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Double and multiple knockout simulations for genome-scale metabolic network reconstructions

BACKGROUND: Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network. RESULTS: We...

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Detalles Bibliográficos
Autores principales: Goldstein, Yaron AB, Bockmayr, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302510/
https://www.ncbi.nlm.nih.gov/pubmed/25649004
http://dx.doi.org/10.1186/s13015-014-0028-y
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author Goldstein, Yaron AB
Bockmayr, Alexander
author_facet Goldstein, Yaron AB
Bockmayr, Alexander
author_sort Goldstein, Yaron AB
collection PubMed
description BACKGROUND: Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network. RESULTS: We present an extension of flux coupling analysis for double and multiple gene or reaction knockouts, and develop corresponding algorithms for an in silico simulation. To evaluate our method, we perform a full single and double knockout analysis on a selection of genome-scale metabolic network reconstructions and compare the results. SOFTWARE: A prototype implementation of double knockout simulation is available at http://hoverboard.io/L4FC.
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spelling pubmed-43025102015-02-03 Double and multiple knockout simulations for genome-scale metabolic network reconstructions Goldstein, Yaron AB Bockmayr, Alexander Algorithms Mol Biol Research BACKGROUND: Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network. RESULTS: We present an extension of flux coupling analysis for double and multiple gene or reaction knockouts, and develop corresponding algorithms for an in silico simulation. To evaluate our method, we perform a full single and double knockout analysis on a selection of genome-scale metabolic network reconstructions and compare the results. SOFTWARE: A prototype implementation of double knockout simulation is available at http://hoverboard.io/L4FC. BioMed Central 2015-01-09 /pmc/articles/PMC4302510/ /pubmed/25649004 http://dx.doi.org/10.1186/s13015-014-0028-y Text en © Goldstein and Bockmayr; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Goldstein, Yaron AB
Bockmayr, Alexander
Double and multiple knockout simulations for genome-scale metabolic network reconstructions
title Double and multiple knockout simulations for genome-scale metabolic network reconstructions
title_full Double and multiple knockout simulations for genome-scale metabolic network reconstructions
title_fullStr Double and multiple knockout simulations for genome-scale metabolic network reconstructions
title_full_unstemmed Double and multiple knockout simulations for genome-scale metabolic network reconstructions
title_short Double and multiple knockout simulations for genome-scale metabolic network reconstructions
title_sort double and multiple knockout simulations for genome-scale metabolic network reconstructions
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302510/
https://www.ncbi.nlm.nih.gov/pubmed/25649004
http://dx.doi.org/10.1186/s13015-014-0028-y
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