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EnzymeML: seamless data flow and modeling of enzymatic data

Published:2023-02-09 Issue:3 Volume:20 Page:400-402
ISSN:1548-7091
Container-title:Nature Methods
language:en
Short-container-title:Nat Methods

Author:

Lauterbach Simone,Dienhart Hannah,Range Jan,Malzacher Stephan,Spöring Jan-Dirk^ORCID,Rother Dörte,Pinto Maria Filipa^ORCID,Martins Pedro,Lagerman Colton E.,Bommarius Andreas S.^ORCID,Høst Amalie Vang,Woodley John M.^ORCID,Ngubane Sandile^ORCID,Kudanga Tukayi^ORCID,Bergmann Frank T.^ORCID,Rohwer Johann M.^ORCID,Iglezakis Dorothea^ORCID,Weidemann Andreas,Wittig Ulrike^ORCID,Kettner Carsten^ORCID,Swainston Neil,Schnell Santiago^ORCID,Pleiss Jürgen^ORCID

Funder

Deutsche Forschungsgemeinschaft

German Federal Ministry of Education and Research

U.S. Department of Health & Human Services | U.S. Food and Drug Administration

National Science Foundation

Danmarks Tekniske Universitet

National Research Foundation of South Africa

Publisher

Springer Science and Business Media LLC

Subject

Cell Biology,Molecular Biology,Biochemistry,Biotechnology

Link

https://www.nature.com/articles/s41592-022-01763-1.pdf

Reference28 articles.

1. Iqbal, S. A., Wallach, J. D., Khoury, M. J., Schully, S. D. & Ioannidis, J. P. A. Reproducible research practices and transparency across the biomedical literature. PLoS Biol. 14, e1002333 (2016).

2. Wulf, C. et al. A unified research data infrastructure for catalysis research—challenges and concepts. ChemCatChem 13, 3223–3236 (2021).

3. Halling, P. et al. An empirical analysis of enzyme function reporting for experimental reproducibility: missing/incomplete information in published papers. Biophys. Chem. 242, 22–27 (2018).

4. Stroberg, W. & Schnell, S. On the estimation errors of KM and V from time-course experiments using the Michaelis–Menten equation. Biophys. Chem. 219, 17–27 (2016).

5. Cvijovic, M. et al. Bridging the gaps in systems biology. Mol. Genet. Genomics 289, 727–734 (2014).

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1. Research Data Management in Simulation Science: Infrastructure, Tools, and Applications;Datenbank-Spektrum;2024-06-04

2. Fluent Integration of Laboratory Data into Biocatalytic Process Simulation Using EnzymeML, DWSIM, and Ontologies;Processes;2024-03-16

3. FAIR Data and Software: Improving Efficiency and Quality of Biocatalytic Science;ACS Catalysis;2024-02-07

4. Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering;ACS Central Science;2024-02-05

5. On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering;Faraday Discussions;2024

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