PatternsBioinformaticsPeer-reviewed journal article
BIAFLOWS: A collaborative framework to reproducibly deploy and benchmark bioimage analysis workflows
Ulysse RubensiD, Romain MormontiD, Lassi PaavolaineniD, Volker Baecker, Benjamin PavieiD, Leandro A. ScholziD, Gino Michiels, Martin MaškaiD, Devrim ÜnayiD, Graeme BalliD, Renaud Hoyoux, Rémy VandaeleiD, Ofra GolaniiD, Stefan G. StanciuiD, Nataša SladojeiD, Perrine Paul‐GilloteauxiD, Raphaël MaréeiD, Sébastien TosiiD
Abstract
Automated image analysis has become key to extract quantitative information from scientific microscopy bioimages, but the methods involved are now often so refined that they can no longer be unambiguously described using written protocols. We introduce BIAFLOWS, a software tool with web services and a user interface specifically designed to document, interface, reproducibly deploy, and benchmark image analysis workflows. BIAFLOWS allows image analysis workflows to be compared fairly and shared in a reproducible manner, safeguarding research results and promoting the highest quality standards in bioimage analysis. A curated instance of BIAFLOWS is available online; it is currently populated with 34 workflows that can be triggered to process image datasets illustrating 15 common bioimage analysis problems organized in 9 major classes. As a complete case study, the open benchmarking of 7 nuclei segmentation workflows, including classical and deep learning techniques, was performed on this online instance. All the results presented can be reproduced online.
- assay: imaging
- research focus: benchmarking
- research focus: software / tool
- approach: experimental assay
- Citations
- 36
- FWCI
- 2.98
- Field percentile
- top 8%
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