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Determining minimal output sets that ensure structural identifiability
The process of inferring parameter values from experimental data can be a cumbersome task. In addition, the collection of experimental data can be time consuming and costly. This paper covers both these issues by addressing the following question: “Which experimental outputs should be measured to en...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231658/ https://www.ncbi.nlm.nih.gov/pubmed/30419074 http://dx.doi.org/10.1371/journal.pone.0207334 |
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author | Joubert, D. Stigter, J. D. Molenaar, J. |
author_facet | Joubert, D. Stigter, J. D. Molenaar, J. |
author_sort | Joubert, D. |
collection | PubMed |
description | The process of inferring parameter values from experimental data can be a cumbersome task. In addition, the collection of experimental data can be time consuming and costly. This paper covers both these issues by addressing the following question: “Which experimental outputs should be measured to ensure that unique model parameters can be calculated?”. Stated formally, we examine the topic of minimal output sets that guarantee a model’s structural identifiability. To that end, we introduce an algorithm that guides a researcher as to which model outputs to measure. Our algorithm consists of an iterative structural identifiability analysis and can determine multiple minimal output sets of a model. This choice in different output sets offers researchers flexibility during experimental design. Our method can determine minimal output sets of large differential equation models within short computational times. |
format | Online Article Text |
id | pubmed-6231658 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62316582018-11-19 Determining minimal output sets that ensure structural identifiability Joubert, D. Stigter, J. D. Molenaar, J. PLoS One Research Article The process of inferring parameter values from experimental data can be a cumbersome task. In addition, the collection of experimental data can be time consuming and costly. This paper covers both these issues by addressing the following question: “Which experimental outputs should be measured to ensure that unique model parameters can be calculated?”. Stated formally, we examine the topic of minimal output sets that guarantee a model’s structural identifiability. To that end, we introduce an algorithm that guides a researcher as to which model outputs to measure. Our algorithm consists of an iterative structural identifiability analysis and can determine multiple minimal output sets of a model. This choice in different output sets offers researchers flexibility during experimental design. Our method can determine minimal output sets of large differential equation models within short computational times. Public Library of Science 2018-11-12 /pmc/articles/PMC6231658/ /pubmed/30419074 http://dx.doi.org/10.1371/journal.pone.0207334 Text en © 2018 Joubert et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Joubert, D. Stigter, J. D. Molenaar, J. Determining minimal output sets that ensure structural identifiability |
title | Determining minimal output sets that ensure structural identifiability |
title_full | Determining minimal output sets that ensure structural identifiability |
title_fullStr | Determining minimal output sets that ensure structural identifiability |
title_full_unstemmed | Determining minimal output sets that ensure structural identifiability |
title_short | Determining minimal output sets that ensure structural identifiability |
title_sort | determining minimal output sets that ensure structural identifiability |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231658/ https://www.ncbi.nlm.nih.gov/pubmed/30419074 http://dx.doi.org/10.1371/journal.pone.0207334 |
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