Year: 2021
Type: article
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.
Source: PLoS Computational Biology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,575
Awards: Applications of Computational and Topological Methods to Dynamical Systems, G2405702604, G2515541506, G295657101, G3064008058, Tripods+X:Res: Collaborative Research: Identification of Gene Regulatory Network Function from Data, G4713059963, G5270150132, G6517621824, G668241585, HDR TRIPODS: Data Science Principles of the Human-Machine Convergence, Needle in a haystack: effective search for dynamics across the space of networks, Tripods+X:Res: Collaborative Research: Identification of Gene Regulatory Network Function from Data
OpenAlex ID: W3091988491