Rechercher
Cournoyer, A., Berner, M.-È., Aboubacar, H., de Toro-Martín, J., Vohl, M.-C., Ravallec, R., Cudennec, B. and Bazinet, L. 2025. Machine learning-driven discovery of bioactive peptides from duckweed (Lemnaceae) protein hydrolysates: Identification and experimental validation of 20 novel antihypertensive, antidiabetic, and/or antioxidant peptides. Food Chem., 482:144029.
Rahimi, D., Sanchez-Reinoso, Z., Thibodeau, J., García-Vela, S., de Toro-Martín, J., Vohl, M.-C., Fliss, I., Mikhaylin, S. and Bazinet, L. 2025. Exploring novel antifungal peptides from peptic hydrolysis of chicken cruor protein via regression-based machine learning approach. Food Chem., 471:142606.
Sanchez-Reinoso, Z., Bazinet, M., Leblanc, B., Clément, J.-P., Germain, P. and Bazinet, L. 2025. Application of machine learning tools to study the synergistic impact of physicochemical properties of peptides and filtration membranes on peptide migration during electrodialysis with filtration membranes. Sep. Purif. Technol., 360(2):130877.
Cournoyer, A., Bazinet, L., Clément, J.-P., Plante, P.-L., Fliss, I. and Bazinet, L. 2025. How peptide migration and fraction bioactivity are modulated by applied electrical current conditions during electromembrane process separation: A comprehensive machine learning-based peptidomic approach. Food Res. Int., 200:115417-115444.