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Bioimage analysis workflows: community resources to navigate through a complex ecosystem.
Paul-Gilloteaux, Perrine; Tosi, Sébastien; Hériché, Jean-Karim; Gaignard, Alban; Ménager, Hervé; Marée, Raphaël; Baecker, Volker; Klemm, Anna; Kalas, Matús; Zhang, Chong; Miura, Kota; Colombelli, Julien.
Afiliação
  • Paul-Gilloteaux P; Université de Nantes, CNRS, INSERM, l'institut du thorax, Nantes, F-44000, France.
  • Tosi S; Université de Nantes, CHU Nantes, Inserm, CNRS, SFR Santé, Inserm UMS 016, CNRS UMS 3556, Nantes, F-44000, France.
  • Hériché JK; Institute for Research in Biomedicine, IRB Barcelona, Barcelona Institute of Science and Technology, BIST, Barcelona, Spain.
  • Gaignard A; Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, 69117, Germany.
  • Ménager H; Université de Nantes, CNRS, INSERM, l'institut du thorax, Nantes, F-44000, France.
  • Marée R; Hub de Bioinformatique et Biostatistique, Département Biologie Computationnelle, Institut Pasteur, USR 3756, CNRS, Paris, 75015, France.
  • Baecker V; CNRS, UMS 3601, Institut Français de Bioinformatique, IFB-core, Evry, 91000, France.
  • Klemm A; Montefiore Institute, University of Liège, Liège, Belgium.
  • Kalas M; Montpellier Ressources Imagerie, BioCampus Montpellier, CNRS, INSERM, University of Montpellier, Montpellier, F-34000, France.
  • Zhang C; BioImage Informatics Facility, SciLifeLab, Stockholm, Sweden.
  • Miura K; Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.
  • Colombelli J; Department of Information and Communication Technologies, University Pompeu Fabra, Barcelona, Spain.
F1000Res ; 10: 320, 2021.
Article em En | MEDLINE | ID: mdl-34136134
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article