PyEnzyme is the interface to the data model EnzymeML and offers a convenient way to document and model research data. Lightweight syntax for rapid development of data management solution in enzymology and biocatalysis.
- Reproducible documentation of enzymatic and biocatalytic experiments.
- Import from and export to the SBML-based markup language EnzymeML and more.
- Perform database-specific validation prior to database upload.
- Model your data using a Thin Layer to popular modeling platforms.
- Visualize experimental results for inspection and publication.
Get started with PyEnzyme by running the following command
# Using PyPI
python -m pip install pyenzyme
Or build by source
git clone https://github.com/EnzymeML/PyEnzyme.git
cd PyEnzyme
python3 setup.py install
PyEnzyme comes with many flavors, choose whether you want only the base installation, the modeling package or all of it using the following options.
# COPASI - modeling
python -m pip install "pyenzyme[copasi]"
# PySCeS - modeling
python -m pip install "pyenzyme[pysces]"
# Modeling package
python -m pip install "pyenzyme[modeling]"
# REST API
python -m pip install "pyenzyme[rest]"
# Dataverse
python -m pip install "pyenzyme[dataverse]"
# Complete
python -m pip install "pyenzyme[all]"
This example will demonstrate how to create a simple EnzymeML document using PyEnzyme and how to use initializers from official databases Chebi and UniProt to gather metadata. For more examples, please visit our documentation (Work in progress)
# To be added for V2
(Code should run as it is)
Explore all the features of PyEnzyme in our documentation and take part in Discussions and/or Issues.
PyEnzyme
is free and open-source software licensed under the BSD 2-Clause License.