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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Autores principales:	Marcio Gameiro, Tomáš Gedeon, Shane Kepley, Konstantin Mischaikow
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/4e3fa112aaf9476398ffc49fdda9e05f
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id	oai:doaj.org-article:4e3fa112aaf9476398ffc49fdda9e05f
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spelling	oai:doaj.org-article:4e3fa112aaf9476398ffc49fdda9e05f2021-12-02T19:57:21ZRational design of complex phenotype via network models.1553-734X1553-735810.1371/journal.pcbi.1009189https://doaj.org/article/4e3fa112aaf9476398ffc49fdda9e05f2021-07-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009189https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358We 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.Marcio GameiroTomáš GedeonShane KepleyKonstantin MischaikowPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 7, p e1009189 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Marcio Gameiro Tomáš Gedeon Shane Kepley Konstantin Mischaikow Rational design of complex phenotype via network models.
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.
format	article
author	Marcio Gameiro Tomáš Gedeon Shane Kepley Konstantin Mischaikow
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)
publishDate	2021
url	https://doaj.org/article/4e3fa112aaf9476398ffc49fdda9e05f
work_keys_str_mv	AT marciogameiro rationaldesignofcomplexphenotypevianetworkmodels AT tomasgedeon rationaldesignofcomplexphenotypevianetworkmodels AT shanekepley rationaldesignofcomplexphenotypevianetworkmodels AT konstantinmischaikow rationaldesignofcomplexphenotypevianetworkmodels
_version_	1718375836428533760

Rational design of complex phenotype via network models.

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