This title appears in the Scientific Report :
2012
Please use the identifier:
http://dx.doi.org/10.3390/metabo2041012 in citations.
Please use the identifier: http://hdl.handle.net/2128/4848 in citations.
Error Propagation Analysis for Quantitative Intracellular Metabolomics
Error Propagation Analysis for Quantitative Intracellular Metabolomics
Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The...
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Personal Name(s): | Tillack, Jana (Corresponding author) |
---|---|
Paczia, Nicole / Nöh, Katharina / Wiechert, Wolfgang / Noack, Stephan | |
Contributing Institute: |
Biotechnologie; IBG-1 |
Published in: | Metabolites, 2 (2012) 4, S. 1012 - 1030 |
Imprint: |
Basel
MDPI
2012
|
PubMed ID: |
24957773 |
DOI: |
10.3390/metabo2041012 |
Document Type: |
Journal Article |
Research Program: |
ohne Topic |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/4848 in citations.
Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The total measurement error of any analytical protocol is the result of an accumulation of single errors introduced by several processing steps. Here, we present a framework for the quantification of intracellular metabolites, including error propagation during metabolome sample processing. Focusing on one specific protocol, we comprehensively investigate all currently known and accessible factors that ultimately impact the accuracy of intracellular metabolite concentration data. All intermediate steps are modeled, and their uncertainty with respect to the final concentration data is rigorously quantified. Finally, on the basis of a comprehensive metabolome dataset of Corynebacterium glutamicum, an integrated error propagation analysis for all parts of the model is conducted, and the most critical steps for intracellular metabolite quantification are detected. |