The Problems

1. Subdomain interfaces (Galaxy, Single-cell, etc.) were previously server-specific. This meant that if a server, such as galaxy.eu, had a genomics subdomain, there was no guarantee that same subdomain existed on other servers. Indeed, genomics community members would have to spin up their own version on a different server - from scratch! This included both content and tooling. How annoying for a Single-cell and sPatial Omics Community that works across continents!
2. These different servers made training extremely difficult, where user’s experiences wildly varied when trying to follow tutorials. This often led to confusion and frustration.
3. Subdomains had no template or consistent, user research informed experience - and became whatever a given individual or group might throw together. How annoying given how little time we all have, to have to collectively contribute and maintain so many sites!

The result? Work duplication, wildly different user experiences depending on the availability of subdomains on a given server and the time community contributors had to polish and maintain a site.

The Solution

After a world tour pointing out this massive waste of resources across the galaxy.* communities, the avengers assembled.

1. The Australians appeared, like a star in a dark sky, with a user research tested GalaxyLabs engine - enabling rapid spinning up of community pages.
2. The European members of the Single-cell and sPatial Omics Community, already experienced in unifying over duplicating subdomains threw their hat in to be the test lab, converting their content to a GalaxyLabs engine, but centralised such that every server could spin up the same instance
3. The USA sys admin, Nate Coraor, logged in from a train station to push GalaxyLab created sites onto their servers as proof of principle.

The Result

A single, centralised location for community content that enables consistent user experience across any server who chooses to host a given subdomain. GalaxyLabs was a hit!

The Benefit

Community curation and maintenance of these Galaxy interfaces takes time and effort - which is now spent on a single, high quality, user research informed and reusable global instance rather than multiple, variable sites across different teams.

You can read the whole story on how this many year mission went down. You can also enjoy the fruits of this labour, when accessing the myriad of GalaxyLabs across servers.

We are pleased to announce a new feature for the Galaxy Training Academy in 2026: a meet the experts daily video. Each day for the week of May 18, we will drop a new video from an expert in a field of interest of Galaxy users. Here are the experts we have lined up for this GTA:

Monday, May 18: Delphine Larivière

Delphine Larivière is a Research Assistant Professor at Penn State University and part of the Galaxy team, where she collaborates with researchers to develop advanced analysis pipelines and implement them in Galaxy. She also works with the Vertebrate Genome Project to help democratize high-quality reference genome assembly and contributes to the Galaxy Training Network as a trainer and mentor. Passionate about open and inclusive science, Delphine also helps develop training materials and workshops that make complex analyses more accessible to the research community. To learn more, you can find Delphine on GitHub (Delphine-L) and LinkedIn.

Tuesday, May 19: Aaron Quinlan

Aaron Quinlan is Professor and Chair of Human Genetics at the University of Utah and a leading figure in computational genomics. His lab is known for combining computational advances with genomics technologies to study the causes and consequences of genome mutation, reveal genetic variation, and understand the genetic basis of rare diseases. He is also well known for supporting open-source software for the genomics community, including tools such as BEDTools and Mosdepth, which have become foundational for analyzing genomic intervals and sequencing data at scale. To learn more, visit his lab’s website.

Wednesday, May 20: Stephanie Hicks

Stephanie Hicks is an Associate Professor of Biomedical Engineering and Biostatistics at Johns Hopkins University, where she develops statistical and computational methods for analyzing high-dimensional genomics data. She is an applied statistician working at the intersection of genomics and biomedical data science, and her work emphasizes single-cell and spatial transcriptomics, with a strong focus on rigor, reproducibility, and open science. Hicks is also widely recognized for her leadership in the Bioconductor community and her advocacy for best practices in data analysis, mentoring, and inclusive scientific training. To learn more, visit her lab’s website.

Thursday, May 21: Timothy Griffin

Timothy Griffin is Professor and Faculty Director of the Center for Metabolomics and Proteomics at the University of Minnesota, where his group develops and applies mass spectrometry-based tools to study proteins and proteomes. This work helps enable system-wide characterization of proteins across a wide range of biological samples to better understand biological function and disease. His group also contributes to Galaxy-P, or Galaxy for proteomics, which supports multi-omic analyses integrating genomic, proteomic, and metabolomic data to provide new insights into biological systems. Griffin’s research is highly interdisciplinary and collaborative, bringing together analytical chemistry, computer science, and biochemistry to address questions of biological and biomedical importance. To learn more about Tim and Galaxy-P, visit his lab website and Galaxy-P’s website.

Friday, May 22: Gareth Price

Gareth Price leads Galaxy Australia, where he provides strategic direction and helps ensure the platform meets the needs of researchers across the life sciences. With a background in bioinformatics and genomics, he supports researchers through training, outreach, and collaboration with the global Galaxy Project, helping connect user needs with ongoing platform development. His experience spans a wide range of genomic technologies, data analysis approaches, and organisms, giving him a broad perspective on how Galaxy can support diverse research communities. Gareth is passionate about making bioinformatics more accessible and useful for researchers through both infrastructure and education. To learn more about Gareth, visit Australian BioCommons.

What is BioNT?

BioNT is an international consortium of academic institutions and SMEs, co-funded by the EU Digital Europe programme (grant agreement 101100604), running from January 2023 to June 2026. Its mission is to build a high-quality training programme in digital skills for the biotechnology and biomedical sectors, particularly for learners with limited prior experience in biological data handling and computational tools.

The University of Freiburg’s Freiburg Galaxy Team is an active BioNT partner, contributing expertise in bioinformatics training and the Galaxy Training Network.

Human-curated translated Tutorials Now Available

One of BioNT’s core goals is to make training materials accessible to non-English-speaking communities. To that end, the BioNT team has produced careful, human-quality translations of key GTN tutorials into German (DE), Spanish (ES), and Italian (IT).

The following tutorials are now available in four languages:

In addition to the tutorials, the BioNT team has translated a comprehensive set of Galaxy FAQs into all three languages, covering common actions such as importing data, creating collections, renaming datasets, using tutorial mode, and more. These translated FAQs are now embedded throughout the corresponding tutorials, giving learners a fully localised experience from start to finish.

Why This Matters

Machine translation can provide a rough guide, but learners, especially those new to bioinformatics, benefit enormously from materials that read naturally in their own language. The BioNT team’s human-translated content ensures that terminology is accurate, explanations are clear, and the learning experience is as smooth as possible for German, Spanish, and Italian-speaking communities across Europe and beyond.

This work is a wonderful example of the GTN community’s commitment to open, FAIR, and inclusive training for everyone.

Thank You!

A huge thank you to all the BioNT contributors who made this possible — translators, reviewers, and everyone involved in getting these materials across the finish line:

Helena Vela , Lisanna Paladin , Alan O’Cais , Daniela Schneider , Saskia Hiltemann , Silvia Di Giorgio , Teresa Müller , Till Sauerwein , Renato Alves .

We also thank the BioNT consortium partners — including EMBL, ZB MED, EPFL, University of Barcelona, University of Freiburg, University of Oslo, biobyte solutions, RIcapacity, and HPCNow! — for making this international effort possible.

The BioNT project is co-funded by the EU Digital Europe programme, grant agreement number 101100604.

As in previous years, GTA is an asynchronous, self-paced global learning event 👩🏽‍💻🌐 open to participants from all around the world. If you would like to learn more about Galaxy, Python programming, Transcriptomics, Microbiome analysis, Genome Assembly, and many other topics, make sure to save the date!

🗓️ Key Infromation

• Dates: May 18-22, 2026
• Location: Global online
• Registration opens: March the 6th

📘 Initial Program:

(*)Tracks: Assembly, Transcriptomics, Microbiome, Machine Learning, From Zero to Hero with Python …

We are currently reaching out to the community to onboard both long-standing and new tracks.

Next steps

Over the coming months, we will finalise the core program and launch a Call for Contributions. If you are a trainer, have experience with Galaxy, or simply want to support the event, we would be thrilled to have you join us next February to help refine and improve the content.

Stay connected with us on LinkedIn, Bluesky, and Mastodon for updates and announcements.

The conference aimed to bring together teaching staff, educational researchers, training coordinators, and HR developers to exchange methods, best practices, and experiences - strengthening collaboration within the Helmholtz Association and its partners.

We were delighted to participate as an external member and to present a short pitch talk about the GTN during the BarCamp session. It was inspiring to listen to engaging talks, take part in interactive workshops, and discuss training-related topics throughout the BarCamp sessions and networking breaks.

We would like to sincerely thank the organizers for hosting this excellent event and for giving us the opportunity to take part.

As in previous years, GTA is planned to take place in Spring 2026 as an asynchronous, self-paced learning event ​👩🏽‍💻​ open to participants all around the world 🌐​. We hope to make this edition even more engaging and to build on the valuable feedback we received from last year’s event.

To make this possible, we need your help! Would you like to join the planning committee for GTA 2026? Do you want to help shape and organize the event together with us?

Based on your availability, we will set up regular organizing meetings at times that best fit the time zones of all organizers. In addition, we will use a Matrix chat for quick and asynchronous communication.

If you would like to join us later as a trainer or helper, stay tuned - we will soon announce an open call for trainers and helpers.

👉 If you are interested in helping with the planning, please fill the following Google form. In the coming weeks, we will arrange one or more meeting times, depending on your time zone, to bring you on board.

Stay connected with us on LinkedIn, Bluesky, and Mastodon for updates and announcements.

Workflows maintained by the Intergalactic Workflow Commission are also automatically registered with WorkflowHub thanks to an earlier integration. Those workflows can be viewed here: IWC on WorkflowHub

Why is it important?

The GTN encompasses a wide array of tutorials that guide researchers in the application of Galaxy for specific analyses, while also onboarding them to both the Galaxy platform itself and its vibrant community of contributors. The tutorials are often underpinned by a computational workflow that has been created to assist with the described training outcomes, and there are currently more than 330 such computational workflows. Each workflow is an investment of time, effort, and most importantly expertise. When combined with the scale, global reach, and impact of Galaxy, there is a demonstrable need for these workflows to be as findable as possible. To address this, every new tutorial that features a workflow will now be registered automatically with the WorkflowHub registry.

About WorkflowHub

WorkflowHub is a public registry dedicated to sharing computational workflows across all scientific domains. It is deliberately agnostic to workflow language, management system or discipline, meaning a Galaxy workflow, a Snakemake pipeline or a custom Python script are equally welcome.

Each workflow entry contains rich metadata, version history, license information and ontology annotations. WorkflowHub supports citation infrastructure (such as DOIs and ORCID IDs) so that authors receive scholarly credit.

Galaxy’s existing integration with WorkflowHub allows researchers to discover, import, and run workflows from WorkflowHub directly within Galaxy. Alternatively, from the WorkflowHub website, users can utilise the “Run on Galaxy” button to launch the workflow in Galaxy.

Where can I learn more?

The existing set of registered GTN workflows can be viewed here.

Read the new WorkflowHub publication to learn more about the registry: Gustafsson et al. 2025

The integration with WorkflowHub will be improved over time, enriching the metadata made discoverable through registration, and further improving the interoperability of WorkflowHub with the Galaxy ecosystem.

Band quantification can be carried out using interactive tools such as QuPath that allow researchers to define regions of interest (ROIs) directly on gel images. These ROIs can be exported as GeoJSON files, which capture the spatial coordinates of the selected bands in a standardized, machine-readable format compatible with other tools. To address this, we’ve developed a new hands-on Galaxy tutorial that shows how to combine QuPath and Galaxy imaging tools for a transparent, reproducible workflow for gel band analysis.

Why This Matters

Open-source workflows make gel quantification more accessible and reliable. They run in a web browser without extra software or powerful hardware. Each step is recorded, ensuring reproducibility, and results can be shared or adapted with ease. With this new workflow:

• QuPath is used to interactively select gel bands as regions of interest (ROIs) and export them as GeoJSON files.
• Galaxy processes these ROI files to create label maps, extract intensity values, and generate tabular results for downstream analysis.

This approach reduces bias, makes results reproducible, and integrates seamlessly with other Galaxy-based analyses.

How the Workflow Works

The tutorial walks learners through each step:

1. Image preparation – Uploading gel images into Galaxy, converting them to TIFF format, and splitting channels for analysis.
2. Annotation with QuPath – Drawing rectangles around gel bands, assigning labels, and exporting the results as GeoJSON files.
3. ROI processing in Galaxy – Converting the coordinates into label maps and extracting pixel intensities.
4. Quantification and output – Generating tabular outputs with mean intensity values for each band.

The workflow is fully documented with screenshots, tool links, and downloadable datasets, making it accessible for both beginners and advanced users.

Smooth, Reproducible Analysis

One of the key advantages of this tutorial is how it bridges the gap between interactive annotation (via QuPath) and automated quantification (via Galaxy). Learners don’t need specialized software installations—everything runs in the browser—and the results can be reproduced or extended in new analyses.

By following the steps, users gain experience with:

• Using QuPath for image annotation
• Generating and handling ROI files
• Leveraging Galaxy imaging tools for reproducible quantification

Open Tools, Open Training

As with all Galaxy Training Network (GTN) tutorials, this workflow is fully open-source and freely available. It supports the GTN’s mission to provide transparent, accessible, and reusable training resources in bioinformatics and bioimaging.

We invite educators, researchers, and learners to try the tutorial, adapt it to their datasets, and integrate it into teaching or research pipelines.

👉 Explore the tutorial here: Quantification of electrophoresis gel bands using QuPath and Galaxy imaging tools