Modeling Biochemical Reactions and Gene Networks with Memristors

This poster investigates qualitative and quantitative analogies between biochemical reactions and memristive devices. It shows that memristors can mimic biochemical reactions and gene networks efficiently, and capture both deterministic and stochastic dynamics at the nanoscale level. We present different abstraction models and memristor-based circuits that inherently model the activity of genetic circuits with low signal-to-noise ratio (SNR). These findings constitute a promising step towards noise-tolerant and energy-efficient electronic circuit design - Cytomorphic electronics.The main goals of this field are to simulate cells, organs, and tissues while considering the stochastic behavior of a single cell and cell-to-cell variation, distortion, and cross-talk using mixed-signal integrated electronics. Additionally, cytomorphic electronics is used to design novel large-scale synthetic biological systems by providing a fast and simple emulative framework. Furthermore, the field has aided in the design of electronic circuits and networks inspired by molecular biology, with uniquely emergent characteristics and concepts to be adopted for energy-efficient hardware realization.