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| 001 | 811790 | ||
| 005 | 20210129223929.0 | ||
| 024 | 7 | _ | |a 10.1016/j.jbiotec.2015.12.032 |2 doi |
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| 100 | 1 | _ | |a Dalman, Tolga |0 P:(DE-Juel1)129008 |b 0 |
| 245 | _ | _ | |a A scientific workflow framework for 13C metabolic flux analysis |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2016 |b Elsevier Science |
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| 520 | _ | _ | |a Metabolic flux analysis (MFA) with 13C labeling data is a high-precision technique to quantify intracellular reaction rates (fluxes). One of the major challenges of 13C 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 13C MFA workflows. 13C 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 13C MFA workflows can be solved with our approach on the basis of two proof-of-concept use cases. |
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| 700 | 1 | _ | |a Wiechert, Wolfgang |0 P:(DE-Juel1)129076 |b 1 |u fzj |
| 700 | 1 | _ | |a Nöh, Katharina |0 P:(DE-Juel1)129051 |b 2 |e Corresponding author |u fzj |
| 773 | _ | _ | |a 10.1016/j.jbiotec.2015.12.032 |g Vol. 232, p. 12 - 24 |0 PERI:(DE-600)2016476-2 |p 12 - 24 |t Journal of biotechnology |v 232 |y 2016 |x 0168-1656 |
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