Platform Ecosystem

Our tools form a modular platform ecosystem for designing, building, testing, learning from, and sharing programmable biological systems. This catalog is synchronized from the public DRAGGON Lab GitHub organization whenever the website is deployed, with the last successful snapshot retained if GitHub is temporarily unavailable.

DBTL Cycle

Select a workflow stage or the infrastructure core to reveal more information.

Photo 51, X-ray diffraction of DNA (1952), produced by Raymond Gosling under Rosalind Franklin’s supervision.Image source.

Search across repository names, descriptions, development stages, and languages.

ATCG-FM is a research workspace for genomic foundation models.

Languages: Python 87.7%, Jupyter Notebook 12.3%

CellModeller2 is a GPU-accelerated multicellular modelling framework with independent implementations for Apple Metal, NVIDIA CUDA, and the CPU

Languages: Python 40.4%, C++ 24.9%, Cuda 13%, Objective-C++ 8.6%, TypeScript 5.2%, Metal 4.2%, Shell 1.2%, CMake 1.1%, CSS 0.9%, HTML 0.6%

This package extracts experimental data and metadata, converts to stardard formats, uploads to SynBioHub and Flapjack, and connects them

Languages: Jupyter Notebook 88.3%, Python 11.7%

Python package for handling SBOL on Inventoris linking physical and digital assets.

Languages: Python 93.6%, Jupyter Notebook 6.4%

GG Circuit is a desktop IDE for building genetic and genomic networks

Languages: TypeScript 61.6%, Rust 35.9%, CSS 1.4%, Shell 0.6%, Python 0.4%, HTML 0.1%, JavaScript 0.1%

DNA plotting library for Python

Languages: Python 92.2%, HTML 6.9%, Perl 0.4%, CSS 0.3%, Shell 0.2%

Python package interfacing the flapjack API with pandas and the numpy stack.

Languages: Jupyter Notebook 75.6%, Python 24.4%

WebCM is a web platform used to develop and run bacterial simulations

Languages: JavaScript 43.5%, Python 35.9%, HTML 7.1%, CSS 6.9%, GLSL 6.7%

Repository with Flapjack backend and frontend.

Languages: Python 55.6%, JavaScript 42.7%, SCSS 1%, Dockerfile 0.3%, HTML 0.2%, CSS 0.1%, Shell 0%

Software tool to predict promoters and promoter activity

Languages: TypeScript 54.9%, Python 37.4%, CSS 6.4%, Makefile 0.9%, JavaScript 0.5%

Software tool to predict operator sites and their dose response effect on gene expression using protein-DNA binding affinity.

Languages: No language data available

No language data available