Determining the expected variability of immune responses using the cyton model

DOI10.1007/s00285-007-0142-2zbMath1206.92013OpenAlexW2115558707WikidataQ51901751 ScholiaQ51901751MaRDI QIDQ938174

Marian L. Turner, Vijay G. Subramanian, Philip D. Hodgkin, Ken R. Duffy

Publication date: 18 August 2008

Published in: Journal of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: http://eprints.maynoothuniversity.ie/1645/1/Hamiltoncyton_model_analysis.pdf

zbMATH Keywords

continuous time branching processesexpected variabilitytime dependent offspring distributions

Mathematics Subject Classification ID

Applications of branching processes (60J85) Medical applications (general) (92C50) Cell biology (92C37)

Related Items (8)

Inferring average generation via division-linked labeling ⋮ Deterministic and stochastic naive T cell population dynamics: symmetric and asymmetric cell division ⋮ On the impact of correlation between collaterally consanguineous cells on lymphocyte population dynamics ⋮ A mathematical model for a T cell fate decision algorithm during immune response ⋮ The effect of correlations on the population dynamics of lymphocytes ⋮ A novel statistical analysis and interpretation of flow cytometry data ⋮ Quantifying T lymphocyte turnover ⋮ Sample path properties of the average generation of a Bellman-Harris process

Cites Work

• The Fourier-series method for inverting transforms of probability distributions
• Numerical inversion of probability generating functions
• Multidimensional transform inversion with applications to the transient \(M/G/1\) queue
• Estimating division and death rates from CFSE data
• Branching processes in biology
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