Literature DB >> 26733310

Inferring average generation via division-linked labeling.

Tom S Weber1, Leïla Perié2,3,4, Ken R Duffy5.   

Abstract

For proliferating cells subject to both division and death, how can one estimate the average generation number of the living population without continuous observation or a division-diluting dye? In this paper we provide a method for cell systems such that at each division there is an unlikely, heritable one-way label change that has no impact other than to serve as a distinguishing marker. If the probability of label change per cell generation can be determined and the proportion of labeled cells at a given time point can be measured, we establish that the average generation number of living cells can be estimated. Crucially, the estimator does not depend on knowledge of the statistics of cell cycle, death rates or total cell numbers. We explore the estimator's features through comparison with physiologically parameterized stochastic simulations and extrapolations from published data, using it to suggest new experimental designs.

Entities:  

Keywords:  Average generation inference; Branching processes; Stochastically decorated trees

Mesh:

Year:  2016        PMID: 26733310     DOI: 10.1007/s00285-015-0963-3

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  57 in total

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Review 7.  Cancer as an evolutionary and ecological process.

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9.  Evidence for a mitotic clock in human hematopoietic stem cells: loss of telomeric DNA with age.

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  2 in total

1.  Sample path properties of the average generation of a Bellman-Harris process.

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Journal:  J Math Biol       Date:  2019-05-08       Impact factor: 2.259

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Authors:  Kaspar Bresser; Lianne Kok; Arpit C Swain; Lisa A King; Laura Jacobs; Tom S Weber; Leïla Perié; Ken R Duffy; Rob J de Boer; Ferenc A Scheeren; Ton N Schumacher
Journal:  Nat Immunol       Date:  2022-04-07       Impact factor: 31.250

  2 in total

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