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PolyRound: polytope rounding for random sampling in metabolic networks

SUMMARY: Random flux sampling is a powerful tool for the constraint-based analysis of metabolic networks. The most efficient sampling method relies on a rounding transform of the constraint polytope, but no available rounding implementation can round all relevant models. By removing redundant polyto...

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Detalles Bibliográficos
Autores principales: Theorell, Axel, Jadebeck, Johann F, Nöh, Katharina, Stelling, Jörg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8723145/
https://www.ncbi.nlm.nih.gov/pubmed/34329395
http://dx.doi.org/10.1093/bioinformatics/btab552
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author Theorell, Axel
Jadebeck, Johann F
Nöh, Katharina
Stelling, Jörg
author_facet Theorell, Axel
Jadebeck, Johann F
Nöh, Katharina
Stelling, Jörg
author_sort Theorell, Axel
collection PubMed
description SUMMARY: Random flux sampling is a powerful tool for the constraint-based analysis of metabolic networks. The most efficient sampling method relies on a rounding transform of the constraint polytope, but no available rounding implementation can round all relevant models. By removing redundant polytope constraints on the go, PolyRound simplifies the numerical problem and rounds all the 108 models in the BiGG database without parameter tuning, compared to ∼50% for the state-of-the-art implementation. AVAILABILITY AND IMPLEMENTATION: The implementation is available on gitlab: https://gitlab.com/csb.ethz/PolyRound. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-87231452022-01-05 PolyRound: polytope rounding for random sampling in metabolic networks Theorell, Axel Jadebeck, Johann F Nöh, Katharina Stelling, Jörg Bioinformatics Applications Notes SUMMARY: Random flux sampling is a powerful tool for the constraint-based analysis of metabolic networks. The most efficient sampling method relies on a rounding transform of the constraint polytope, but no available rounding implementation can round all relevant models. By removing redundant polytope constraints on the go, PolyRound simplifies the numerical problem and rounds all the 108 models in the BiGG database without parameter tuning, compared to ∼50% for the state-of-the-art implementation. AVAILABILITY AND IMPLEMENTATION: The implementation is available on gitlab: https://gitlab.com/csb.ethz/PolyRound. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-07-30 /pmc/articles/PMC8723145/ /pubmed/34329395 http://dx.doi.org/10.1093/bioinformatics/btab552 Text en © The Author(s) 2021. 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 (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 Applications Notes
Theorell, Axel
Jadebeck, Johann F
Nöh, Katharina
Stelling, Jörg
PolyRound: polytope rounding for random sampling in metabolic networks
title PolyRound: polytope rounding for random sampling in metabolic networks
title_full PolyRound: polytope rounding for random sampling in metabolic networks
title_fullStr PolyRound: polytope rounding for random sampling in metabolic networks
title_full_unstemmed PolyRound: polytope rounding for random sampling in metabolic networks
title_short PolyRound: polytope rounding for random sampling in metabolic networks
title_sort polyround: polytope rounding for random sampling in metabolic networks
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8723145/
https://www.ncbi.nlm.nih.gov/pubmed/34329395
http://dx.doi.org/10.1093/bioinformatics/btab552
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