Publications by authors named "Jan Range"
A modular research data management toolbox based on the programming language Python, the widely used computing platform , the standardized data exchange format for analytical data (AnIML) and the generic repository Dataverse has been established and applied to analyze small-angle X-ray scattering (SAXS) data according to the FAIR data principles (findable, accessible, interoperable and reusable). The library is a community-driven effort to develop tools for data acquisition, analysis, visualization and publishing of SAXS data. Metadata from the experiment and the results of data analysis are stored as an AnIML document using the novel Python-native API.
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- * To address these challenges, EnzymeML is an XML-based markup language designed to standardize storage and sharing of enzymatic data, enhancing its findability and accessibility (the FAIR principles).
- * The EnzymeML toolbox has been tested in six scenarios, demonstrating its effectiveness in facilitating communication between various platforms and promoting collaboration within the scientific community, with all resources freely available online.
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.
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