standards
Biological Software Foundations
Standards, metadata, repositories, and open software infrastructure for reproducible programmable biology.
- standards
- SBOL
- FAIR data
- infrastructure
DRAGGON Lab treats DNA as an engineerable information substrate and asks what software infrastructure is needed to make biological systems easier to design, reproduce, share, and extend. This research area focuses on the standards, metadata models, repositories, and developer tools that let biological design work more like a collaborative software ecosystem.
Why it matters
Synthetic biology needs reusable abstractions, traceable build plans, calibrated measurements, and machine-readable context. Standards such as SBOL, FAIR metadata practices, and repository infrastructure such as SynBioHub can make design-build-test-learn work auditable across people, institutions, and automation platforms.
What we build
We develop content models, graph representations, and software interfaces that connect genetic designs, build metadata, experimental measurements, and learning workflows. This foundation supports functional synthetic biology: describing systems by what they are intended to do, not only by the DNA sequence used to implement them.
Near-term outputs
Early outputs include a public map of the DRAGGON ecosystem, reusable SBOL/SynBioHub content patterns, and validation rules that help keep lab data and software documentation ready for collaboration, automation, and AI-assisted analysis.