APA (7th ed.) Citation

Kelch, M. A., Vera-Guapi, A., Beder, T., Oswald, M., Hiemisch, A., Beil, N., . . . Koenig, R. (2023). Machine learning on large scale perturbation screens for SARS-CoV-2 host factors identifies β-catenin/CBP inhibitor PRI-724 as a potent antiviral. Frontiers in microbiology, 14, . https://doi.org/10.3389/fmicb.2023.1193320

Chicago Style (17th ed.) Citation

Kelch, Maximilian A., et al. "Machine Learning on Large Scale Perturbation Screens for SARS-CoV-2 Host Factors Identifies β-catenin/CBP Inhibitor PRI-724 as a Potent Antiviral." Frontiers in Microbiology 14 (2023). https://doi.org/10.3389/fmicb.2023.1193320.

MLA (9th ed.) Citation

Kelch, Maximilian A., et al. "Machine Learning on Large Scale Perturbation Screens for SARS-CoV-2 Host Factors Identifies β-catenin/CBP Inhibitor PRI-724 as a Potent Antiviral." Frontiers in Microbiology, vol. 14, 2023, https://doi.org/10.3389/fmicb.2023.1193320.