ArticleF1000Research2021
Bioimage analysis workflows: community resources to navigate through a complex ecosystem.
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.
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Who cites it
14 citing papers in PubMed.
- AutoMorphoTrack: A modular framework for quantitative analysis of organelle morphology, motility, and interactions at single-cell resolution.bioRxiv : the preprint server for biology · 2026Article
- From cells to pixels: A decision tree for designing bioimage analysis pipelines.Journal of microscopy · 2025Article
- Perspectives on label-free microscopy of heterogeneous and dynamic biological systems.Journal of biomedical optics · 2025Article
- High-content screening (HCS) workflows for FAIR image data management with OMERO.Scientific reports · 2025Article
- Bridging imaging users to imaging analysis - A community survey.Journal of microscopy · 2024Article
- CellProfiler plugins - An easy image analysis platform integration for containers and Python tools.Journal of microscopy · 2024Article
- Recent Advances in Bioimage Analysis Methods for Detecting Skeletal Deformities in Biomedical and Aquaculture Fish Species.Biomolecules · 2023Review
- Partnering with health sciences libraries to address challenges in bioimaging data management and sharing.Histochemistry and cell biology · 2023Article
- Building a FAIR image data ecosystem for microscopy communities.Histochemistry and cell biology · 2023Review
- CellProfiler plugins -- an easy image analysis platform integration for containers and Python tools.ArXiv · 2023Article
- Bioimage informatics: Investing in software usability is essential.PLoS biology · 2023Article
- Bridging Imaging Users to Imaging Analysis - A community survey.bioRxiv : the preprint server for biology · 2023Article
- A biologist's guide to planning and performing quantitative bioimaging experiments.PLoS biology · 2023Article
- Cloud-enabled Biodepot workflow builder integrates image processing using Fiji with reproducible data analysis using Jupyter notebooks.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
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.