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Flux-P: Automating Metabolic Flux Analysis
Quantitative knowledge of intracellular fluxes in metabolic networks is invaluable for inferring metabolic system behavior and the design principles of biological systems. However, intracellular reaction rates can not often be calculated directly but have to be estimated; for instance, via (13)C-bas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901227/ https://www.ncbi.nlm.nih.gov/pubmed/24957766 http://dx.doi.org/10.3390/metabo2040872 |
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author | Ebert, Birgitta E. Lamprecht, Anna-Lena Steffen, Bernhard Blank, Lars M. |
author_facet | Ebert, Birgitta E. Lamprecht, Anna-Lena Steffen, Bernhard Blank, Lars M. |
author_sort | Ebert, Birgitta E. |
collection | PubMed |
description | Quantitative knowledge of intracellular fluxes in metabolic networks is invaluable for inferring metabolic system behavior and the design principles of biological systems. However, intracellular reaction rates can not often be calculated directly but have to be estimated; for instance, via (13)C-based metabolic flux analysis, a model-based interpretation of stable carbon isotope patterns in intermediates of metabolism. Existing software such as FiatFlux, OpenFLUX or 13CFLUX supports experts in this complex analysis, but requires several steps that have to be carried out manually, hence restricting the use of this software for data interpretation to a rather small number of experiments. In this paper, we present Flux-P as an approach to automate and standardize (13)C-based metabolic flux analysis, using the Bio-jETI workflow framework. Exemplarily based on the FiatFlux software, it demonstrates how services can be created that carry out the different analysis steps autonomously and how these can subsequently be assembled into software workflows that perform automated, high-throughput intracellular flux analysis of high quality and reproducibility. Besides significant acceleration and standardization of the data analysis, the agile workflow-based realization supports flexible changes of the analysis workflows on the user level, making it easy to perform custom analyses. |
format | Online Article Text |
id | pubmed-3901227 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-39012272014-05-27 Flux-P: Automating Metabolic Flux Analysis Ebert, Birgitta E. Lamprecht, Anna-Lena Steffen, Bernhard Blank, Lars M. Metabolites Article Quantitative knowledge of intracellular fluxes in metabolic networks is invaluable for inferring metabolic system behavior and the design principles of biological systems. However, intracellular reaction rates can not often be calculated directly but have to be estimated; for instance, via (13)C-based metabolic flux analysis, a model-based interpretation of stable carbon isotope patterns in intermediates of metabolism. Existing software such as FiatFlux, OpenFLUX or 13CFLUX supports experts in this complex analysis, but requires several steps that have to be carried out manually, hence restricting the use of this software for data interpretation to a rather small number of experiments. In this paper, we present Flux-P as an approach to automate and standardize (13)C-based metabolic flux analysis, using the Bio-jETI workflow framework. Exemplarily based on the FiatFlux software, it demonstrates how services can be created that carry out the different analysis steps autonomously and how these can subsequently be assembled into software workflows that perform automated, high-throughput intracellular flux analysis of high quality and reproducibility. Besides significant acceleration and standardization of the data analysis, the agile workflow-based realization supports flexible changes of the analysis workflows on the user level, making it easy to perform custom analyses. MDPI 2012-11-12 /pmc/articles/PMC3901227/ /pubmed/24957766 http://dx.doi.org/10.3390/metabo2040872 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0/ This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Ebert, Birgitta E. Lamprecht, Anna-Lena Steffen, Bernhard Blank, Lars M. Flux-P: Automating Metabolic Flux Analysis |
title | Flux-P: Automating Metabolic Flux Analysis |
title_full | Flux-P: Automating Metabolic Flux Analysis |
title_fullStr | Flux-P: Automating Metabolic Flux Analysis |
title_full_unstemmed | Flux-P: Automating Metabolic Flux Analysis |
title_short | Flux-P: Automating Metabolic Flux Analysis |
title_sort | flux-p: automating metabolic flux analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901227/ https://www.ncbi.nlm.nih.gov/pubmed/24957766 http://dx.doi.org/10.3390/metabo2040872 |
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