From the September 2020 PLoS Computational Biology the peer-reviewed article “A compiler for biological networks on silicon chips“.
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008063
Author summary:
We present a “silicon compiler” that is capable of translating biochemical models encoded in the SBML standard into specialized analog cytomorphic hardware and transfer function–level simulations of such hardware. We show how the compiler and hardware address challenges in analog computing: 1) We ensure that the integration of errors due to the mismatch between analog circuit parameters does not become infinite over time but always remains finite via the use of total variables (the solution of the “divergence problem”); 2) We describe the compilation process through a series of examples using building blocks of biological networks, and show the results of compiling two SBML models from the literature: the Elowitz repressilator model and a rule–based model of a MAP kinase cascade.
Source code for the compiler is available at https://zenodo.org/record/3948393.
Authors:
J Kyle Medley, Jonathan Teo, Sung Sik Woo, Joseph Hellerstein, Rahul Sarpeshkar, Herbert Sauro