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Pleione: A tool for statistical and multi-objective calibration of Rule-based models
Mathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805871/ https://www.ncbi.nlm.nih.gov/pubmed/31641245 http://dx.doi.org/10.1038/s41598-019-51546-6 |
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author | Santibáñez, Rodrigo Garrido, Daniel Martin, Alberto J. M. |
author_facet | Santibáñez, Rodrigo Garrido, Daniel Martin, Alberto J. M. |
author_sort | Santibáñez, Rodrigo |
collection | PubMed |
description | Mathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative number of statements that are easier to understand and correct. They are also gaining popularity because of their conciseness and simulation flexibility. However, RBMs generally lack tools to perform further analysis that requires simulation. This situation arises because exact and approximate simulations are computationally intensive. Translating RBMs into ODEs is commonly used to reduce simulation time, but this technique may be prohibitive due to combinatorial explosion. Here, we present the software called Pleione to calibrate RBMs. Parameter calibration is essential given the incomplete experimental determination of reaction rates and the goal of using models to reproduce experimental data. The software distributes stochastic simulations and calculations and incorporates equivalence tests to determine the fitness of RBMs compared with data. The primary features of Pleione were thoroughly tested on a model of gene regulation in Escherichia coli. Pleione yielded satisfactory results regarding calculation time and error reduction for multiple simulators, models, parameter search strategies, and computing infrastructures. |
format | Online Article Text |
id | pubmed-6805871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68058712019-10-24 Pleione: A tool for statistical and multi-objective calibration of Rule-based models Santibáñez, Rodrigo Garrido, Daniel Martin, Alberto J. M. Sci Rep Article Mathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative number of statements that are easier to understand and correct. They are also gaining popularity because of their conciseness and simulation flexibility. However, RBMs generally lack tools to perform further analysis that requires simulation. This situation arises because exact and approximate simulations are computationally intensive. Translating RBMs into ODEs is commonly used to reduce simulation time, but this technique may be prohibitive due to combinatorial explosion. Here, we present the software called Pleione to calibrate RBMs. Parameter calibration is essential given the incomplete experimental determination of reaction rates and the goal of using models to reproduce experimental data. The software distributes stochastic simulations and calculations and incorporates equivalence tests to determine the fitness of RBMs compared with data. The primary features of Pleione were thoroughly tested on a model of gene regulation in Escherichia coli. Pleione yielded satisfactory results regarding calculation time and error reduction for multiple simulators, models, parameter search strategies, and computing infrastructures. Nature Publishing Group UK 2019-10-22 /pmc/articles/PMC6805871/ /pubmed/31641245 http://dx.doi.org/10.1038/s41598-019-51546-6 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Santibáñez, Rodrigo Garrido, Daniel Martin, Alberto J. M. Pleione: A tool for statistical and multi-objective calibration of Rule-based models |
title | Pleione: A tool for statistical and multi-objective calibration of Rule-based models |
title_full | Pleione: A tool for statistical and multi-objective calibration of Rule-based models |
title_fullStr | Pleione: A tool for statistical and multi-objective calibration of Rule-based models |
title_full_unstemmed | Pleione: A tool for statistical and multi-objective calibration of Rule-based models |
title_short | Pleione: A tool for statistical and multi-objective calibration of Rule-based models |
title_sort | pleione: a tool for statistical and multi-objective calibration of rule-based models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805871/ https://www.ncbi.nlm.nih.gov/pubmed/31641245 http://dx.doi.org/10.1038/s41598-019-51546-6 |
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