Merge pull request #3093 from galaxyproject/article-bmz

Create new article Galaxy <-> BMZ

Author: bgruening

content/news/2025-04-23-bmz-galaxy/BMZ-Galaxy.png

@@ -0,0 +1,35 @@
+---
+title: 'The BioImage Model Zoo meets the Galaxy platform'
+date: "2025-04-23"
+tease: "New tool to run AI models for image analysis"
+tags:
+- nfdi4bioimage
+- imaging
+subsites: [all-eu,all,global]
+main_subsite: eu
+---
+
+A new Galaxy integration enables researchers to access AI models from the [BioImage Model Zoo (BioImage.IO)](https://bioimage.io/#/).
+This integration bridges open-source AI models and an accessible, workflow-based computational environment, allowing scientists across disciplines to include deep learning
+models in their workflows.
+This integration is a leap forward for the AI4Life project, which aims to democratize AI in life sciences. “We’re broadening our focus to engage a wider community of
+users by expanding the reach of the BioImage.IO Model Zoo,” explains Diana Chiang Jurado, who, together with Leonid Kostrykin, developed a dedicated tutorial to support users.
+“Using the Galaxy infrastructure, we’re not only lowering technical barriers but also making sure that researchers with no access to local computational resources can still run their analyses.”
+
+Galaxy's established ecosystem brings some benefits: cloud-based computing, reproducibility through workflow provenance, and a collaborative environment thousands of scientists use worldwide.
+
+Integrating these models wasn’t without its challenges. “The BioImage Model Zoo hosts models built on different architectures and frameworks,” notes Anup Kumar,
+the leading developer behind the integration. “One of the most exciting outcomes,” Anup adds, “is the accessibility it provides. Scientists who don’t have a background
+in AI, or who work at underfunded institutions, can now use powerful models with just a few clicks. That’s the kind of impact we’re aiming for.”
+
+With AI-driven image analysis becoming increasingly relevant across scientific fields, from biology to earth sciences or astronomy, the integration sets the stage
+for new cross-disciplinary collaborations like those outlined in the [OSCARS-FIESTA project](https://www.oscars-project.eu/projects/fair-image-analysis-across-sciences).
+“Workflows created in Galaxy are easy to share and adapt,” says Leonid. “That means a model trained on biological data could inspire solutions in climate science or vice versa. It’s about breaking down silos.”
+
+By combining rich model repositories with user-friendly, FAIR workflows, this integration makes advanced image analysis more approachable, adaptable, and impactful for scientists everywhere.
+
+Try the tutorial developed by Diana and Leonid here: [Using BioImage.IO models for image analysis in Galaxy](https://training.galaxyproject.org/training-material/topics/imaging/tutorials/process-image-bioimageio/tutorial.html).
+
+<div class="img-sizer" style="width: 128px">
+![Galaxy tool to run BMZ models](./BMZ-Galaxy.png)]
+</div>