Robin Rydbergh

AI-guided discovery for low-resource peptide engineering using evolutionary scale modeling

It is demonstrated that CV R² computed from as few as 50 labeled peptides can be sufficient to estimate final active learning end-point performance, providing a practical, data-efficient criterion for deciding whether a given dataset combined with SCARSE is suitable for iterative peptide discovery.