End-to-end platform for genetic circuit design integrating Cello and Knox with machine learning to rank rule impact and guide design decisions

End-to-end generative design and evolution of synthetic biology designs — BE552 course project

Full stack application for creating, combining, and storing combinatorial genetic design spaces.

This is the code of KA-GNN

Scripts and sample data associated with Rai & O'Connell et al (2023)

Fit interpretable models. Explain blackbox machine learning.

Streamlined Cello Algorithm. Feed it Verilog and UCF from CIDARLAB/CELLO-UCF, and run celloAlgo.py in terminal to make genetic circuit designs locally on your machine.

🚀 LangGraph for Java. A library for develop AI Agentic Architectures in the Java ecosystem. Designed to work seamlessly with both Langchain4j and Spring AI.

A Machine Learning Microservice for Knox

Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages (ICML 2025) & Directed Graph Grammars for Sequence-based Learning (ICML 2025)

SBOL Designer Project

Library for combinatorially specifying, constraining, and exploring genetic design spaces.

Embedded language for defining and working with genetic design spaces.

Tool for GOLDBAR Generation using Rule Templates

A Python GUI-based framework for segmentation, tracking and cell cycle annotations of microscopy data