Lin, B.M.;                     Cho, H.;                     Liu, C.;                     Roach, J.;                     Ribeiro, A.A.;                     Divaris, K.;                     Wu, D.    
        BZINB Model-Based Pathway Analysis and Module Identification Facilitates Integration of Microbiome and Metabolome Data. Microorganisms 2023, 11, 766.
    https://doi.org/10.3390/microorganisms11030766
    AMA Style
    
                                Lin BM,                                 Cho H,                                 Liu C,                                 Roach J,                                 Ribeiro AA,                                 Divaris K,                                 Wu D.        
                BZINB Model-Based Pathway Analysis and Module Identification Facilitates Integration of Microbiome and Metabolome Data. Microorganisms. 2023; 11(3):766.
        https://doi.org/10.3390/microorganisms11030766
    
    Chicago/Turabian Style
    
                                Lin, Bridget M.,                                 Hunyong Cho,                                 Chuwen Liu,                                 Jeff Roach,                                 Apoena Aguiar Ribeiro,                                 Kimon Divaris,                                 and Di Wu.        
                2023. "BZINB Model-Based Pathway Analysis and Module Identification Facilitates Integration of Microbiome and Metabolome Data" Microorganisms 11, no. 3: 766.
        https://doi.org/10.3390/microorganisms11030766
    
    APA Style
    
                                Lin, B. M.,                                 Cho, H.,                                 Liu, C.,                                 Roach, J.,                                 Ribeiro, A. A.,                                 Divaris, K.,                                 & Wu, D.        
        
        (2023). BZINB Model-Based Pathway Analysis and Module Identification Facilitates Integration of Microbiome and Metabolome Data. Microorganisms, 11(3), 766.
        https://doi.org/10.3390/microorganisms11030766