A branching process model for flow cytometry and budding index measurements in cell synchrony experiments.

dc.contributor.author

Orlando, David A

dc.contributor.author

Iversen, Edwin S

dc.contributor.author

Hartemink, Alexander J

dc.contributor.author

Haase, Steven B

dc.coverage.spatial

United States

dc.date.accessioned

2016-12-12T20:06:04Z

dc.date.issued

2009

dc.description.abstract

We present a flexible branching process model for cell population dynamics in synchrony/time-series experiments used to study important cellular processes. Its formulation is constructive, based on an accounting of the unique cohorts in the population as they arise and evolve over time, allowing it to be written in closed form. The model can attribute effects to subsets of the population, providing flexibility not available using the models historically applied to these populations. It provides a tool for in silico synchronization of the population and can be used to deconvolve population-level experimental measurements, such as temporal expression profiles. It also allows for the direct comparison of assay measurements made from multiple experiments. The model can be fit either to budding index or DNA content measurements, or both, and is easily adaptable to new forms of data. The ability to use DNA content data makes the model applicable to almost any organism. We describe the model and illustrate its utility and flexibility in a study of cell cycle progression in the yeast Saccharomyces cerevisiae.

dc.identifier

http://www.ncbi.nlm.nih.gov/pubmed/21853014

dc.identifier.issn

1932-6157

dc.identifier.uri

https://hdl.handle.net/10161/13267

dc.language

eng

dc.publisher

Institute of Mathematical Statistics

dc.relation.ispartof

Ann Appl Stat

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10.1214/09-AOAS264

dc.title

A branching process model for flow cytometry and budding index measurements in cell synchrony experiments.

dc.type

Journal article

duke.contributor.orcid

Hartemink, Alexander J|0000-0002-1292-2606

duke.contributor.orcid

Haase, Steven B|0000-0001-8127-8992

pubs.author-url

http://www.ncbi.nlm.nih.gov/pubmed/21853014

pubs.begin-page

1521

pubs.end-page

1541

pubs.issue

4

pubs.organisational-group

Biology

pubs.organisational-group

Computer Science

pubs.organisational-group

Duke

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Duke Cancer Institute

pubs.organisational-group

Institutes and Centers

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School of Medicine

pubs.organisational-group

Statistical Science

pubs.organisational-group

Trinity College of Arts & Sciences

pubs.publication-status

Published

pubs.volume

3

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