Evidence map›Paper›PMID 28954851›Full record

ArticleJournal of the Royal Society, Interface2017

Bioelectric gene and reaction networks: computational modelling of genetic, biochemical and bioelectrical dynamics in pattern regulation.

Alexis Pietak, Michael Levin

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Cancer: A bioelectric disease?Clinical and translational medicine · 2026
    Review
  2. Article
  3. Article
  4. Article
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  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Review
  19. Beyond Neurons: Long Distance Communication in Development and Cancer.Frontiers in cell and developmental biology · 2021
    Review
  20. Rewiring Endogenous Bioelectric Circuits in the Xenopus laevis Embryo Model.Methods in molecular biology (Clifton, N.J.) · 2021
    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.

Alexis PietakAllen Discovery Center, Tufts University, Medford, MA, USA.
Michael LevinAllen Discovery Center, Tufts University, Medford, MA, USA michael.levin@tufts.edu.ORCID 0000-0001-7292-8084

Funding

Electrotherapeutic strategies for connective tissue repairR01AR061988 · NIAMS · TUFTS UNIVERSITY MEDFORD · PI HUNG, CLARK T., KAPLAN, DAVID L. · 2011 to 2015
$3.3M
Tissue Regeneration by Biophysical SignalingR01AR055993 · NIAMS · TUFTS UNIVERSITY MEDFORD · PI KAPLAN, DAVID L., LEVIN, MICHAEL · 2010 to 2018
$3.2M
Induction of limb development in XenopusR03HD081401 · NICHD · TUFTS UNIVERSITY MEDFORD · PI LEVIN, MICHAEL · 2014 to 2015
$154k
NIAMS NIH HHS R01 AR055993NIAMS NIH HHS R01 AR061988NICHD NIH HHS R03 HD081401
6 · The paper itself

Abstract

Gene regulatory networks (GRNs) describe interactions between gene products and transcription factors that control gene expression. In combination with reaction-diffusion models, GRNs have enhanced comprehension of biological pattern formation. However, although it is well known that biological systems exploit an interplay of genetic and physical mechanisms, instructive factors such as transmembrane potential (

Indexed as

Computer SimulationElectrophysiological PhenomenaModels, BiologicalAnimalsGene Regulatory NetworksHumansbioelectricitygene regulatory networksin silico simulationsregeneration

Identifiers

PMID28954851
PMCPMC5636277

What OpenQuestion holds

Textmetadata
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.