Training opportunities at GCC2026

GCC2026 will bring about an exciting set of educational sessions so you can learn new concepts, get some practical, hands-on training, interact with others working in the similar space, and get answers for any questions you have by the top experts on the topic.

Training takes place on June 25–26, immediately following the main conference days (June 22–24). These sessions run in parallel with CoFest — you can attend training on one or both days, and switch between training and CoFest activities as your interests dictate. Registration for June 25–26 is separate from the main conference.

Training Schedule

Day 1 — Thursday, June 25

Session 1 (9:00 am – 12:00 pm)

Three parallel tracks — choose the one that fits your interests.

New and Experienced User Walkthroughs

Room A128

Galaxy developers and talk with newcomers and experince users who show how they use galaxy, highlighting how users think, and possible improvements to the platform.

Tool Wrapping

Room A129

Learn how to bring your own command-line tools into Galaxy, from writing the wrapper to testing and publishing.

Getting Ready for Galaxy Development in CoFest

Room A130

Prepare for the CoFest collaboration with this hands-on training session. Learn how to set up a local Galaxy instance on your laptop and get an introduction to Galaxy development — the perfect launchpad for contributing to Galaxy during CoFest.

Day 2 — Friday, June 26

Session 2 (9:00 am – 12:00 pm)

Three parallel tracks — choose the one that fits your interests.

Developers Do Bioinformatics

Room A128

Core Galaxy developers work through a complete bioinformatics analysis from scratch, narrating their experience live while answering a real scientific question from start to finish.

Earth Science & Ecology

Room A129

A hands-on introduction to Galaxy for environmental and ecological research, covering tools and workflows for biodiversity analysis, earth observation, and ecological modeling.

Machine Learning for Genomics

Room A130

An introduction to machine learning on Galaxy, showing how to apply models and build workflows.