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Generalized Structural Kinetic Modeling: A Survey and Guide

Many current challenges involve understanding the complex dynamical interplay between the constituents of systems. Typically, the number of such constituents is high, but only limited data sources on them are available. Conventional dynamical models of complex systems are rarely mathematically tract...

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Detalles Bibliográficos
Autores principales: Massing, Jana C., Gross, Thilo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9098827/
https://www.ncbi.nlm.nih.gov/pubmed/35573734
http://dx.doi.org/10.3389/fmolb.2022.825052
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author Massing, Jana C.
Gross, Thilo
author_facet Massing, Jana C.
Gross, Thilo
author_sort Massing, Jana C.
collection PubMed
description Many current challenges involve understanding the complex dynamical interplay between the constituents of systems. Typically, the number of such constituents is high, but only limited data sources on them are available. Conventional dynamical models of complex systems are rarely mathematically tractable and their numerical exploration suffers both from computational and data limitations. Here we review generalized modeling, an alternative approach for formulating dynamical models to gain insights into dynamics and bifurcations of uncertain systems. We argue that this approach deals elegantly with the uncertainties that exist in real world data and enables analytical insight or highly efficient numerical investigation. We provide a survey of recent successes of generalized modeling and a guide to the application of this modeling approach in future studies such as complex integrative ecological models.
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spelling pubmed-90988272022-05-14 Generalized Structural Kinetic Modeling: A Survey and Guide Massing, Jana C. Gross, Thilo Front Mol Biosci Molecular Biosciences Many current challenges involve understanding the complex dynamical interplay between the constituents of systems. Typically, the number of such constituents is high, but only limited data sources on them are available. Conventional dynamical models of complex systems are rarely mathematically tractable and their numerical exploration suffers both from computational and data limitations. Here we review generalized modeling, an alternative approach for formulating dynamical models to gain insights into dynamics and bifurcations of uncertain systems. We argue that this approach deals elegantly with the uncertainties that exist in real world data and enables analytical insight or highly efficient numerical investigation. We provide a survey of recent successes of generalized modeling and a guide to the application of this modeling approach in future studies such as complex integrative ecological models. Frontiers Media S.A. 2022-04-29 /pmc/articles/PMC9098827/ /pubmed/35573734 http://dx.doi.org/10.3389/fmolb.2022.825052 Text en Copyright © 2022 Massing and Gross. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Massing, Jana C.
Gross, Thilo
Generalized Structural Kinetic Modeling: A Survey and Guide
title Generalized Structural Kinetic Modeling: A Survey and Guide
title_full Generalized Structural Kinetic Modeling: A Survey and Guide
title_fullStr Generalized Structural Kinetic Modeling: A Survey and Guide
title_full_unstemmed Generalized Structural Kinetic Modeling: A Survey and Guide
title_short Generalized Structural Kinetic Modeling: A Survey and Guide
title_sort generalized structural kinetic modeling: a survey and guide
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9098827/
https://www.ncbi.nlm.nih.gov/pubmed/35573734
http://dx.doi.org/10.3389/fmolb.2022.825052
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