001002265 001__ 1002265 001002265 005__ 20230929112514.0 001002265 0247_ $$2doi$$a10.1038/s41592-022-01763-1 001002265 0247_ $$2ISSN$$a1548-7091 001002265 0247_ $$2ISSN$$a1548-7105 001002265 0247_ $$2pmid$$a36759590 001002265 0247_ $$2WOS$$aWOS:000931967700001 001002265 037__ $$aFZJ-2023-01247 001002265 082__ $$a610 001002265 1001_ $$0P:(DE-HGF)0$$aLauterbach, Simone$$b0 001002265 245__ $$aEnzymeML: seamless data flow and modeling of enzymatic data 001002265 260__ $$aLondon [u.a.]$$bNature Publishing Group$$c2023 001002265 3367_ $$2DRIVER$$aarticle 001002265 3367_ $$2DataCite$$aOutput Types/Journal article 001002265 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1692271354_31794 001002265 3367_ $$2BibTeX$$aARTICLE 001002265 3367_ $$2ORCID$$aJOURNAL_ARTICLE 001002265 3367_ $$00$$2EndNote$$aJournal Article 001002265 520__ $$aThe design of biocatalytic reaction systems is highly complex owing to the dependency of the estimated kinetic parameters on the enzyme, the reaction conditions, and the modeling method. Consequently, reproducibility of enzymatic experiments and reusability of enzymatic data are challenging. We developed the XML-based markup language EnzymeML to enable storage and exchange of enzymatic data such as reaction conditions, the time course of the substrate and the product, kinetic parameters and the kinetic model, thus making enzymatic data findable, accessible, interoperable and reusable (FAIR). The feasibility and usefulness of the EnzymeML toolbox is demonstrated in six scenarios, for which data and metadata of different enzymatic reactions are collected and analyzed. EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling of enzyme kinetics, publication platforms and enzymatic reaction databases. EnzymeML is open and transparent, and invites the community to contribute. 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