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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.zeige mehrzeige weniger

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Metadaten
Verfasserangaben: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
Titel des übergeordneten Werks (Deutsch):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Untertitel (Englisch):automating metabolic flux analysis
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (1054)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:21.12.2020
Erscheinungsjahr:2012
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:21.12.2020
Freies Schlagwort / Tag:13C metabolic flux analysis; Bio-jETI; MFA; high-throughput analysis; scientific workflows; workflow management
Ausgabe:1054
Seitenanzahl:21
Erste Seite:872
Letzte Seite:890
Quelle:Metabolites 2 (2012) 4, 872-890 DOI: 10.3390/metabo2040872
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik und Computational Science
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer Review:Referiert
Publikationsweg:Open Access / Green Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
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