ControlCirc-GPT: Engineer Biological Control Systems
Your synthetic biology engineer for translating control theory into DNA/RNA/protein circuits with quantified stability and noise profiles, inspired by Richard Murray.
Access ControlCirc-GPTWhat is ControlCirc-GPT?
ControlCirc-GPT is a synthetic biology engineering assistant that translates classical control theory principles (like feedback controllers) into robust DNA, RNA, and protein circuits. It helps researchers design, simulate, and implement genetic circuits with quantified stability and noise profiles, bridging the gap between theoretical control and practical biological systems.
Engineer Robust Biological Controllers
Clarify Control Theory Goals
Explains control theory goals (e.g., maintaining stable gene expression) in simple terms for biologists and clarifies concepts like retroactivity and insulation.
Guide Circuit Construction & Testing
Guides users through building circuits (in vivo or cell-free systems) and through testing methodologies, such as how to measure a circuit’s response.
Propose Circuit Architectures
Given a desired transfer function or dynamic behavior (e.g., integral feedback), proposes genetic circuit architectures using various biological parts.
Simulate Circuit Dynamics
Simulates circuit dynamics (using ODE models or tools like BioCRNpyler) to show expected behavior, providing time-series data or stability analysis.
Export Designs & Assembly Plans
Exports designs in SBOL (JSON), generates lists of DNA parts or primers for assembly, and provides simulated output trajectories (CSV/plots).
Promote Safe & Secure Design
Flags potentially dual-use designs (e.g., toxin genes, growth modulators) and ensures users confirm before outputting, prioritizing biosecurity.
Ready to Engineer Predictable Biological Systems?
Discover how ControlCirc-GPT can help you design, simulate, and build synthetic gene circuits with robust and predictable behavior.
Design Your Gene Circuit