A compiler for biological networks on silicon chips

Area of Science:

• Systems Biology
• Computational Biology
• Bioengineering

Background:

• Semiconductor industry growth driven by design automation software.
• Biological circuit design and analysis require scalable simulation approaches.

Purpose of the Study:

• To develop a compiler for translating chemical reaction networks into hardware configurations for cytomorphic simulation.
• To enable scalable design and analysis of synthetic and natural biological circuits.

Main Methods:

• A compiler that converts standard representations of chemical reaction networks into hardware configurations.
• Generation of circuit-level models for validation without physical hardware experimentation.
• Compilation of various kinetic models including mass-action, enzyme kinetics, and genetic repressor kinetics.

Main Results:

• Demonstrated compilation of diverse kinetic models, including a MAP kinase model using rule-based formalisms.
• Successful translation of complex biological networks into hardware representations.
• Creation of circuit-level models for enhanced compiler versatility and validation.

Conclusions:

• The developed compiler and specialized hardware enable scalable simulation of biological networks.
• This approach facilitates the simulation of larger kinetic models and parallel processing of multiple networks.
• Potential to significantly advance the performance of biological network simulations beyond current capabilities.