A minimal model of T cell avidity may identify subtherapeutic vaccine schedules
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Publication:2240254
DOI10.1016/j.mbs.2021.108556zbMath1475.92084OpenAlexW3112376456MaRDI QIDQ2240254
Danya Rose, Peter P. Lee, Adarsh Kumbhari, Peter S. Kim
Publication date: 8 November 2021
Published in: Mathematical Biosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1101/2020.12.06.413864
Uses Software
Cites Work
- Alternative to Ritt's pseudodivision for finding the input-output equations of multi-output models
- Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations
- Identification of parametric models from experimental data. Transl. from an upd. French version by the authors, with the help of John Norton
- Quantifying T lymphocyte turnover
- On immunotherapies and cancer vaccination protocols: a mathematical modelling approach
- Developing a minimally structured mathematical model of cancer treatment with oncolytic viruses and dendritic cell injections
- A mathematical model of the enhancement of tumor vaccine efficacy by immunotherapy
- Periodically pulsed immunotherapy in a mathematical model of tumor, CD4\(^+\) T cells, and antitumor cytokine interactions
- The union between structural and practical identifiability makes strength in reducing oncological model complexity: a case study
- Mathematical modelling of cancer stem cell-targeted immunotherapy
- Optimisation of anti-cancer peptide vaccines to preferentially elicit high-avidity T cells
- An algorithm for finding globally identifiable parameter combinations of nonlinear ODE models using Gröbner bases
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