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Using genome-scale metabolic networks for analysis, visualization, and integration of targeted metabolomics data.
In: Computational Methods and Data Analysis for Metabolomics. Berlin [u.a.]: Springer, 2020. 361-386 (Methods Mol. Biol. ; 2104)
Interpretation of metabolomics data in the context of biological pathways is important to gain knowledge about underlying metabolic processes. In this chapter we present methods to analyze genome-scale models (GSMs) and metabolomics data together. This includes reading and mining of GSMs using the SBTab format to retrieve information on genes, reactions, and metabolites. Furthermore, the chapter showcases the generation of metabolic pathway maps using the Escher tool, which can be used for data visualization. Lastly, approaches to constrain flux balance analysis (FBA) by metabolomics data are presented.
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Publication type
Article: Edited volume or book chapter
Keywords
Analysis ; Integration ; Metabolic Networks ; Metabolomics ; Visualization
Language
english
Publication Year
2020
HGF-reported in Year
2020
ISSN (print) / ISBN
1064-3745
e-ISSN
1940-6029
Book Volume Title
Computational Methods and Data Analysis for Metabolomics
Journal
Methods in Molecular Biology
Quellenangaben
Volume: 2104,
Pages: 361-386
Publisher
Springer
Publishing Place
Berlin [u.a.]
Reviewing status
Peer reviewed
Institute(s)
Research Unit BioGeoChemistry and Analytics (BGC)
POF-Topic(s)
30202 - Environmental Health
Research field(s)
Environmental Sciences
PSP Element(s)
G-504800-001
Scopus ID
85078038019
PubMed ID
31953826
Erfassungsdatum
2020-03-11