The open-source ecosystem for data-intensive science, workflow automation, and reproducible research.
Galaxy Project is an advanced, open-source scientific workflow management system designed to make data-intensive research accessible and reproducible. By 2026, it has solidified its position as the industry standard for researchers without deep programming expertise, offering a web-based interface for complex computational biology. The technical architecture revolves around a Python-based core that integrates with distributed computing resources (SLURM, Kubernetes, HTCondor) via the Pulsar engine. Galaxy leverages Conda and Singularity for containerized tool environments, ensuring that every analysis step is precisely versioned. Its 2026 market position is defined by the integration of AI-assisted workflow generation, where Large Language Models help researchers map experimental designs to validated tool sequences. The platform supports massive datasets across genomics, proteomics, and metabolomics, utilizing a shared data library system that minimizes redundant storage. Whether deployed on public instances like UseGalaxy.org or private institutional clouds, it maintains a strict adherence to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, making it indispensable for clinical and academic research compliance.
Galaxy Project is an advanced, open-source scientific workflow management system designed to make data-intensive research accessible and reproducible.
Explore all tools that specialize in automate scientific workflows. This domain focus ensures Galaxy Project delivers optimized results for this specific requirement.
Explore all tools that specialize in sequence alignment. This domain focus ensures Galaxy Project delivers optimized results for this specific requirement.
A Python server application that allows Galaxy to run jobs on remote compute resources without a shared file system.
Embedded Jupyter and RStudio instances within the Galaxy UI that have direct access to Galaxy datasets.
An app-store like repository for sharing and versioning thousands of bioinformatics tools and wrappers.
Integration of machine learning models to predict the next best tool in an analysis pipeline based on input data types.
Automatically records every tool version, parameter setting, and input file for every analysis step.
A system for managing large shared datasets across entire research groups to prevent data duplication.
Granular permissions for datasets, tools, and histories managed via group memberships.
Create an account on a public instance (UseGalaxy.org/eu/org.au) or deploy a local instance using Docker.
Upload datasets via the 'Get Data' tool or import directly from NCBI/EBI SRA.
Organize data into 'Histories' for specific project tracking.
Select tools from the 'Tool Panel' (e.g., BWA-MEM for mapping).
Configure tool parameters and execute jobs on the distributed compute back-end.
Monitor progress in the History panel; green indicates successful completion.
Extract a reusable 'Workflow' from a successful analysis history.
Use the 'Workflow Editor' to fine-tune logic, including conditional branching.
Share results via public links or collaborate within shared Data Libraries.
Export finalized data and provenance metadata for publication or downstream AI modeling.
All Set
Ready to go
Verified feedback from other users.
"Users praise the platform for its accessibility to non-programmers and its robust reproducibility, though some note the learning curve for system administration."
Post questions, share tips, and help other users.
The global backbone for biomedical data, genomic intelligence, and clinical research informatics.
High-performance computational biology and bioinformatics infrastructure for the Julia language.
The computational science platform for reproducible research and automated R&D workflows.
The world’s first remotely operated life sciences laboratory.
Interactively visualize and analyze genomic data.
