Yan, J.;                     Chen, Z.;                     Cai, J.;                     Xian, W.;                     Wei, X.;                     Qin, Y.;                     Li, Y.    
        Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges. Appl. Sci. 2025, 15, 7363.
    https://doi.org/10.3390/app15137363
    AMA Style
    
                                Yan J,                                 Chen Z,                                 Cai J,                                 Xian W,                                 Wei X,                                 Qin Y,                                 Li Y.        
                Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges. Applied Sciences. 2025; 15(13):7363.
        https://doi.org/10.3390/app15137363
    
    Chicago/Turabian Style
    
                                Yan, Jielu,                                 Zhengli Chen,                                 Jianxiu Cai,                                 Weizhi Xian,                                 Xuekai Wei,                                 Yi Qin,                                 and Yifan Li.        
                2025. "Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges" Applied Sciences 15, no. 13: 7363.
        https://doi.org/10.3390/app15137363
    
    APA Style
    
                                Yan, J.,                                 Chen, Z.,                                 Cai, J.,                                 Xian, W.,                                 Wei, X.,                                 Qin, Y.,                                 & Li, Y.        
        
        (2025). Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges. Applied Sciences, 15(13), 7363.
        https://doi.org/10.3390/app15137363