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EnzymeML—a data exchange format for biocatalysis and enzymology
Author(s) -
Range Jan,
Halupczok Colin,
Lohmann Jens,
Swainston Neil,
Kettner Carsten,
Bergmann Frank T.,
Weidemann Andreas,
Wittig Ulrike,
Schnell Santiago,
Pleiss Jürgen
Publication year - 2022
Publication title -
the febs journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 204
eISSN - 1742-4658
pISSN - 1742-464X
DOI - 10.1111/febs.16318
Subject(s) - computer science , data exchange , xml , python (programming language) , interoperability , documentation , database , upload , sbml , scripting language , application programming interface , software , markup language , information retrieval , data mining , programming language , world wide web
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.