APA (7th ed.) Citation

Morris, D. J., Kennedy, L., & Black, A. J. (2025). Random time-shift approximation enables hierarchical Bayesian inference of mechanistic within-host viral dynamics models on large datasets. PLoS Computational Biology, 21(12), 1. https://doi.org/10.1371/journal.pcbi.1013775

Chicago Style (17th ed.) Citation

Morris, Dylan J., Lauren Kennedy, and Andrew J. Black. "Random Time-shift Approximation Enables Hierarchical Bayesian Inference of Mechanistic Within-host Viral Dynamics Models on Large Datasets." PLoS Computational Biology 21, no. 12 (2025): 1. https://doi.org/10.1371/journal.pcbi.1013775.

MLA (9th ed.) Citation

Morris, Dylan J., et al. "Random Time-shift Approximation Enables Hierarchical Bayesian Inference of Mechanistic Within-host Viral Dynamics Models on Large Datasets." PLoS Computational Biology, vol. 21, no. 12, 2025, p. 1, https://doi.org/10.1371/journal.pcbi.1013775.