Quitté, L.;                     Leclercq, M.;                     Prunier, J.;                     Scott-Boyer, M.-P.;                     Moroy, G.;                     Droit, A.    
        A Machine Learning Approach to Identify Key Residues Involved in Protein–Protein Interactions Exemplified with SARS-CoV-2 Variants. Int. J. Mol. Sci. 2024, 25, 6535.
    https://doi.org/10.3390/ijms25126535
    AMA Style
    
                                Quitté L,                                 Leclercq M,                                 Prunier J,                                 Scott-Boyer M-P,                                 Moroy G,                                 Droit A.        
                A Machine Learning Approach to Identify Key Residues Involved in Protein–Protein Interactions Exemplified with SARS-CoV-2 Variants. International Journal of Molecular Sciences. 2024; 25(12):6535.
        https://doi.org/10.3390/ijms25126535
    
    Chicago/Turabian Style
    
                                Quitté, Léopold,                                 Mickael Leclercq,                                 Julien Prunier,                                 Marie-Pier Scott-Boyer,                                 Gautier Moroy,                                 and Arnaud Droit.        
                2024. "A Machine Learning Approach to Identify Key Residues Involved in Protein–Protein Interactions Exemplified with SARS-CoV-2 Variants" International Journal of Molecular Sciences 25, no. 12: 6535.
        https://doi.org/10.3390/ijms25126535
    
    APA Style
    
                                Quitté, L.,                                 Leclercq, M.,                                 Prunier, J.,                                 Scott-Boyer, M.-P.,                                 Moroy, G.,                                 & Droit, A.        
        
        (2024). A Machine Learning Approach to Identify Key Residues Involved in Protein–Protein Interactions Exemplified with SARS-CoV-2 Variants. International Journal of Molecular Sciences, 25(12), 6535.
        https://doi.org/10.3390/ijms25126535