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Applications of Coarse-Grained Models in Metabolic Engineering

Mathematical modeling is a promising tool for better understanding of cellular processes. In recent years, the development of coarse-grained models has gained attraction since these simple models are able to capture and describe a broad range of growth conditions. Coarse-grained models often compris...

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Autores principales: Doan, Dieu Thi, Hoang, Manh Dat, Heins, Anna-Lena, Kremling, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957914/
https://www.ncbi.nlm.nih.gov/pubmed/35350716
http://dx.doi.org/10.3389/fmolb.2022.806213
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author Doan, Dieu Thi
Hoang, Manh Dat
Heins, Anna-Lena
Kremling, Andreas
author_facet Doan, Dieu Thi
Hoang, Manh Dat
Heins, Anna-Lena
Kremling, Andreas
author_sort Doan, Dieu Thi
collection PubMed
description Mathematical modeling is a promising tool for better understanding of cellular processes. In recent years, the development of coarse-grained models has gained attraction since these simple models are able to capture and describe a broad range of growth conditions. Coarse-grained models often comprise only two cellular components, a low molecular component as representative for central metabolism and energy generation and a macromolecular component, representing the entire proteome. A framework is presented that presents a strict mass conservative model for bacterial growth during a biotechnological production process. After providing interesting properties for the steady-state solution, applications are presented 1) for a production process of an amino acid and 2) production of a metabolite from central metabolism.
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spelling pubmed-89579142022-03-28 Applications of Coarse-Grained Models in Metabolic Engineering Doan, Dieu Thi Hoang, Manh Dat Heins, Anna-Lena Kremling, Andreas Front Mol Biosci Molecular Biosciences Mathematical modeling is a promising tool for better understanding of cellular processes. In recent years, the development of coarse-grained models has gained attraction since these simple models are able to capture and describe a broad range of growth conditions. Coarse-grained models often comprise only two cellular components, a low molecular component as representative for central metabolism and energy generation and a macromolecular component, representing the entire proteome. A framework is presented that presents a strict mass conservative model for bacterial growth during a biotechnological production process. After providing interesting properties for the steady-state solution, applications are presented 1) for a production process of an amino acid and 2) production of a metabolite from central metabolism. Frontiers Media S.A. 2022-03-08 /pmc/articles/PMC8957914/ /pubmed/35350716 http://dx.doi.org/10.3389/fmolb.2022.806213 Text en Copyright © 2022 Doan, Hoang, Heins and Kremling. 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
Doan, Dieu Thi
Hoang, Manh Dat
Heins, Anna-Lena
Kremling, Andreas
Applications of Coarse-Grained Models in Metabolic Engineering
title Applications of Coarse-Grained Models in Metabolic Engineering
title_full Applications of Coarse-Grained Models in Metabolic Engineering
title_fullStr Applications of Coarse-Grained Models in Metabolic Engineering
title_full_unstemmed Applications of Coarse-Grained Models in Metabolic Engineering
title_short Applications of Coarse-Grained Models in Metabolic Engineering
title_sort applications of coarse-grained models in metabolic engineering
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957914/
https://www.ncbi.nlm.nih.gov/pubmed/35350716
http://dx.doi.org/10.3389/fmolb.2022.806213
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