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Mathematical models in GnRH research
Mathematical modelling is an indispensable tool in modern biosciences, enabling quantitative analysis and integration of biological data, transparent formulation of our understanding of complex biological systems, and efficient experimental design based on model predictions. This review article prov...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285519/ https://www.ncbi.nlm.nih.gov/pubmed/35080068 http://dx.doi.org/10.1111/jne.13085 |
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author | Voliotis, Margaritis Plain, Zoe Li, Xiao Feng McArdle, Craig A. O’Byrne, Kevin T. Tsaneva‐Atanasova, Krasimira |
author_facet | Voliotis, Margaritis Plain, Zoe Li, Xiao Feng McArdle, Craig A. O’Byrne, Kevin T. Tsaneva‐Atanasova, Krasimira |
author_sort | Voliotis, Margaritis |
collection | PubMed |
description | Mathematical modelling is an indispensable tool in modern biosciences, enabling quantitative analysis and integration of biological data, transparent formulation of our understanding of complex biological systems, and efficient experimental design based on model predictions. This review article provides an overview of the impact that mathematical models had on GnRH research. Indeed, over the last 20 years mathematical modelling has been used to describe and explore the physiology of the GnRH neuron, the mechanisms underlying GnRH pulsatile secretion, and GnRH signalling to the pituitary. Importantly, these models have contributed to GnRH research via novel hypotheses and predictions regarding the bursting behaviour of the GnRH neuron, the role of kisspeptin neurons in the emergence of pulsatile GnRH dynamics, and the decoding of GnRH signals by biochemical signalling networks. We envisage that with the advent of novel experimental technologies, mathematical modelling will have an even greater role to play in our endeavour to understand the complex spatiotemporal dynamics underlying the reproductive neuroendocrine system. |
format | Online Article Text |
id | pubmed-9285519 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92855192022-07-18 Mathematical models in GnRH research Voliotis, Margaritis Plain, Zoe Li, Xiao Feng McArdle, Craig A. O’Byrne, Kevin T. Tsaneva‐Atanasova, Krasimira J Neuroendocrinol Invited Review Mathematical modelling is an indispensable tool in modern biosciences, enabling quantitative analysis and integration of biological data, transparent formulation of our understanding of complex biological systems, and efficient experimental design based on model predictions. This review article provides an overview of the impact that mathematical models had on GnRH research. Indeed, over the last 20 years mathematical modelling has been used to describe and explore the physiology of the GnRH neuron, the mechanisms underlying GnRH pulsatile secretion, and GnRH signalling to the pituitary. Importantly, these models have contributed to GnRH research via novel hypotheses and predictions regarding the bursting behaviour of the GnRH neuron, the role of kisspeptin neurons in the emergence of pulsatile GnRH dynamics, and the decoding of GnRH signals by biochemical signalling networks. We envisage that with the advent of novel experimental technologies, mathematical modelling will have an even greater role to play in our endeavour to understand the complex spatiotemporal dynamics underlying the reproductive neuroendocrine system. John Wiley and Sons Inc. 2022-01-25 2022-05 /pmc/articles/PMC9285519/ /pubmed/35080068 http://dx.doi.org/10.1111/jne.13085 Text en © 2021 The Authors. Journal of Neuroendocrinology published by John Wiley & Sons Ltd on behalf of British Society for Neuroendocrinology. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Invited Review Voliotis, Margaritis Plain, Zoe Li, Xiao Feng McArdle, Craig A. O’Byrne, Kevin T. Tsaneva‐Atanasova, Krasimira Mathematical models in GnRH research |
title | Mathematical models in GnRH research |
title_full | Mathematical models in GnRH research |
title_fullStr | Mathematical models in GnRH research |
title_full_unstemmed | Mathematical models in GnRH research |
title_short | Mathematical models in GnRH research |
title_sort | mathematical models in gnrh research |
topic | Invited Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285519/ https://www.ncbi.nlm.nih.gov/pubmed/35080068 http://dx.doi.org/10.1111/jne.13085 |
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