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Found 5 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.
Quantification of Ebola virus replication kinetics in vitro
Mathematical modelling has successfully been used to provide quantitative descriptions of many viral infections, but for the Ebola virus, which requires biosafety level 4 facilities for experimentation, modelling can play a crucial role.
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.
