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Steady-State-Preserving Simulation of Genetic Regulatory Systems
A novel family of exponential Runge-Kutta (expRK) methods are designed incorporating the stable steady-state structure of genetic regulatory systems. A natural and convenient approach to constructing new expRK methods on the base of traditional RK methods is provided. In the numerical integration of...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288607/ https://www.ncbi.nlm.nih.gov/pubmed/28203268 http://dx.doi.org/10.1155/2017/2729683 |
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author | Zhang, Ruqiang Ehigie, Julius Osato Hou, Xilin You, Xiong Yuan, Chunlu |
author_facet | Zhang, Ruqiang Ehigie, Julius Osato Hou, Xilin You, Xiong Yuan, Chunlu |
author_sort | Zhang, Ruqiang |
collection | PubMed |
description | A novel family of exponential Runge-Kutta (expRK) methods are designed incorporating the stable steady-state structure of genetic regulatory systems. A natural and convenient approach to constructing new expRK methods on the base of traditional RK methods is provided. In the numerical integration of the one-gene, two-gene, and p53-mdm2 regulatory systems, the new expRK methods are shown to be more accurate than their prototype RK methods. Moreover, for nonstiff genetic regulatory systems, the expRK methods are more efficient than some traditional exponential RK integrators in the scientific literature. |
format | Online Article Text |
id | pubmed-5288607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-52886072017-02-15 Steady-State-Preserving Simulation of Genetic Regulatory Systems Zhang, Ruqiang Ehigie, Julius Osato Hou, Xilin You, Xiong Yuan, Chunlu Comput Math Methods Med Research Article A novel family of exponential Runge-Kutta (expRK) methods are designed incorporating the stable steady-state structure of genetic regulatory systems. A natural and convenient approach to constructing new expRK methods on the base of traditional RK methods is provided. In the numerical integration of the one-gene, two-gene, and p53-mdm2 regulatory systems, the new expRK methods are shown to be more accurate than their prototype RK methods. Moreover, for nonstiff genetic regulatory systems, the expRK methods are more efficient than some traditional exponential RK integrators in the scientific literature. Hindawi Publishing Corporation 2017 2017-01-19 /pmc/articles/PMC5288607/ /pubmed/28203268 http://dx.doi.org/10.1155/2017/2729683 Text en Copyright © 2017 Ruqiang Zhang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhang, Ruqiang Ehigie, Julius Osato Hou, Xilin You, Xiong Yuan, Chunlu Steady-State-Preserving Simulation of Genetic Regulatory Systems |
title | Steady-State-Preserving Simulation of Genetic Regulatory Systems |
title_full | Steady-State-Preserving Simulation of Genetic Regulatory Systems |
title_fullStr | Steady-State-Preserving Simulation of Genetic Regulatory Systems |
title_full_unstemmed | Steady-State-Preserving Simulation of Genetic Regulatory Systems |
title_short | Steady-State-Preserving Simulation of Genetic Regulatory Systems |
title_sort | steady-state-preserving simulation of genetic regulatory systems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288607/ https://www.ncbi.nlm.nih.gov/pubmed/28203268 http://dx.doi.org/10.1155/2017/2729683 |
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