Evidence map›Paper›PMID 34743598›Full record

ReviewPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2021

Turing pattern design principles and their robustness.

Sean T Vittadello, Thomas Leyshon, David Schnoerr, Michael P H Stumpf

Abstract readReview
In one paragraph

Review in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Revisiting Turing's Chemical Basis of Morphogenesis.Bulletin of mathematical biology · 2026
    Review
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  9. Interactions between neural representations of the social and spatial environment.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  10. Article
  11. Minimal reaction schemes for pattern formation.Journal of the Royal Society, Interface · 2024
    Article
  12. Article
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  14. Article
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  16. Physical interactions in non-ideal fluids promote Turing patterns.Journal of the Royal Society, Interface · 2023
    Article
  17. Review
  18. Article
  19. Article
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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

4 authors.

Sean T VittadelloSchool of BioSciences, University of Melbourne, Melbourne, Victoria 3010, Australia.ORCID 0000-0002-4476-6732
Thomas LeyshonDepartment of Life Sciences, Imperial College London, London, UK.
David SchnoerrDepartment of Life Sciences, Imperial College London, London, UK.
Michael P H StumpfSchool of BioSciences, University of Melbourne, Melbourne, Victoria 3010, Australia.ORCID 0000-0002-3577-1222

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Turing patterns have morphed from mathematical curiosities into highly desirable targets for synthetic biology. For a long time, their biological significance was sometimes disputed but there is now ample evidence for their involvement in processes ranging from skin pigmentation to digit and limb formation. While their role in developmental biology is now firmly established, their synthetic design has so far proved challenging. Here, we review recent large-scale mathematical analyses that have attempted to narrow down potential design principles. We consider different aspects of robustness of these models and outline why this perspective will be helpful in the search for synthetic Turing-patterning systems. We conclude by considering robustness in the context of developmental modelling more generally. This article is part of the theme issue 'Recent progress and open frontiers in Turing's theory of morphogenesis'.

Indexed as

Models, BiologicalSynthetic BiologyMorphogenesisdesign principlespattern formationpositional information

Identifiers

PMID34743598
PMCPMC8580431

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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.