Cytomorphic Electronics With Memristors for Modeling Fundamental Genetic Circuits

Area of Science:

• Electronics
• Systems Biology
• Synthetic Biology

Background:

• Cytomorphic engineering studies cellular behavior using electronics, analogous to neuromorphic engineering.
• Current cytomorphic circuits often use translinear electronics, but could benefit from reduced memory area using memristive circuits.

Purpose of the Study:

• To propose a novel approach for modeling biological systems using memristive circuits.
• To demonstrate the ability of memristive devices to capture the nonlinear and stochastic behavior of biochemical reactions.
• To design analog memristive circuits that emulate biophysical mechanisms of gene expression.

Main Methods:

• Utilizing Boltzmann-exponential stochastic transport of ionic species through insulators.
• Designing two-terminal memristive devices to model biochemical reactions.
• Developing analog memristive circuit building blocks for gene expression mechanisms.
• Forming complex mixed-signal networks to simulate biological pathways.

Main Results:

• Memristive devices successfully captured nonlinear and stochastic biochemical reaction behaviors.
• Designed circuits inherently modeled gene expression mechanisms like induction, repression, and regulation.
• Simulated complex networks, including a delay-induced oscillator and the p53-mdm2 cancer pathway interaction.

Conclusions:

• The proposed memristive approach provides a fast and simple emulative framework for studying genetic and biological networks.
• This method is applicable to systems biology and synthetic biology research.
• Challenges include memristor longevity and slower time constants compared to traditional electronics.