Evidence map›Paper›PMID 22977731›Full record

ArticleScientific reports2012

The cell cycle switch computes approximate majority.

Luca Cardelli, Attila Csikász-Nagy

Abstract read
In one paragraph

Article in Scientific reports, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Distributed algorithms from arboreal ants for the shortest path problem.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Communication cost of consensus for nodes with limited memory.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Modelling the spread of innovation in wild birds.Journal of the Royal Society, Interface · 2017
    Article
  18. Efficient Switches in Biology and Computer Science.PLoS computational biology · 2017
    Article
  19. Article
  20. 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

2 authors.

Luca CardelliMicrosoft Research, 7 J J Thomson Ave, Cambridge CB3 0FB, UK. luca@microsoft.com
Attila Csikász-Nagy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Both computational and biological systems have to make decisions about switching from one state to another. The 'Approximate Majority' computational algorithm provides the asymptotically fastest way to reach a common decision by all members of a population between two possible outcomes, where the decision approximately matches the initial relative majority. The network that regulates the mitotic entry of the cell-cycle in eukaryotes also makes a decision before it induces early mitotic processes. Here we show that the switch from inactive to active forms of the mitosis promoting Cyclin Dependent Kinases is driven by a system that is related to both the structure and the dynamics of the Approximate Majority computation. We investigate the behavior of these two switches by deterministic, stochastic and probabilistic methods and show that the steady states and temporal dynamics of the two systems are similar and they are exchangeable as components of oscillatory networks.

Indexed as

Cell Cycle CheckpointsComputer SimulationModels, BiologicalAnimalsHumansMarkov ChainsMitosisModels, StatisticalSignal TransductionStochastic Processes

Identifiers

PMID22977731
PMCPMC3440625

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

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.