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Chemical Reaction Networks’ Programming for Solving Equations

The computational ability of the chemical reaction networks (CRNs) using DNA as the substrate has been verified previously. To solve more complex computational problems and perform the computational steps as expected, the practical design of the basic modules of calculation and the steps in the reac...

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Detalles Bibliográficos
Autores principales: Shang, Ziwei, Zhou, Changjun, Zhang, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164072/
https://www.ncbi.nlm.nih.gov/pubmed/35723377
http://dx.doi.org/10.3390/cimb44040119
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author Shang, Ziwei
Zhou, Changjun
Zhang, Qiang
author_facet Shang, Ziwei
Zhou, Changjun
Zhang, Qiang
author_sort Shang, Ziwei
collection PubMed
description The computational ability of the chemical reaction networks (CRNs) using DNA as the substrate has been verified previously. To solve more complex computational problems and perform the computational steps as expected, the practical design of the basic modules of calculation and the steps in the reactions have become the basic requirements for biomolecular computing. This paper presents a method for solving nonlinear equations in the CRNs with DNA as the substrate. We used the basic calculation module of the CRNs with a gateless structure to design discrete and analog algorithms and realized the nonlinear equations that could not be solved in the previous work, such as exponential, logarithmic, and simple triangle equations. The solution of the equation uses the transformation method, Taylor expansion, and Newton iteration method, and the simulation verified this through examples. We used and improved the basic calculation module of the CRN++ programming language, optimized the error in the basic module, and analyzed the error’s variation over time.
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spelling pubmed-91640722022-06-04 Chemical Reaction Networks’ Programming for Solving Equations Shang, Ziwei Zhou, Changjun Zhang, Qiang Curr Issues Mol Biol Article The computational ability of the chemical reaction networks (CRNs) using DNA as the substrate has been verified previously. To solve more complex computational problems and perform the computational steps as expected, the practical design of the basic modules of calculation and the steps in the reactions have become the basic requirements for biomolecular computing. This paper presents a method for solving nonlinear equations in the CRNs with DNA as the substrate. We used the basic calculation module of the CRNs with a gateless structure to design discrete and analog algorithms and realized the nonlinear equations that could not be solved in the previous work, such as exponential, logarithmic, and simple triangle equations. The solution of the equation uses the transformation method, Taylor expansion, and Newton iteration method, and the simulation verified this through examples. We used and improved the basic calculation module of the CRN++ programming language, optimized the error in the basic module, and analyzed the error’s variation over time. MDPI 2022-04-14 /pmc/articles/PMC9164072/ /pubmed/35723377 http://dx.doi.org/10.3390/cimb44040119 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shang, Ziwei
Zhou, Changjun
Zhang, Qiang
Chemical Reaction Networks’ Programming for Solving Equations
title Chemical Reaction Networks’ Programming for Solving Equations
title_full Chemical Reaction Networks’ Programming for Solving Equations
title_fullStr Chemical Reaction Networks’ Programming for Solving Equations
title_full_unstemmed Chemical Reaction Networks’ Programming for Solving Equations
title_short Chemical Reaction Networks’ Programming for Solving Equations
title_sort chemical reaction networks’ programming for solving equations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164072/
https://www.ncbi.nlm.nih.gov/pubmed/35723377
http://dx.doi.org/10.3390/cimb44040119
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