Rational design of complex phenotype via network models.

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...

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Main Authors: Marcio Gameiro, Tomáš Gedeon, Shane Kepley, Konstantin Mischaikow
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-07-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1009189
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spelling doaj-4e3fa112aaf9476398ffc49fdda9e05f2021-08-14T04:31:58ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-07-01177e100918910.1371/journal.pcbi.1009189Rational design of complex phenotype via network models.Marcio GameiroTomáš GedeonShane KepleyKonstantin MischaikowWe 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.https://doi.org/10.1371/journal.pcbi.1009189
collection DOAJ
language English
format Article
sources DOAJ
author Marcio Gameiro
Tomáš Gedeon
Shane Kepley
Konstantin Mischaikow
spellingShingle Marcio Gameiro
Tomáš Gedeon
Shane Kepley
Konstantin Mischaikow
Rational design of complex phenotype via network models.
PLoS Computational Biology
author_facet Marcio Gameiro
Tomáš Gedeon
Shane Kepley
Konstantin Mischaikow
author_sort Marcio Gameiro
title Rational design of complex phenotype via network models.
title_short Rational design of complex phenotype via network models.
title_full Rational design of complex phenotype via network models.
title_fullStr Rational design of complex phenotype via network models.
title_full_unstemmed Rational design of complex phenotype via network models.
title_sort rational design of complex phenotype via network models.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2021-07-01
description 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.
url https://doi.org/10.1371/journal.pcbi.1009189
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