Evidence map›Paper›PMID 34136134›Full record

ArticleF1000Research2021

Bioimage analysis workflows: community resources to navigate through a complex ecosystem.

Perrine Paul-Gilloteaux, Sébastien Tosi, Jean-Karim Hériché, Alban Gaignard, Hervé Ménager, Raphaël Marée, Volker Baecker, Anna Klemm, Matúš Kalaš, Chong Zhang and 2 more

Abstract read
In one paragraph

Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Bridging Imaging Users to Imaging Analysis - A community survey.bioRxiv : the preprint server for biology · 2023
    Article
  13. Article
  14. 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

12 authors.

Perrine Paul-GilloteauxUniversité de Nantes, CNRS, INSERM, l'institut du thorax, Nantes, F-44000, France.ORCID 0000-0002-4822-165X
Sébastien TosiInstitute for Research in Biomedicine, IRB Barcelona, Barcelona Institute of Science and Technology, BIST, Barcelona, Spain.ORCID 0000-0001-8348-2778
Jean-Karim HérichéCell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, 69117, Germany.
Alban GaignardUniversité de Nantes, CNRS, INSERM, l'institut du thorax, Nantes, F-44000, France.
Hervé MénagerHub de Bioinformatique et Biostatistique, Département Biologie Computationnelle, Institut Pasteur, USR 3756, CNRS, Paris, 75015, France.
Raphaël MaréeMontefiore Institute, University of Liège, Liège, Belgium.
Volker BaeckerMontpellier Ressources Imagerie, BioCampus Montpellier, CNRS, INSERM, University of Montpellier, Montpellier, F-34000, France.ORCID 0000-0002-9129-6403
Anna KlemmBioImage Informatics Facility, SciLifeLab, Stockholm, Sweden.ORCID 0000-0002-3466-1320
Matúš KalašComputational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.ORCID 0000-0002-1509-4981
Chong ZhangDepartment of Information and Communication Technologies, University Pompeu Fabra, Barcelona, Spain.
Kota MiuraNikon Imaging Center, University of Heidelberg, Heidelberg, Germany.
Julien ColombelliInstitute for Research in Biomedicine, IRB Barcelona, Barcelona Institute of Science and Technology, BIST, Barcelona, Spain.ORCID 0000-0002-2784-4276

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Workflows are the keystone of bioimage analysis, and the NEUBIAS (Network of European BioImage AnalystS) community is trying to gather the actors of this field and organize the information around them.  One of its most recent outputs is the opening of the F1000Research NEUBIAS gateway, whose main objective is to offer a channel of publication for bioimage analysis workflows and associated resources. In this paper we want to express some personal opinions and recommendations related to finding, handling and developing bioimage analysis workflows.  The emergence of "big data" in bioimaging and resource-intensive analysis algorithms make local data storage and computing solutions a limiting factor. At the same time, the need for data sharing with collaborators and a general shift towards remote work, have created new challenges and avenues for the execution and sharing of bioimage analysis workflows. These challenges are to reproducibly run workflows in remote environments, in particular when their components come from different software packages, but also to document them and link their parameters and results by following the FAIR principles (Findable, Accessible, Interoperable, Reusable) to foster open and reproducible science. In this opinion paper, we focus on giving some directions to the reader to tackle these challenges and navigate through this complex ecosystem, in order to find and use workflows, and to compare workflows addressing the same problem. We also discuss tools to run workflows in the cloud and on High Performance Computing resources, and suggest ways to make these workflows FAIR.

Indexed as

Computational BiologyEcosystemAlgorithmsInformation Storage and RetrievalWorkflowBioimage analysiscollectionscomponentsFAIR principlesknowledge databaseNEUBIASremote computingscientific workflow management systemsworkflows

Identifiers

PMID34136134
PMCPMC8182692

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.