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Found 4 papers, 2 papers with code
A closer look at parameter identifiability, model selection and handling of censored data with Bayesian Inference in mathematical models of tumour growth
Mathematical models (MMs) are a powerful tool to help us understand and predict the dynamics of tumour growth under various conditions.
Stochastic failure of cell infection post viral entry: Implications for infection outcomes and antiviral therapy
We show that infections wherein virus is release by an infected cell as a single burst, rather than at a constant rate over the cell's infectious lifespan, has the same probability of infection extinction, despite previous claims to this effect [Pearson 2011, doi:10. 1371/journal. pcbi. 1001058].
Quantifying the relative contribution of free virus and cell-to-cell transmission routes to the propagation of hepatitis C virus infections in vitro using an agent-based model
Experiments have shown that hepatitis C virus (HCV) infections in vitro disseminate both distally via the release and diffusion of cell-free virus through the medium, and locally via direct, cell-to-cell transmission.
A mathematical model describing the localization and spread of influenza A virus infection within the human respiratory tract
The MM herein represents the HRT as a one-dimensional track extending from the nose down to a depth of 30 cm, wherein stationary cells interact with the concentration of IAV which move along within the PCF.
