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Noise control for molecular computing
Synthetic biology is a growing interdisciplinary field, with far-reaching applications, which aims to design biochemical systems that behave in a desired manner. With the advancement in nucleic-acid-based technology in general, and strand-displacement DNA computing in particular, a large class of ab...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6073653/ https://www.ncbi.nlm.nih.gov/pubmed/29997258 http://dx.doi.org/10.1098/rsif.2018.0199 |
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author | Plesa, Tomislav Zygalakis, Konstantinos C. Anderson, David F. Erban, Radek |
author_facet | Plesa, Tomislav Zygalakis, Konstantinos C. Anderson, David F. Erban, Radek |
author_sort | Plesa, Tomislav |
collection | PubMed |
description | Synthetic biology is a growing interdisciplinary field, with far-reaching applications, which aims to design biochemical systems that behave in a desired manner. With the advancement in nucleic-acid-based technology in general, and strand-displacement DNA computing in particular, a large class of abstract biochemical networks may be physically realized using nucleic acids. Methods for systematic design of the abstract systems with prescribed behaviours have been predominantly developed at the (less-detailed) deterministic level. However, stochastic effects, neglected at the deterministic level, are increasingly found to play an important role in biochemistry. In such circumstances, methods for controlling the intrinsic noise in the system are necessary for a successful network design at the (more-detailed) stochastic level. To bridge the gap, the noise-control algorithm for designing biochemical networks is developed in this paper. The algorithm structurally modifies any given reaction network under mass-action kinetics, in such a way that (i) controllable state-dependent noise is introduced into the stochastic dynamics, while (ii) the deterministic dynamics are preserved. The capabilities of the algorithm are demonstrated on a production–decay reaction system, and on an exotic system displaying bistability. For the production–decay system, it is shown that the algorithm may be used to redesign the network to achieve noise-induced multistability. For the exotic system, the algorithm is used to redesign the network to control the stochastic switching, and achieve noise-induced oscillations. |
format | Online Article Text |
id | pubmed-6073653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-60736532018-08-07 Noise control for molecular computing Plesa, Tomislav Zygalakis, Konstantinos C. Anderson, David F. Erban, Radek J R Soc Interface Life Sciences–Mathematics interface Synthetic biology is a growing interdisciplinary field, with far-reaching applications, which aims to design biochemical systems that behave in a desired manner. With the advancement in nucleic-acid-based technology in general, and strand-displacement DNA computing in particular, a large class of abstract biochemical networks may be physically realized using nucleic acids. Methods for systematic design of the abstract systems with prescribed behaviours have been predominantly developed at the (less-detailed) deterministic level. However, stochastic effects, neglected at the deterministic level, are increasingly found to play an important role in biochemistry. In such circumstances, methods for controlling the intrinsic noise in the system are necessary for a successful network design at the (more-detailed) stochastic level. To bridge the gap, the noise-control algorithm for designing biochemical networks is developed in this paper. The algorithm structurally modifies any given reaction network under mass-action kinetics, in such a way that (i) controllable state-dependent noise is introduced into the stochastic dynamics, while (ii) the deterministic dynamics are preserved. The capabilities of the algorithm are demonstrated on a production–decay reaction system, and on an exotic system displaying bistability. For the production–decay system, it is shown that the algorithm may be used to redesign the network to achieve noise-induced multistability. For the exotic system, the algorithm is used to redesign the network to control the stochastic switching, and achieve noise-induced oscillations. The Royal Society 2018-07 2018-07-11 /pmc/articles/PMC6073653/ /pubmed/29997258 http://dx.doi.org/10.1098/rsif.2018.0199 Text en © 2018 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Life Sciences–Mathematics interface Plesa, Tomislav Zygalakis, Konstantinos C. Anderson, David F. Erban, Radek Noise control for molecular computing |
title | Noise control for molecular computing |
title_full | Noise control for molecular computing |
title_fullStr | Noise control for molecular computing |
title_full_unstemmed | Noise control for molecular computing |
title_short | Noise control for molecular computing |
title_sort | noise control for molecular computing |
topic | Life Sciences–Mathematics interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6073653/ https://www.ncbi.nlm.nih.gov/pubmed/29997258 http://dx.doi.org/10.1098/rsif.2018.0199 |
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