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Welcome to the EnzymeML GitHub!

This organization is home to various useful tools, libraries, and data models revolving around the data exchange format EnzymeML.

What is EnzymeML?

EnzymeML is a free, open XML-based format that adheres to the FAIR principles and serves as a standard for the systematic monitoring and exchange of data pertaining to enzyme-catalyzed reactions. Its primary objective is to facilitate the storage and transfer of enzyme kinetics data across electronic laboratory notebooks, software tools, and databases.

An EnzymeML document encompasses a comprehensive collection of data, including both the results of experimental measurements and the modeling outcomes. This may include time course data derived from a series of experiments with varying initial substrate concentrations, analyzed using the Michaelis-Menten model.

EnzymeML is compatible with the Systems Biology Markup Language (SBML) and continues to be developed and extended by an international community, with support from the STRENDA Commission.

📦 List of Repositories

In the following, you can find a list of repositories that are part of the EnzymeML project and its toolbox. We provide a brief description for each repository, but you can find more detailed information in the respective README files.

📚 Publications

The following publications provide more information about EnzymeML and its use cases.

🤝 EnzymeML Training Course

The EnzymeML Training course is a collaborative project with multiple experimental biocatalysis groups, jointly developing novel tools and standards for FAIR and reproducible data analysis of biocatalytic data.


  1. PyEnzyme PyEnzyme Public

    🧬 - Data management and modeling framework based on EnzymeML.

    Python 20 9

  2. Lauterbach_2022 Lauterbach_2022 Public

    📦 - Supporting information and notebooks to "EnzymeML: seamless data flow and modeling of enzymatic data"

    Jupyter Notebook 1 3


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