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MC(3): a steady-state model and constraint consistency checker for biochemical networks

BACKGROUND: Stoichiometric models provide a structural framework for analyzing steady-state cellular behavior. Models are developed either through augmentations of existing models or more recently through automatic reconstruction tools. There is currently no standardized practice or method for valid...

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Autores principales: Yousofshahi, Mona, Ullah, Ehsan, Stern, Russell, Hassoun, Soha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4222687/
https://www.ncbi.nlm.nih.gov/pubmed/24261865
http://dx.doi.org/10.1186/1752-0509-7-129
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author Yousofshahi, Mona
Ullah, Ehsan
Stern, Russell
Hassoun, Soha
author_facet Yousofshahi, Mona
Ullah, Ehsan
Stern, Russell
Hassoun, Soha
author_sort Yousofshahi, Mona
collection PubMed
description BACKGROUND: Stoichiometric models provide a structural framework for analyzing steady-state cellular behavior. Models are developed either through augmentations of existing models or more recently through automatic reconstruction tools. There is currently no standardized practice or method for validating the properties of a model before placing it in the public domain. Considerable effort is often required to understand a model’s inconsistencies before its reuse within new research efforts. RESULTS: We present a review of common issues in stoichiometric models typically uncovered during pathway analysis and constraint-based optimization, and we detail succinct and efficient ways to find them. We present MC(3), Model and Constraint Consistency Checker, a computational tool that can be used for two purposes: (a) identifying potential connectivity and topological issues for a given stoichiometric matrix, S, and (b) flagging issues that arise during constraint-based optimization. The MC(3) tool includes three distinct checking components. The first examines the results of computing the basis for the null space for Sv = 0; the second uses connectivity analysis; and the third utilizes Flux Variability Analysis. MC(3) takes as input a stoichiometric matrix and flux constraints, and generates a report summarizing issues. CONCLUSIONS: We report the results of applying MC(3) to published models for several systems including Escherichia coli, an adipocyte cell, a Chinese Hamster Ovary cell, and Leishmania major. Several issues with no prior documentation are identified. MC(3) provides a standalone MATLAB-based comprehensive tool for model validation, a task currently performed either ad hoc or implemented in part within other computational tools.
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spelling pubmed-42226872014-11-10 MC(3): a steady-state model and constraint consistency checker for biochemical networks Yousofshahi, Mona Ullah, Ehsan Stern, Russell Hassoun, Soha BMC Syst Biol Methodology Article BACKGROUND: Stoichiometric models provide a structural framework for analyzing steady-state cellular behavior. Models are developed either through augmentations of existing models or more recently through automatic reconstruction tools. There is currently no standardized practice or method for validating the properties of a model before placing it in the public domain. Considerable effort is often required to understand a model’s inconsistencies before its reuse within new research efforts. RESULTS: We present a review of common issues in stoichiometric models typically uncovered during pathway analysis and constraint-based optimization, and we detail succinct and efficient ways to find them. We present MC(3), Model and Constraint Consistency Checker, a computational tool that can be used for two purposes: (a) identifying potential connectivity and topological issues for a given stoichiometric matrix, S, and (b) flagging issues that arise during constraint-based optimization. The MC(3) tool includes three distinct checking components. The first examines the results of computing the basis for the null space for Sv = 0; the second uses connectivity analysis; and the third utilizes Flux Variability Analysis. MC(3) takes as input a stoichiometric matrix and flux constraints, and generates a report summarizing issues. CONCLUSIONS: We report the results of applying MC(3) to published models for several systems including Escherichia coli, an adipocyte cell, a Chinese Hamster Ovary cell, and Leishmania major. Several issues with no prior documentation are identified. MC(3) provides a standalone MATLAB-based comprehensive tool for model validation, a task currently performed either ad hoc or implemented in part within other computational tools. BioMed Central 2013-11-21 /pmc/articles/PMC4222687/ /pubmed/24261865 http://dx.doi.org/10.1186/1752-0509-7-129 Text en Copyright © 2013 Yousofshahi et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Yousofshahi, Mona
Ullah, Ehsan
Stern, Russell
Hassoun, Soha
MC(3): a steady-state model and constraint consistency checker for biochemical networks
title MC(3): a steady-state model and constraint consistency checker for biochemical networks
title_full MC(3): a steady-state model and constraint consistency checker for biochemical networks
title_fullStr MC(3): a steady-state model and constraint consistency checker for biochemical networks
title_full_unstemmed MC(3): a steady-state model and constraint consistency checker for biochemical networks
title_short MC(3): a steady-state model and constraint consistency checker for biochemical networks
title_sort mc(3): a steady-state model and constraint consistency checker for biochemical networks
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4222687/
https://www.ncbi.nlm.nih.gov/pubmed/24261865
http://dx.doi.org/10.1186/1752-0509-7-129
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