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This repository includes code and documentation for a synthetic biology course work focusing on designing and simulating genetic circuits using logical gates (AND, OR). It features Verilog circuit descriptions, SBOL representations, machine learning-guided genetic optimization, and biological promoter libraries.

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Genetic Circuit Design and Optimization

Overview

This project focuses on designing and optimizing genetic circuits, specifically AND and OR gates, using computational and synthetic biology tools. The circuits are designed to simulate biosensing in E. coli, producing specific outputs based on given chemical inputs (AHL and Benzoate).

Key Features

  • Verilog Logical Gate Representations: AND and OR gates encoded as digital logic in Verilog.
  • SBOL Generation: Conversion of logic gates to SBOL (Synthetic Biology Open Language) format for compatibility with bio-design platforms.
  • Machine Learning Integration: Random Forest models for parameter prediction.
  • Genetic Algorithm: Optimization of circuit parameters to achieve desired biological functionality.
  • Promoter Mapping: Integration of real-world biological promoters to match circuit requirements.
  • ODE Simulation: Simulations to model gene expression and output fluorescence.

About

This repository includes code and documentation for a synthetic biology course work focusing on designing and simulating genetic circuits using logical gates (AND, OR). It features Verilog circuit descriptions, SBOL representations, machine learning-guided genetic optimization, and biological promoter libraries.

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