BioRxToolbox: a computational framework to streamline genetic circuit design in molecular data communications

Area of Science:

• Bioengineering
• Synthetic Biology
• Nanotechnology

Background:

• Molecular communication systems face challenges with signal distortion due to diffusing molecules.
• Existing models lack end-to-end system response, overlooking receiver detection of distorted signals.

Purpose of the Study:

• To present BioRxToolbox, a computational framework for designing diffusion-based, end-to-end molecular communication systems.
• To enable efficient data encoding and decoding using synthetic genetic circuits and novel molecular strategies.

Main Methods:

• Developed a novel framework for encoding information as molecular bursts.
• Implemented equalization techniques to minimize signal interference.
• Utilized two types of molecules: a data carrier and an antagonist for signal cancellation.

Main Results:

• Demonstrated BioRxToolbox with biological designs and simulations.
• Showcased efficient encoding and decoding of data bits.
• Identified optimal communication parameters and scenarios for cellular signal generation.

Conclusions:

• BioRxToolbox facilitates the design of robust molecular communication systems.
• The framework automates parameter selection and identifies efficient communication scenarios.
• This approach advances the integration of communication theory with synthetic biology for biological data transmission.