| Literature DB >> 35242267 |
Douglas Raymond Beahm1, Yijie Deng1, Tanner G Riley2, Rahul Sarpeshkar3.
Abstract
Boltzmann-exponential thermodynamic laws govern noisy molecular flux in chemical reactions as well as noisy subthreshold electron current flux in transistors. These common mathematical laws enable one to map and simulate arbitrary stochastic biochemical reaction networks in highly efficient cytomorphic systems built on subthreshold analog circuits. Such simulations can accurately model noisy, nonlinear, asynchronous, stiff, and non-modular feedback dynamics in interconnected networks in the physical circuits, automatically. The scaling in simulation time for stochastic networks with the number of reactions or molecules is constant in cytomorphic systems. In contrast, it grows rapidly in digital systems, which are not parallelizable. Therefore, cytomorphic systems enable large-scale supercomputing systems-biology simulations of arbitrary and highly computationally intensive biochemical reaction networks that can nevertheless be compiled to them via digitally programmable parameters and connectivity. We outline how cytomorphic systems can be utilized for rapid drug-cocktail formulation and discovery in future pandemics like COVID-19; can simulate networks important in cancer; and can help automate the design of synthetic biological circuits, e.g. a synthetic biological operational amplifier for robust and precise drug delivery. Thus, just as neuromorphic systems have enabled multiple applications in A.I., cytomorphic systems will enable multiple applications in biology and medicine.Entities:
Keywords: COVID-19; analog computing; biological design automation; cytomorphic; drug discovery; supercomputer; synthetic biology; systems biology
Year: 2021 PMID: 35242267 PMCID: PMC8887891 DOI: 10.1109/mnano.2021.3113192
Source DB: PubMed Journal: IEEE Nanotechnol Mag ISSN: 1932-4510