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Flux-P

  • 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 13C-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 13C-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 softwareQuantitative 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 13C-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 13C-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.show moreshow less

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Metadaten
Author details:Birgitta E. EbertORCiDGND, Anna-Lena LamprechtORCiDGND, Bernhard SteffenORCiDGND, Lars M. BlankORCiDGND
URN:urn:nbn:de:kobv:517-opus4-476696
DOI:https://doi.org/10.25932/publishup-47669
ISSN:1866-8372
Title of parent work (German):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Subtitle (English):automating metabolic flux analysis
Publication series (Volume number):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (1054)
Publication type:Postprint
Language:English
Date of first publication:2020/12/21
Publication year:2012
Publishing institution:Universität Potsdam
Release date:2020/12/21
Tag:13C metabolic flux analysis; Bio-jETI; MFA; high-throughput analysis; scientific workflows; workflow management
Issue:1054
Number of pages:21
First page:872
Last Page:890
Source:Metabolites 2 (2012) 4, 872-890 DOI: 10.3390/metabo2040872
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik und Computational Science
DDC classification:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer review:Referiert
Publishing method:Open Access / Green Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
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