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Multiscale models driving hypothesis and theory-based research in microbial ecology
Hypothesis and theory-based studies in microbial ecology have been neglected in favour of those that are descriptive and aim for data-gathering of uncultured microbial species. This tendency limits our capacity to create new mechanistic explanations of microbial community dynamics, hampering the imp...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10251115/ https://www.ncbi.nlm.nih.gov/pubmed/37303746 http://dx.doi.org/10.1098/rsfs.2023.0008 |
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author | Martinez-Rabert, Eloi Sloan, William T. Gonzalez-Cabaleiro, Rebeca |
author_facet | Martinez-Rabert, Eloi Sloan, William T. Gonzalez-Cabaleiro, Rebeca |
author_sort | Martinez-Rabert, Eloi |
collection | PubMed |
description | Hypothesis and theory-based studies in microbial ecology have been neglected in favour of those that are descriptive and aim for data-gathering of uncultured microbial species. This tendency limits our capacity to create new mechanistic explanations of microbial community dynamics, hampering the improvement of current environmental biotechnologies. We propose that a multiscale modelling bottom-up approach (piecing together sub-systems to give rise to more complex systems) can be used as a framework to generate mechanistic hypotheses and theories (in-silico bottom-up methodology). To accomplish this, formal comprehension of the mathematical model design is required together with a systematic procedure for the application of the in-silico bottom-up methodology. Ruling out the belief that experimentation before modelling is indispensable, we propose that mathematical modelling can be used as a tool to direct experimentation by validating theoretical principles of microbial ecology. Our goal is to develop methodologies that effectively integrate experimentation and modelling efforts to achieve superior levels of predictive capacity. |
format | Online Article Text |
id | pubmed-10251115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-102511152023-06-10 Multiscale models driving hypothesis and theory-based research in microbial ecology Martinez-Rabert, Eloi Sloan, William T. Gonzalez-Cabaleiro, Rebeca Interface Focus Articles Hypothesis and theory-based studies in microbial ecology have been neglected in favour of those that are descriptive and aim for data-gathering of uncultured microbial species. This tendency limits our capacity to create new mechanistic explanations of microbial community dynamics, hampering the improvement of current environmental biotechnologies. We propose that a multiscale modelling bottom-up approach (piecing together sub-systems to give rise to more complex systems) can be used as a framework to generate mechanistic hypotheses and theories (in-silico bottom-up methodology). To accomplish this, formal comprehension of the mathematical model design is required together with a systematic procedure for the application of the in-silico bottom-up methodology. Ruling out the belief that experimentation before modelling is indispensable, we propose that mathematical modelling can be used as a tool to direct experimentation by validating theoretical principles of microbial ecology. Our goal is to develop methodologies that effectively integrate experimentation and modelling efforts to achieve superior levels of predictive capacity. The Royal Society 2023-06-09 /pmc/articles/PMC10251115/ /pubmed/37303746 http://dx.doi.org/10.1098/rsfs.2023.0008 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles Martinez-Rabert, Eloi Sloan, William T. Gonzalez-Cabaleiro, Rebeca Multiscale models driving hypothesis and theory-based research in microbial ecology |
title | Multiscale models driving hypothesis and theory-based research in microbial ecology |
title_full | Multiscale models driving hypothesis and theory-based research in microbial ecology |
title_fullStr | Multiscale models driving hypothesis and theory-based research in microbial ecology |
title_full_unstemmed | Multiscale models driving hypothesis and theory-based research in microbial ecology |
title_short | Multiscale models driving hypothesis and theory-based research in microbial ecology |
title_sort | multiscale models driving hypothesis and theory-based research in microbial ecology |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10251115/ https://www.ncbi.nlm.nih.gov/pubmed/37303746 http://dx.doi.org/10.1098/rsfs.2023.0008 |
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