TY - JOUR T1 - BIAFLOWS: A collaborative framework to reproducibly deploy and benchmark bioimage analysis workflows JF - bioRxiv DO - 10.1101/707489 SP - 707489 AU - Ulysse Rubens AU - Romain Mormont AU - Lassi Paavolainen AU - Volker Bäcker AU - Gino Michiels AU - Benjamin Pavie AU - Leandro A. Scholz AU - Martin Maška AU - Devrim Ünay AU - Graeme Ball AU - Renaud Hoyoux AU - Rémy Vandaele AU - Ofra Golani AU - Anatole Chessel AU - Stefan G. Stanciu AU - Natasa Sladoje AU - Perrine Paul-Gilloteaux AU - Raphaël Marée AU - Sébastien Tosi Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/02/06/707489.abstract N2 - 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. ER -