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A global sensitivity analysis approach for morphogenesis models

BACKGROUND: Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and th...

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Autores principales: Boas, Sonja E. M., Navarro Jimenez, Maria I., Merks, Roeland M. H., Blom, Joke G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4654849/
https://www.ncbi.nlm.nih.gov/pubmed/26589144
http://dx.doi.org/10.1186/s12918-015-0222-7
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author Boas, Sonja E. M.
Navarro Jimenez, Maria I.
Merks, Roeland M. H.
Blom, Joke G.
author_facet Boas, Sonja E. M.
Navarro Jimenez, Maria I.
Merks, Roeland M. H.
Blom, Joke G.
author_sort Boas, Sonja E. M.
collection PubMed
description BACKGROUND: Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. RESULTS: To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. CONCLUSIONS: We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-015-0222-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-46548492015-11-22 A global sensitivity analysis approach for morphogenesis models Boas, Sonja E. M. Navarro Jimenez, Maria I. Merks, Roeland M. H. Blom, Joke G. BMC Syst Biol Research Article BACKGROUND: Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. RESULTS: To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. CONCLUSIONS: We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-015-0222-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-21 /pmc/articles/PMC4654849/ /pubmed/26589144 http://dx.doi.org/10.1186/s12918-015-0222-7 Text en © Boas et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Boas, Sonja E. M.
Navarro Jimenez, Maria I.
Merks, Roeland M. H.
Blom, Joke G.
A global sensitivity analysis approach for morphogenesis models
title A global sensitivity analysis approach for morphogenesis models
title_full A global sensitivity analysis approach for morphogenesis models
title_fullStr A global sensitivity analysis approach for morphogenesis models
title_full_unstemmed A global sensitivity analysis approach for morphogenesis models
title_short A global sensitivity analysis approach for morphogenesis models
title_sort global sensitivity analysis approach for morphogenesis models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4654849/
https://www.ncbi.nlm.nih.gov/pubmed/26589144
http://dx.doi.org/10.1186/s12918-015-0222-7
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