Evidence map›Paper›PMID 32441778›Full record

ReviewFEBS letters2020

The palette of techniques for cell cycle analysis.

Anna E Eastman, Shangqin Guo

Open access · hybridAbstract readReview
In one paragraph

Review in FEBS letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

19 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
  2. Mitigating Cell Cycle Effects in Multi-Omics Data: Solutions and Analytical Frameworks.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Conserved physical mechanisms of cell and tissue elongation.Development (Cambridge, England) · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Basic Methods of Cell Cycle Analysis.International journal of molecular sciences · 2023
    Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
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

2 authors at 1 institution in 1 country.

Anna E EastmanDepartment of Cell Biology and Yale Stem Cell Center, Yale University, New Haven, CT, USA.ORCID https://orcid.org/0000-0002-1455-291X
Shangqin GuoDepartment of Cell Biology and Yale Stem Cell Center, Yale University, New Haven, CT, USA.ORCID https://orcid.org/0000-0003-1157-0423
Yale Cancer Center · US

Funding

Yale Cooperative Hematology Specialized Core CenterU54DK106857 · NIDDK · YALE UNIVERSITY · PI JOHN HWA, Diane S Krause · 2015 to 2026
$9.7M
Molecular definition of cancer cell-of-originDP2GM123507 · NIGMS · YALE UNIVERSITY · PI GUO, SHANGQIN · 2016 to 2016
$2.5M
NIDDK NIH HHS U54 DK106857NIGMS NIH HHS DP2 GM123507NIH Office of the Director DP2GM123507NIH Office of the Director U54DK106857
6 · The paper itself

Abstract

The cell division cycle is the generational period of cellular growth and propagation. Cell cycle progression needs to be highly regulated to preserve genomic fidelity while increasing cell number. In multicellular organisms, the cell cycle must also coordinate with cell fate specification during development and tissue homeostasis. Altered cell cycle dynamics play a central role also in a number of pathophysiological processes. Thus, extensive effort has been made to define the biochemical machineries that execute the cell cycle and their regulation, as well as implementing more sensitive and accurate cell cycle measurements. Here, we review the available techniques for cell cycle analysis, revisiting the assumptions behind conventional population-based measurements and discussing new tools to better address cell cycle heterogeneity in the single-cell era. We weigh the strengths, weaknesses, and trade-offs of methods designed to measure temporal aspects of the cell cycle. Finally, we discuss emerging techniques for capturing cell cycle speed at single-cell resolution in live animals.

Indexed as

cell cycle phasescell cycle speedheterogeneity

Identifiers

PMID32441778
PMCPMC9261528
OpenAlexW3027995577

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.