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Process-based design of dynamical biological systems

The computational design of dynamical systems is an important emerging task in synthetic biology. Given desired properties of the behaviour of a dynamical system, the task of design is to build an in-silico model of a system whose simulated be- haviour meets these properties. We introduce a new, pro...

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Detalles Bibliográficos
Autores principales: Tanevski, Jovan, Todorovski, Ljupčo, Džeroski, Sašo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5043446/
https://www.ncbi.nlm.nih.gov/pubmed/27686219
http://dx.doi.org/10.1038/srep34107
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author Tanevski, Jovan
Todorovski, Ljupčo
Džeroski, Sašo
author_facet Tanevski, Jovan
Todorovski, Ljupčo
Džeroski, Sašo
author_sort Tanevski, Jovan
collection PubMed
description The computational design of dynamical systems is an important emerging task in synthetic biology. Given desired properties of the behaviour of a dynamical system, the task of design is to build an in-silico model of a system whose simulated be- haviour meets these properties. We introduce a new, process-based, design methodology for addressing this task. The new methodology combines a flexible process-based formalism for specifying the space of candidate designs with multi-objective optimization approaches for selecting the most appropriate among these candidates. We demonstrate that the methodology is general enough to both formulate and solve tasks of designing deterministic and stochastic systems, successfully reproducing plausible designs reported in previous studies and proposing new designs that meet the design criteria, but have not been previously considered.
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spelling pubmed-50434462016-10-05 Process-based design of dynamical biological systems Tanevski, Jovan Todorovski, Ljupčo Džeroski, Sašo Sci Rep Article The computational design of dynamical systems is an important emerging task in synthetic biology. Given desired properties of the behaviour of a dynamical system, the task of design is to build an in-silico model of a system whose simulated be- haviour meets these properties. We introduce a new, process-based, design methodology for addressing this task. The new methodology combines a flexible process-based formalism for specifying the space of candidate designs with multi-objective optimization approaches for selecting the most appropriate among these candidates. We demonstrate that the methodology is general enough to both formulate and solve tasks of designing deterministic and stochastic systems, successfully reproducing plausible designs reported in previous studies and proposing new designs that meet the design criteria, but have not been previously considered. Nature Publishing Group 2016-09-30 /pmc/articles/PMC5043446/ /pubmed/27686219 http://dx.doi.org/10.1038/srep34107 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Tanevski, Jovan
Todorovski, Ljupčo
Džeroski, Sašo
Process-based design of dynamical biological systems
title Process-based design of dynamical biological systems
title_full Process-based design of dynamical biological systems
title_fullStr Process-based design of dynamical biological systems
title_full_unstemmed Process-based design of dynamical biological systems
title_short Process-based design of dynamical biological systems
title_sort process-based design of dynamical biological systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5043446/
https://www.ncbi.nlm.nih.gov/pubmed/27686219
http://dx.doi.org/10.1038/srep34107
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