Evidence map›Paper›PMID 33748708›Full record

ArticleiScience2021

Cell size distribution of lineage data: analytic results and parameter inference.

Chen Jia, Abhyudai Singh, Ramon Grima

Abstract read
In one paragraph

Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. A GeneralizedbioRxiv : the preprint server for biology · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Metabolic regulation of endothelial senescence.Frontiers in cardiovascular medicine · 2023
    Review
  13. Article
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Chen JiaApplied and Computational Mathematics Division, Beijing Computational Science Research Center, Beijing 100193, China.
Abhyudai SinghDepartment of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA.
Ramon GrimaSchool of Biological Sciences, University of Edinburgh, EH9 3JH, UK.

Funding

Stochastic hybrid systems approach to uncovering cell-size control mechanisms R01GM126557 · NIGMS · UNIVERSITY OF DELAWARE · PI SINGH, ABHYUDAI · 2017 to 2019
$675k
NIGMS NIH HHS R01 GM126557
6 · The paper itself

Abstract

Recent advances in single-cell technologies have enabled time-resolved measurements of the cell size over several cell cycles. These data encode information on how cells correct size aberrations so that they do not grow abnormally large or small. Here, we formulate a piecewise deterministic Markov model describing the evolution of the cell size over many generations, for all three cell size homeostasis strategies (timer, sizer, and adder). The model is solved to obtain an analytical expression for the non-Gaussian cell size distribution in a cell lineage; the theory is used to understand how the shape of the distribution is influenced by the parameters controlling the dynamics of the cell cycle and by the choice of cell tracking protocol. The theoretical cell size distribution is found to provide an excellent match to the experimental cell size distribution of

Indexed as

Cell BiologyIn Silico BiologySystems Biology

Identifiers

PMID33748708
PMCPMC7961097

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.