APA (7th ed.) Citation

TM, K., PB, B., CJ, B., SC, P., & DC, L. (2018). A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds. Journal of chemical information and modeling, 58(8), 1544. https://doi.org/10.1021/acs.jcim.7b00475

Chicago Style (17th ed.) Citation

TM, Kaiser, Burger PB, Butch CJ, Pelly SC, and Liotta DC. "A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds." Journal of Chemical Information and Modeling 58, no. 8 (2018): 1544. https://doi.org/10.1021/acs.jcim.7b00475.

MLA (9th ed.) Citation

TM, Kaiser, et al. "A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds." Journal of Chemical Information and Modeling, vol. 58, no. 8, 2018, p. 1544, https://doi.org/10.1021/acs.jcim.7b00475.