Carolina Muñoz-Camargo

This study evaluates AI-prioritized antimicrobial peptides derived from Malassezia furfur genomes, showing their antimicrobial activity and highlighting AI prediction biases.

This study investigates how antimicrobial peptides LL-37 and ATRA-1 alter lipid composition and membrane biophysical properties in Staphylococcus aureus, revealing peptide-specific lipid remodeling responses.

PharmaNet uses deep RNNs to predict drug-target interactions, achieving high accuracy in ligand prediction and identifying potential antiviral compounds.