Biological Software Foundations
Reusable standards, data structures, software, and metadata for programmable biology.
University of Bristol, School of Engineering Mathematics and Technology
AI-aided biodesign platforms for programming biological systems.
We develop software, data, and automation workflows to engineer organisms with novel capabilities, from more nutritious and resilient crops to microbiome therapeutics.
Developing, Researching, and Architecting Genetic and Genomic Networks.
Research Vision
Programming biology with reusable platforms
DRAGGON Lab builds AI-aided biodesign platforms that connect biological software foundations, automated DBTL workflows, machine learning, digital twins, and genetic network engineering.
Automated DBTL Workflows
Programmatic design-build-test-learn workflows for genetic network engineering.
AI-Aided Biodesign
Machine learning and hybrid models that improve design from standardized biological data.
Digital Twins of Living Systems
Simulations connecting engineered systems with cells, organisms, communities, and environments.
Intelligent Genetic & Genomic Networks
Biological architectures for sensing, computing, feedback, and decision-making in living systems.
Tool Ecosystem Preview
A platform ecosystem for the DBTL cycle
We build open, reusable software, standards-enabled metadata, and FAIR data workflows so that biological engineering can become more reproducible, collaborative, and programmable.
Design - LOICA
Program genetic networks and biological functions before building them.
Build - PUDU and BuildCompiler
Translate designs into assembly and automation-ready build plans.
Test, Learn, and Infrastructure
Connect Flapjack workflows, SeqTrainer, SynBioSuite, standards, and repositories.
Applications / Impact
Engineering organisms with useful capabilities
Resilient crops
Biodesign workflows for more nutritious, robust, and sustainable plant systems.
Microbiome therapeutics
Programmable living systems that can sense, respond, and support healthier communities.
Reusable bioengineering infrastructure
Open tools and standards that make biological engineering easier to reproduce and extend.
Featured Publications
Selected scholarly outputs
PhD thesis
Automated design, build, test, learn workflows to engineer synthetic genetic networks.
LOICA
Design automation for genetic networks.
SBOL and metadata
Standards-enabled infrastructure for reproducible biological engineering.
Featured Lab Notes
Research logs and explainers
Launching the DRAGGON Lab website
An invitation to build open AI-aided biodesign platforms.
What is biological software engineering?
A research explainer for the lab identity.
From DBTL to AI-aided biodesign
A software-platform note for the DRAGGON ecosystem.
Join / Collaborate
Build open AI-aided biodesign platforms with us
We welcome prospective students, postdocs, collaborators, funders, open-source contributors, and technically curious partners interested in programmable biological systems.