Abstract
We demonstrate a modeling and computational framework that allows for rapid screening of thousands of potential network designs for particular dynamic behavior. To illustrate this capability we consider the problem of hysteresis, a prerequisite for construction of robust bistable switches and hence a cornerstone for construction of more complex synthetic circuits. We evaluate and rank most three node networks according to their ability to robustly exhibit hysteresis where robustness is measured with respect to parameters over multiple dynamic phenotypes. Focusing on the highest ranked networks, we demonstrate how additional robustness and design constraints can be applied. We compare our results to more traditional methods based on specific parameterization of ordinary differential equation models and demonstrate a strong qualitative match at a small fraction of the computational cost.
Highlights
Our goal is to identify three-node networks that act as bistable switches over large regions of parameter space
We focus on partial paths because we do not presume to know the parameter values associated to node 0 at which the regulatory network is acting in the absence of the input signal
Our investigation into the identification of the robust expression of the phenotype of hysteresis demonstrates Dynamic Signatures Generated by Regulatory Networks (DSGRN)’s practical value—in synthetic biology hysteresis forms a basis for a design of a bistable switch
Summary
Foundation under awards DMS-1839294 and HDR TRIPODS award CCF-1934924, DARPA contract HR0011-16-2-0033, and National Institutes of Health award R01 GM126555. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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