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Trends in Microbiology
Article . 2017 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Step by Step, Cell by Cell: Quantification of the Bacterial Cell Cycle

Authors: Osella, Matteo; Tans, Sander J.; Cosentino Lagomarsino, Marco;

Step by Step, Cell by Cell: Quantification of the Bacterial Cell Cycle

Abstract

The Escherichia coli cell cycle is a classic, but we are still missing some of its essential aspects. The reason is that our knowledge is mostly based on population data, and our grasp of the behavior of single cells is still very limited. Today, new dynamic single-cell data promise to overcome this barrier. Existing data from single cells have already led to findings and hypotheses that challenge standard views, and have raised new questions. Here, we review these recent developments and propose that a systematic exploration of the correlation patterns between 'cell-cycle intervals' defined by key molecular events measured in many single cells could lead to a quantitative characterization of the cell cycle in terms of inherent stochasticity and homeostatic controls.

Countries
Italy, France
Keywords

[SDV] Life Sciences [q-bio], DNA Replication, DNA, Bacterial, Escherichia coli, Cell Division, genetics, physiology; DNA Replication, genetics; DNA, Bacterial, genetics; Escherichia coli, genetics, growth & development, metabolism; Single-Cell Analysis, methods; E. coli; cell cycle; division homeostasis; key intervals; replication initiation; stochasticity, Single-Cell Analysis, Cell Division

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    51
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
51
Top 10%
Top 10%
Top 10%
Green
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