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dc.contributor.authorPaul-Gilloteaux, Perrine
dc.contributor.authorTosi, Sébastien
dc.contributor.authorHériche, Jean-Karim
dc.contributor.authorGaignard, Alban
dc.contributor.authorMénager, Hervé
dc.contributor.authorMarée, Raphaël
dc.contributor.authorBaecker, Volker
dc.contributor.authorKlemm, Anna
dc.contributor.authorKalaš, Matúš
dc.contributor.authorZhang, Chong
dc.contributor.authorMiura, Kota
dc.contributor.authorColombelli, Julien
dc.date.accessioned2022-03-18T08:47:43Z
dc.date.available2022-03-18T08:47:43Z
dc.date.created2022-01-18T01:54:51Z
dc.date.issued2021
dc.identifier.issn2046-1402
dc.identifier.urihttps://hdl.handle.net/11250/2986050
dc.description.abstractWorkflows 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.en_US
dc.language.isoengen_US
dc.publisherF1000en_US
dc.relation.urihttps://doi.org/10.12688/f1000research.52569.1
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleBioimage analysis workflows: community resources to navigate through a complex ecosystem [version 1; peer review: 2 approved]en_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2021 The Author(s)en_US
dc.source.articlenumber320en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.12688/f1000research.52569.1
dc.identifier.cristin1983084
dc.source.journalF1000 Researchen_US
dc.identifier.citationF1000 Research. 2021, 10, 320.en_US
dc.source.volume10en_US


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal