Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-14867
Authors: Range, Jan
Halupczok, Colin
Lohmann, Jens
Swainston, Neil
Kettner, Carsten
Bergmann, Frank T.
Weidemann, Andreas
Wittig, Ulrike
Schnell, Santiago
Pleiss, Jürgen
Title: EnzymeML : a data exchange format for biocatalysis and enzymology
Issue Date: 2021
metadata.ubs.publikation.typ: Zeitschriftenartikel
metadata.ubs.publikation.seiten: 5864-5874
metadata.ubs.publikation.source: The FEBS journal 289 (2022), S. 5864-5874
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-148860
http://elib.uni-stuttgart.de/handle/11682/14886
http://dx.doi.org/10.18419/opus-14867
ISSN: 1432-1033
0014-2956
Abstract: EnzymeML is an XML‐based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO‐RK.
Appears in Collections:03 Fakultät Chemie

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