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The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes

For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemis...

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Autores principales: Seaver, Samuel M D, Liu, Filipe, Zhang, Qizhi, Jeffryes, James, Faria, José P, Edirisinghe, Janaka N, Mundy, Michael, Chia, Nicholas, Noor, Elad, Beber, Moritz E, Best, Aaron A, DeJongh, Matthew, Kimbrel, Jeffrey A, D’haeseleer, Patrik, McCorkle, Sean R, Bolton, Jay R, Pearson, Erik, Canon, Shane, Wood-Charlson, Elisha M, Cottingham, Robert W, Arkin, Adam P, Henry, Christopher S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778927/
https://www.ncbi.nlm.nih.gov/pubmed/32986834
http://dx.doi.org/10.1093/nar/gkaa746
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author Seaver, Samuel M D
Liu, Filipe
Zhang, Qizhi
Jeffryes, James
Faria, José P
Edirisinghe, Janaka N
Mundy, Michael
Chia, Nicholas
Noor, Elad
Beber, Moritz E
Best, Aaron A
DeJongh, Matthew
Kimbrel, Jeffrey A
D’haeseleer, Patrik
McCorkle, Sean R
Bolton, Jay R
Pearson, Erik
Canon, Shane
Wood-Charlson, Elisha M
Cottingham, Robert W
Arkin, Adam P
Henry, Christopher S
author_facet Seaver, Samuel M D
Liu, Filipe
Zhang, Qizhi
Jeffryes, James
Faria, José P
Edirisinghe, Janaka N
Mundy, Michael
Chia, Nicholas
Noor, Elad
Beber, Moritz E
Best, Aaron A
DeJongh, Matthew
Kimbrel, Jeffrey A
D’haeseleer, Patrik
McCorkle, Sean R
Bolton, Jay R
Pearson, Erik
Canon, Shane
Wood-Charlson, Elisha M
Cottingham, Robert W
Arkin, Adam P
Henry, Christopher S
author_sort Seaver, Samuel M D
collection PubMed
description For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.
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spelling pubmed-77789272021-01-06 The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes Seaver, Samuel M D Liu, Filipe Zhang, Qizhi Jeffryes, James Faria, José P Edirisinghe, Janaka N Mundy, Michael Chia, Nicholas Noor, Elad Beber, Moritz E Best, Aaron A DeJongh, Matthew Kimbrel, Jeffrey A D’haeseleer, Patrik McCorkle, Sean R Bolton, Jay R Pearson, Erik Canon, Shane Wood-Charlson, Elisha M Cottingham, Robert W Arkin, Adam P Henry, Christopher S Nucleic Acids Res Database Issue For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase. Oxford University Press 2020-09-28 /pmc/articles/PMC7778927/ /pubmed/32986834 http://dx.doi.org/10.1093/nar/gkaa746 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Seaver, Samuel M D
Liu, Filipe
Zhang, Qizhi
Jeffryes, James
Faria, José P
Edirisinghe, Janaka N
Mundy, Michael
Chia, Nicholas
Noor, Elad
Beber, Moritz E
Best, Aaron A
DeJongh, Matthew
Kimbrel, Jeffrey A
D’haeseleer, Patrik
McCorkle, Sean R
Bolton, Jay R
Pearson, Erik
Canon, Shane
Wood-Charlson, Elisha M
Cottingham, Robert W
Arkin, Adam P
Henry, Christopher S
The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes
title The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes
title_full The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes
title_fullStr The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes
title_full_unstemmed The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes
title_short The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes
title_sort modelseed biochemistry database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778927/
https://www.ncbi.nlm.nih.gov/pubmed/32986834
http://dx.doi.org/10.1093/nar/gkaa746
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