Advancing research software in the life sciences
Software plays a critical role in modern life sciences research, from analysing large-scale datasets to automating complex workflows. To ensure bioinformatics software is reliable, reproducible and sustainable, ELIXIR provides best practices, guidelines and recommendations for software development. These resources are developed in collaboration with ELIXIR Nodes, Communities and research institutes. They help researchers and developers create software that is FAIR (findable, accessible, interoperable and reusable), workflow-ready and optimised for long-term usability.
Best practices in research software
Follow established principles to help make your software reliable, usable and sustainable:
- Encourage good development habits using four simple recommendations
- Apply consistent design patterns with the general guidelines for biomedical software
- Evaluate your software’s quality using the top ten metrics for good practice
Workflow and automation in life sciences
Design tools that fit smoothly into workflows and automated analysis pipelines:
- Understand automation challenges with perspectives on workflow composition
- Make your tool easier to integrate using the ten simple rules for workflow-ready tools
Software packaging and management
Improve reusability and reproducibility through effective packaging and maintenance:
- Package your software for reuse with the containerisation recommendations
- Plan for long-term sustainability using the ELIXIR software management plan
FAIR principles for research software
Support openness and reuse by applying the FAIR principles to your software:
- Align your work with the FAIR4RS principles
- Explore how to adopt them through introducing the FAIR principles for software
Machine learning validation in biology
Ensure your AI models are robust and reliable with dedicated guidance:
- Improve model performance using DOME recommendations for validation
By following these ELIXIR-supported guidelines, researchers and developers can create high-quality, sustainable and reusable software that supports open and collaborative science.