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Reconstruction of cell population dynamics using CFSE
BACKGROUND: Quantifying cell division and death is central to many studies in the biological sciences. The fluorescent dye CFSE allows the tracking of cell division in vitro and in vivo and provides a rich source of information with which to test models of cell kinetics. Cell division and death have...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1929124/ https://www.ncbi.nlm.nih.gov/pubmed/17565685 http://dx.doi.org/10.1186/1471-2105-8-196 |
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author | Yates, Andrew Chan, Cliburn Strid, Jessica Moon, Simon Callard, Robin George, Andrew JT Stark, Jaroslav |
author_facet | Yates, Andrew Chan, Cliburn Strid, Jessica Moon, Simon Callard, Robin George, Andrew JT Stark, Jaroslav |
author_sort | Yates, Andrew |
collection | PubMed |
description | BACKGROUND: Quantifying cell division and death is central to many studies in the biological sciences. The fluorescent dye CFSE allows the tracking of cell division in vitro and in vivo and provides a rich source of information with which to test models of cell kinetics. Cell division and death have a stochastic component at the single-cell level, and the probabilities of these occurring in any given time interval may also undergo systematic variation at a population level. This gives rise to heterogeneity in proliferating cell populations. Branching processes provide a natural means of describing this behaviour. RESULTS: We present a likelihood-based method for estimating the parameters of branching process models of cell kinetics using CFSE-labeling experiments, and demonstrate its validity using synthetic and experimental datasets. Performing inference and model comparison with real CFSE data presents some statistical problems and we suggest methods of dealing with them. CONCLUSION: The approach we describe here can be used to recover the (potentially variable) division and death rates of any cell population for which division tracking information is available. |
format | Text |
id | pubmed-1929124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-19291242007-07-21 Reconstruction of cell population dynamics using CFSE Yates, Andrew Chan, Cliburn Strid, Jessica Moon, Simon Callard, Robin George, Andrew JT Stark, Jaroslav BMC Bioinformatics Research Article BACKGROUND: Quantifying cell division and death is central to many studies in the biological sciences. The fluorescent dye CFSE allows the tracking of cell division in vitro and in vivo and provides a rich source of information with which to test models of cell kinetics. Cell division and death have a stochastic component at the single-cell level, and the probabilities of these occurring in any given time interval may also undergo systematic variation at a population level. This gives rise to heterogeneity in proliferating cell populations. Branching processes provide a natural means of describing this behaviour. RESULTS: We present a likelihood-based method for estimating the parameters of branching process models of cell kinetics using CFSE-labeling experiments, and demonstrate its validity using synthetic and experimental datasets. Performing inference and model comparison with real CFSE data presents some statistical problems and we suggest methods of dealing with them. CONCLUSION: The approach we describe here can be used to recover the (potentially variable) division and death rates of any cell population for which division tracking information is available. BioMed Central 2007-06-12 /pmc/articles/PMC1929124/ /pubmed/17565685 http://dx.doi.org/10.1186/1471-2105-8-196 Text en Copyright © 2007 Yates et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Yates, Andrew Chan, Cliburn Strid, Jessica Moon, Simon Callard, Robin George, Andrew JT Stark, Jaroslav Reconstruction of cell population dynamics using CFSE |
title | Reconstruction of cell population dynamics using CFSE |
title_full | Reconstruction of cell population dynamics using CFSE |
title_fullStr | Reconstruction of cell population dynamics using CFSE |
title_full_unstemmed | Reconstruction of cell population dynamics using CFSE |
title_short | Reconstruction of cell population dynamics using CFSE |
title_sort | reconstruction of cell population dynamics using cfse |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1929124/ https://www.ncbi.nlm.nih.gov/pubmed/17565685 http://dx.doi.org/10.1186/1471-2105-8-196 |
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