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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2021-07-01
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Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1009189 |
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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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1721207629547569152 |