Evidence map›Paper›PMID 25181461›Full record

ArticlePloS one2014

esyN: network building, sharing and publishing.

Daniel M Bean, Joshua Heimbach, Lorenzo Ficorella, Gos Micklem, Stephen G Oliver, Giorgio Favrin

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Naturally Occurring Variability in the Regulatory Region of theInternational journal of molecular sciences · 2026
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  13. Using FlyBase: A Database of Drosophila Genes and Genetics.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  14. Article
  15. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Daniel M BeanCambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom; Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.
Joshua HeimbachCambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom.
Lorenzo FicorellaCambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom; Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom; Dipartimento di Biochimica, Universita' degli studi di Pisa, Pisa, Italy.
Gos MicklemCambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom; Department of Genetics, University of Cambridge, Cambridge, United Kingdom.
Stephen G OliverCambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom; Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.
Giorgio FavrinCambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom; Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.

Funding

Medical Research Council MC_G1000734Wellcome Trust
6 · The paper itself

Abstract

The construction and analysis of networks is increasingly widespread in biological research. We have developed esyN ("easy networks") as a free and open source tool to facilitate the exchange of biological network models between researchers. esyN acts as a searchable database of user-created networks from any field. We have developed a simple companion web tool that enables users to view and edit networks using data from publicly available databases. Both normal interaction networks (graphs) and Petri nets can be created. In addition to its basic tools, esyN contains a number of logical templates that can be used to create models more easily. The ability to use previously published models as building blocks makes esyN a powerful tool for the construction of models and network graphs. Users are able to save their own projects online and share them either publicly or with a list of collaborators. The latter can be given the ability to edit the network themselves, allowing online collaboration on network construction. esyN is designed to facilitate unrestricted exchange of this increasingly important type of biological information. Ultimately, the aim of esyN is to bring the advantages of Open Source software development to the construction of biological networks.

Indexed as

Gene Regulatory NetworksInformation DisseminationPublishingSignal TransductionSoftwareProtein KinasesSubstrate SpecificityProtein Kinases

Identifiers

PMID25181461
PMCPMC4152123

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.