Literature DB >> 26721184

A scientific workflow framework for (13)C metabolic flux analysis.

Tolga Dalman1, Wolfgang Wiechert1, Katharina Nöh2.   

Abstract

Metabolic flux analysis (MFA) with (13)C labeling data is a high-precision technique to quantify intracellular reaction rates (fluxes). One of the major challenges of (13)C MFA is the interactivity of the computational workflow according to which the fluxes are determined from the input data (metabolic network model, labeling data, and physiological rates). Here, the workflow assembly is inevitably determined by the scientist who has to consider interacting biological, experimental, and computational aspects. Decision-making is context dependent and requires expertise, rendering an automated evaluation process hardly possible. Here, we present a scientific workflow framework (SWF) for creating, executing, and controlling on demand (13)C MFA workflows. (13)C MFA-specific tools and libraries, such as the high-performance simulation toolbox 13CFLUX2, are wrapped as web services and thereby integrated into a service-oriented architecture. Besides workflow steering, the SWF features transparent provenance collection and enables full flexibility for ad hoc scripting solutions. To handle compute-intensive tasks, cloud computing is supported. We demonstrate how the challenges posed by (13)C MFA workflows can be solved with our approach on the basis of two proof-of-concept use cases.
Copyright © 2015 Elsevier B.V. All rights reserved.

Keywords:  (13)C metabolic flux analysis; 13CFLUX2; Cloud computing; Scientific workflows; Service-oriented architecture; Web services

Mesh:

Substances:

Year:  2015        PMID: 26721184     DOI: 10.1016/j.jbiotec.2015.12.032

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  4 in total

1.  Metabolic flux analysis of the neural cell glycocalyx reveals differential utilization of monosaccharides.

Authors:  Maurice Wong; Gege Xu; Mariana Barboza; Izumi Maezawa; Lee-Way Jin; Angela Zivkovic; Carlito B Lebrilla
Journal:  Glycobiology       Date:  2020-10-21       Impact factor: 4.313

Review 2.  Towards an Understanding of Energy Impairment in Huntington's Disease Brain.

Authors:  Janet M Dubinsky
Journal:  J Huntingtons Dis       Date:  2017

3.  The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis.

Authors:  Martin Beyß; Salah Azzouzi; Michael Weitzel; Wolfgang Wiechert; Katharina Nöh
Journal:  Front Microbiol       Date:  2019-05-24       Impact factor: 5.640

4.  Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors.

Authors:  Nicolas Sundqvist; Nina Grankvist; Jeramie Watrous; Jain Mohit; Roland Nilsson; Gunnar Cedersund
Journal:  PLoS Comput Biol       Date:  2022-04-11       Impact factor: 4.779

  4 in total

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