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dc.contributor.authorRange, Jan-
dc.contributor.authorHalupczok, Colin-
dc.contributor.authorLohmann, Jens-
dc.contributor.authorSwainston, Neil-
dc.contributor.authorKettner, Carsten-
dc.contributor.authorBergmann, Frank T.-
dc.contributor.authorWeidemann, Andreas-
dc.contributor.authorWittig, Ulrike-
dc.contributor.authorSchnell, Santiago-
dc.contributor.authorPleiss, Jürgen-
dc.date.accessioned2024-08-24T11:31:29Z-
dc.date.available2024-08-24T11:31:29Z-
dc.date.issued2021de
dc.identifier.issn1432-1033-
dc.identifier.issn0014-2956-
dc.identifier.other1900823659-
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-148860de
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/14886-
dc.identifier.urihttp://dx.doi.org/10.18419/opus-14867-
dc.description.abstractEnzymeML 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.en
dc.description.sponsorshipDeutsche Forschungsgemeinschaftde
dc.description.sponsorshipBiotechnology and Biological Sciences Research Councilde
dc.description.sponsorshipGerman Federal Ministry of Education and Researchde
dc.description.sponsorshipUniversity of Liverpoolde
dc.description.sponsorshipKlaus Tschira Foundationde
dc.description.sponsorshipProjekt DEALde
dc.language.isoende
dc.relation.uridoi:10.1111/febs.16318de
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/de
dc.subject.ddc004de
dc.subject.ddc570de
dc.titleEnzymeML : a data exchange format for biocatalysis and enzymologyen
dc.typearticlede
dc.date.updated2023-11-14T00:09:31Z-
ubs.fakultaetChemiede
ubs.fakultaetFakultätsübergreifend / Sonstige Einrichtungde
ubs.institutInstitut für Biochemie und Technische Biochemiede
ubs.institutFakultätsübergreifend / Sonstige Einrichtungde
ubs.publikation.seiten5864-5874de
ubs.publikation.sourceThe FEBS journal 289 (2022), S. 5864-5874de
ubs.publikation.typZeitschriftenartikelde
Enthalten in den Sammlungen:03 Fakultät Chemie

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