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Isolating structural errors in reaction networks in systems biology
MOTIVATION: The growing complexity of reaction-based models necessitates early detection and resolution of model errors. Considerable work has been done on the detection of mass balance errors, especially atomic mass analysis (AMA) (which compares the counts of atoms in the reactants and products) a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058775/ https://www.ncbi.nlm.nih.gov/pubmed/32790862 http://dx.doi.org/10.1093/bioinformatics/btaa720 |
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author | Shin, Woosub Hellerstein, Joseph L |
author_facet | Shin, Woosub Hellerstein, Joseph L |
author_sort | Shin, Woosub |
collection | PubMed |
description | MOTIVATION: The growing complexity of reaction-based models necessitates early detection and resolution of model errors. Considerable work has been done on the detection of mass balance errors, especially atomic mass analysis (AMA) (which compares the counts of atoms in the reactants and products) and Linear Programming analysis (which detects stoichiometric inconsistencies). This article extends model error checking to include: (i) certain structural errors in reaction networks and (ii) error isolation. First, we consider the balance of chemical structures (moieties) between reactants and products. This balance is expected in many biochemical reactions, but the imbalance of chemical structures cannot be detected if the analysis is done in units of atomic masses. Second, we improve on error isolation for stoichiometric inconsistencies by identifying a small number of reactions and/or species that cause the error. Doing so simplifies error remediation. RESULTS: We propose two algorithms that address isolating structural errors in reaction networks. Moiety analysis finds imbalances of moieties using the same algorithm as AMA, but moiety analysis works in units of moieties instead of atomic masses. We argue for the value of checking moiety balance, and discuss two approaches to decomposing chemical species into moieties. Graphical Analysis of Mass Equivalence Sets (GAMES) provides isolation for stoichiometric inconsistencies by constructing explanations that relate errors in the structure of the reaction network to elements of the reaction network. We study the effectiveness of moiety analysis and GAMES on curated models in the BioModels repository. We have created open source codes for moiety analysis and GAMES. AVAILABILITY AND IMPLEMENTATION: Our project is hosted at https://github.com/ModelEngineering/SBMLLint, which contains examples, documentation, source code files and build scripts used to create SBMLLint. Our source code is licensed under the MIT open source license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8058775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-80587752021-04-28 Isolating structural errors in reaction networks in systems biology Shin, Woosub Hellerstein, Joseph L Bioinformatics Original Papers MOTIVATION: The growing complexity of reaction-based models necessitates early detection and resolution of model errors. Considerable work has been done on the detection of mass balance errors, especially atomic mass analysis (AMA) (which compares the counts of atoms in the reactants and products) and Linear Programming analysis (which detects stoichiometric inconsistencies). This article extends model error checking to include: (i) certain structural errors in reaction networks and (ii) error isolation. First, we consider the balance of chemical structures (moieties) between reactants and products. This balance is expected in many biochemical reactions, but the imbalance of chemical structures cannot be detected if the analysis is done in units of atomic masses. Second, we improve on error isolation for stoichiometric inconsistencies by identifying a small number of reactions and/or species that cause the error. Doing so simplifies error remediation. RESULTS: We propose two algorithms that address isolating structural errors in reaction networks. Moiety analysis finds imbalances of moieties using the same algorithm as AMA, but moiety analysis works in units of moieties instead of atomic masses. We argue for the value of checking moiety balance, and discuss two approaches to decomposing chemical species into moieties. Graphical Analysis of Mass Equivalence Sets (GAMES) provides isolation for stoichiometric inconsistencies by constructing explanations that relate errors in the structure of the reaction network to elements of the reaction network. We study the effectiveness of moiety analysis and GAMES on curated models in the BioModels repository. We have created open source codes for moiety analysis and GAMES. AVAILABILITY AND IMPLEMENTATION: Our project is hosted at https://github.com/ModelEngineering/SBMLLint, which contains examples, documentation, source code files and build scripts used to create SBMLLint. Our source code is licensed under the MIT open source license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-07-13 /pmc/articles/PMC8058775/ /pubmed/32790862 http://dx.doi.org/10.1093/bioinformatics/btaa720 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Shin, Woosub Hellerstein, Joseph L Isolating structural errors in reaction networks in systems biology |
title | Isolating structural errors in reaction networks in systems biology |
title_full | Isolating structural errors in reaction networks in systems biology |
title_fullStr | Isolating structural errors in reaction networks in systems biology |
title_full_unstemmed | Isolating structural errors in reaction networks in systems biology |
title_short | Isolating structural errors in reaction networks in systems biology |
title_sort | isolating structural errors in reaction networks in systems biology |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058775/ https://www.ncbi.nlm.nih.gov/pubmed/32790862 http://dx.doi.org/10.1093/bioinformatics/btaa720 |
work_keys_str_mv | AT shinwoosub isolatingstructuralerrorsinreactionnetworksinsystemsbiology AT hellersteinjosephl isolatingstructuralerrorsinreactionnetworksinsystemsbiology |