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multiTFA: a Python package for multi-variate thermodynamics-based flux analysis
MOTIVATION: We achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly r...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479682/ https://www.ncbi.nlm.nih.gov/pubmed/33682879 http://dx.doi.org/10.1093/bioinformatics/btab151 |
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author | Mahamkali, Vishnuvardhan McCubbin, Tim Beber, Moritz Emanuel Noor, Elad Marcellin, Esteban Nielsen, Lars Keld |
author_facet | Mahamkali, Vishnuvardhan McCubbin, Tim Beber, Moritz Emanuel Noor, Elad Marcellin, Esteban Nielsen, Lars Keld |
author_sort | Mahamkali, Vishnuvardhan |
collection | PubMed |
description | MOTIVATION: We achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly reduces the uncertainty of thermodynamic variables. RESULTS: We present multiTFA, a Python implementation of our framework. We evaluated our application using the core Escherichia coli model and achieved a median reduction of 6.8 kJ/mol in reaction Gibbs free energy ranges, while three out of 12 reactions in glycolysis changed from reversible to irreversible. AVAILABILITY AND IMPLEMENTATION: Our framework along with documentation is available on https://github.com/biosustain/multitfa. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8479682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84796822021-09-30 multiTFA: a Python package for multi-variate thermodynamics-based flux analysis Mahamkali, Vishnuvardhan McCubbin, Tim Beber, Moritz Emanuel Noor, Elad Marcellin, Esteban Nielsen, Lars Keld Bioinformatics Applications Notes MOTIVATION: We achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly reduces the uncertainty of thermodynamic variables. RESULTS: We present multiTFA, a Python implementation of our framework. We evaluated our application using the core Escherichia coli model and achieved a median reduction of 6.8 kJ/mol in reaction Gibbs free energy ranges, while three out of 12 reactions in glycolysis changed from reversible to irreversible. AVAILABILITY AND IMPLEMENTATION: Our framework along with documentation is available on https://github.com/biosustain/multitfa. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-03-03 /pmc/articles/PMC8479682/ /pubmed/33682879 http://dx.doi.org/10.1093/bioinformatics/btab151 Text en © The Author(s) 2021. Published by Oxford University Press. https://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 (https://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 | Applications Notes Mahamkali, Vishnuvardhan McCubbin, Tim Beber, Moritz Emanuel Noor, Elad Marcellin, Esteban Nielsen, Lars Keld multiTFA: a Python package for multi-variate thermodynamics-based flux analysis |
title | multiTFA: a Python package for multi-variate thermodynamics-based flux analysis |
title_full | multiTFA: a Python package for multi-variate thermodynamics-based flux analysis |
title_fullStr | multiTFA: a Python package for multi-variate thermodynamics-based flux analysis |
title_full_unstemmed | multiTFA: a Python package for multi-variate thermodynamics-based flux analysis |
title_short | multiTFA: a Python package for multi-variate thermodynamics-based flux analysis |
title_sort | multitfa: a python package for multi-variate thermodynamics-based flux analysis |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479682/ https://www.ncbi.nlm.nih.gov/pubmed/33682879 http://dx.doi.org/10.1093/bioinformatics/btab151 |
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