona, Barbara Bravi
Understanding the intertwined contributions of amino acid sequence and spatial structure is essential to explain protein behaviour. Here, we introduce INFUSSE (Integrated Network F…
q-bio.QM2025
Machine learning approaches for interpretable antibody property prediction using structural data
Kevin Michalewicz, Mauricio Barahona, Barbara Bravi
Understanding the relationship between antibody sequence, structure and function is essential for the design of antibody-based therapeutics and research tools. Recently, machine le…
q-bio.QM2025
Protein generation with embedding learning for motif diversification
Kevin Michalewicz, Chen Jin, Philip Alexander Teare +4
A fundamental challenge in protein design is the trade-off between generating structural diversity while preserving motif biological function. Current state-of-the-art methods, suc…