Evidence map›Paper›PMID 27137889›Full record

ArticleNucleic acids research2016

The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update.

Enis Afgan, Dannon Baker, Marius van den Beek, Daniel Blankenberg, Dave Bouvier, Martin Čech, John Chilton, Dave Clements, Nate Coraor, Carl Eberhard and 10 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,048 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,048citing papers in PubMed, 1 pooled it
–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

1,048 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. The metabolic trap:Journal of medical microbiology · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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  19. Divergence and conservation of satellite DNA in the loggerhead sea turtle (Caretta caretta): a comparative cytogenomic analysis.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2026
    Article
  20. Article

988 more citing papers are in PubMed but not listed here.

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

20 authors.

Enis AfganDepartment of Biology, Johns Hopkins University, Baltimore, MD USA.
Dannon BakerDepartment of Biology, Johns Hopkins University, Baltimore, MD USA.
Marius van den BeekInstitut de Biologie Paris-Seine, Université Pierre et Marie Curie, Paris, France.
Daniel BlankenbergDepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.
Dave BouvierDepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.
Martin ČechDepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.
John ChiltonDepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.
Dave ClementsDepartment of Biology, Johns Hopkins University, Baltimore, MD USA.
Nate CoraorDepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.
Carl EberhardDepartment of Biology, Johns Hopkins University, Baltimore, MD USA.
Björn GrüningDepartment of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany Center for Biological Systems Analysis (ZBSA), University of Freiburg, Freiburg, Germany.
Aysam GuerlerDepartment of Biology, Johns Hopkins University, Baltimore, MD USA.
Jennifer Hillman-JacksonDepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.
Greg Von KusterAcademic Computing Services, Penn State University, University Park, PA, USA.
Eric RascheDepartment of Biochemistry and Biophysics, Texas A&M University, College Station, TX, USA.
Nicola SoranzoThe Genome Analysis Centre, Norwich, United Kingdom.
Nitesh TuragaDepartment of Biology, Johns Hopkins University, Baltimore, MD USA.
James TaylorDepartment of Biology, Johns Hopkins University, Baltimore, MD USA james@taylorlab.org.
Anton NekrutenkoDepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA anton@nekrut.org.
Jeremy GoecksThe Computational Biology Institute, George Washington University, Washington DC, USA jgoecks@gwu.edu.

Funding

Democratization of Data Analysis in Life Sciences Through GalaxyU41HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI NEKRUTENKO, ANTON, SCHATZ, MICHAEL · 2012 to 2020
$14.4M
Dynamically scalable accessible analysis for next generation sequence dataRC2HG005542 · NHGRI · EMORY UNIVERSITY · PI NEKRUTENKO, ANTON, TAYLOR, JAMES PETER · 2009 to 2010
$1.5M
An Efficient Lightweight Environment for Biomedical ComputationR01HG004909 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI NEKRUTENKO, ANTON · 2009 to 2011
$1.3M
A Turnkey Solution for Next Generation Sequence Data AnalysisR21HG005133 · NHGRI · EMORY UNIVERSITY · PI TAYLOR, JAMES PETER · 2009 to 2010
$445k
NHGRI NIH HHS R01 HG004909NHGRI NIH HHS R21 HG005133NHGRI NIH HHS RC2 HG005542NHGRI NIH HHS U41 HG006620
6 · The paper itself

Abstract

High-throughput data production technologies, particularly 'next-generation' DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.

Indexed as

User-Computer InterfaceBiomedical ResearchComputational BiologyDatabases, GeneticDatasets as TopicHumansInternetReproducibility of Results

Identifiers

PMID27137889
PMCPMC4987906

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.