Project description
The goal of research project PN 2-6 is to establish a data management environment for biocatalytic data which
- enables data acquisition and documentation according to FAIR data principles,
- provides a searchable data repository for structured data, that can be searched by standardized metadata,
- enables workflow solutions for a seamless data transfer between experiment, modelling platforms, and databases with minimal human intervention.
The core of the project is the development of EnzymeML as a standardized exchange format for biocatalytic data.
Project information
Project title |
Seamlesss data flow by EnzymeML, an SBML-based exchange format for the integration of enzymatic reaction data |
Project leader | Jürgen Pleiss |
Project partners | Nicole Radde (PN2-9) Tobias Siebert, Oliver Röhrle (PN2-8) |
Project duration | February 2021 - July 2021 |
Project number | PN 2-6 |
- Follow-up project 2-6 (II)
Software-driven RDM (sdRDM), a generic and extensible bottom-up research data management concept and its application in biocatalysis and beyond
Publications PN 2-6 and PN 2-6 (II)
2025
- T. Giess and J. Pleiss, “Digitalization of biocatalysis: Best practices to research data management,” in Methods in Enzymology. , Academic Press, 2025. doi: https://doi.org/10.1016/bs.mie.2025.01.040.
- M. B. M. Spera, S. Darouich, J. Pleiss, and N. Hansen, “Influence of water content on thermophysical properties of aqueous glyceline solutions predicted by molecular dynamics simulations,” Fluid Phase Equilibria, vol. 592, p. 114324, 2025, doi: https://doi.org/10.1016/j.fluid.2024.114324.
2024
- H. F. Carvalho, L. Mestrom, U. Hanefeld, and J. Pleiss, “Beyond the Chemical Step: The Role of Substrate Access in Acyltransferase from Mycobacterium smegmatis,” ACS Catal., vol. 14, pp. 10077–10088, Jun. 2024, doi: 10.1021/acscatal.4c00812.
- F. Neubauer, P. Bredl, M. Xu, K. Patel, J. Pleiss, and B. Uekermann, “MetaConfigurator: A User-Friendly Tool for Editing Structured Data Files,” Datenbank-Spektrum, vol. 24, pp. 161–169, 2024, doi: 10.1007/s13222-024-00472-7.
- A. Windels, J. Franceus, J. Pleiss, and T. Desmet, “CANDy: Automated analysis of domain architectures in carbohydrate-active enzymes,” PLOS ONE, vol. 19, Art. no. 7, Jul. 2024, doi: 10.1371/journal.pone.0306410.
- J. Pleiss, “FAIR Data and Software: Improving Efficiency and Quality of Biocatalytic Science,” ACS Catal., vol. 14, Art. no. 4, Feb. 2024, doi: 10.1021/acscatal.3c06337.
- S. Malzacher et al., “The STRENDA Biocatalysis Guidelines for cataloguing metadata,” Nature Catalysis, vol. 7, Art. no. 12, 2024, doi: 10.1038/s41929-024-01261-x.
- J. Pleiss, “Modeling Enzyme Kinetics: Current Challenges and Future Perspectives for Biocatalysis,” Biochemistry, vol. 63, Art. no. 20, Sep. 2024, doi: 10.1021/acs.biochem.4c00501.
- B. Flemisch et al., “Research Data Management in Simulation Science: Infrastructure, Tools, and Applications,” Datenbank-Spektrum, 2024, doi: https://doi.org/10.1007/s13222-024-00475-4.
2023
- S. Lauterbach et al., “EnzymeML: seamless data flow and modeling of enzymatic data,” Nature Methods, vol. 20, Art. no. 3, 2023, doi: 10.1038/s41592-022-01763-1.
- T. Giess, S. Itzigehl, J. Range, R. Schömig, J. R. Bruckner, and J. Pleiss, “FAIR and scalable management of small-angle X-ray scattering data,” Journal of Applied Crystallography, vol. 56, Art. no. 2, Apr. 2023, doi: 10.1107/S1600576723001577.
- S. Höpfl, J. Pleiss, and N. E. Radde, “Bayesian estimation reveals that reproducible models in Systems Biology get more citations,” Scientific reports, vol. 13, p. 2695, 2023, doi: 10.1038/s41598-023-29340-2.
2022
- A. Mack et al., “Preferential Self-interaction of DNA Methyltransferase DNMT3A Subunits Containing the R882H Cancer Mutation Leads to Dominant Changes of Flanking Sequence Preferences,” Journal of Molecular Biology, vol. 434, Art. no. 7, 2022, doi: 10.1016/j.jmb.2022.167482.
- J. Range et al., “EnzymeML—a data exchange format for biocatalysis and enzymology,” The FEBS Journal, vol. 289, Art. no. 19, Oct. 2022, doi: https://doi.org/10.1111/febs.16318.
2021
- J. Pleiss, “Standardized data, scalable documentation, sustainable storage – EnzymeML as a basis for FAIR data management in biocatalysis,” ChemCatChem, vol. 13, pp. 3909–3913, 2021, doi: https://doi.org/10.1002/cctc.202100822.