Inferring average generation via division-linked labeling View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-08

AUTHORS

Tom S. Weber, Leïla Perié, Ken R. Duffy

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. More... »

PAGES

491-523

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00285-015-0963-3

    DOI

    http://dx.doi.org/10.1007/s00285-015-0963-3

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1011672257

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26733310


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