[](https://codecov.io/gh/ModelEngineering/SBMLKinetics)
# SBMLKinetics
SBMLKinetics is a Python package to evaluate and classify kinetics in SBML models.
There are many possible kinetics like the zeroth order, mass action, Michaelis-Menten,
Hill kinetics and others. This work characterizes the kinetics in the BioModels
Database as an example to improve modeling best practices. Our tool can analyze any data sets
with SBML files as input. Users can also use this tool to compare different data sets. For
instance, we compare the distribution of kinetics for the signaling and metabolic networks and
find the substantial differences between two types of networks.
## Citing
If you are using any of the
code, please cite the article (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05380-3) and the PYPI web page (https://pypi.org/project/SBMLKinetics/).
## For users
### Installation
``pip install SBMLKinetics``
## A Classification Example
Here is a classification example generated by SBMLKinetics:
<img src="https://raw.githubusercontent.com/SunnyXu/SBMLKinetics/master/docs/Figures/Fig1_curated.png" width="450" height="350">
Please see more examples in the documentation.
### Documentation
Please see the documentation at https://sunnyxu.github.io/SBMLKinetics/ for details.
## For developers
### Setup environment
- Install [spyder3](http://www.psych.mcgill.ca/labs/mogillab/anaconda2/lib/python2.7/site-packages/spyder/doc/installation.html)
- Clone the ``SBMLKinetics`` repository using ``git clone https://github.com/SunnyXu/SBMLKinetics``
- Create a virtual environment for the project.
- ``cd SBMLKinetics``
- ``python -m venv kv``
- ``source kv/Scripts/activate``
(Use "\\" in windows.)
- ``pip install -r requirements.txt``
- ``deactivate``
To verify the setup:
- Return to the ``SBMLKinetics`` directory.
- ``source kv/Scripts/activate``
(Use "\\" in windows.)
- ``export PYTHONPATH=`pwd` ``
- ``python tests/test_simple_sbml.py``. The
tests should run without error.
(Use "\\" in windows.)
### Running Codes
- ``cd SBMLKinetics``
- ``source kv/bin/activate``
(Use "\\" in windows.)
When you're done, use ``deactivate``.
### Documentation
- ``examples/tutorial.py`` has code illustrating usage
- ``SBMLKinetics/common/*.py`` has codes for the
SmpleSBML (``simple_sbml.py``),
Reaction (``reaction.py``),
and KineticLaw (``kinetic_law.py``).
Raw data
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"description": "\n\n[](https://codecov.io/gh/ModelEngineering/SBMLKinetics)\n\n# SBMLKinetics\n\nSBMLKinetics is a Python package to evaluate and classify kinetics in SBML models. \nThere are many possible kinetics like the zeroth order, mass action, Michaelis-Menten, \nHill kinetics and others. This work characterizes the kinetics in the BioModels \nDatabase as an example to improve modeling best practices. Our tool can analyze any data sets \nwith SBML files as input. Users can also use this tool to compare different data sets. For \ninstance, we compare the distribution of kinetics for the signaling and metabolic networks and \nfind the substantial differences between two types of networks. \n\n## Citing\nIf you are using any of the \ncode, please cite the article (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05380-3) and the PYPI web page (https://pypi.org/project/SBMLKinetics/).\n\n## For users\n### Installation\n\n``pip install SBMLKinetics``\n\n## A Classification Example\n\nHere is a classification example generated by SBMLKinetics:\n\n<img src=\"https://raw.githubusercontent.com/SunnyXu/SBMLKinetics/master/docs/Figures/Fig1_curated.png\" width=\"450\" height=\"350\">\n\nPlease see more examples in the documentation.\n\n### Documentation\nPlease see the documentation at https://sunnyxu.github.io/SBMLKinetics/ for details.\n\n\n## For developers\n### Setup environment\n- Install [spyder3](http://www.psych.mcgill.ca/labs/mogillab/anaconda2/lib/python2.7/site-packages/spyder/doc/installation.html)\n- Clone the ``SBMLKinetics`` repository using ``git clone https://github.com/SunnyXu/SBMLKinetics``\n- Create a virtual environment for the project.\n - ``cd SBMLKinetics``\n - ``python -m venv kv``\n - ``source kv/Scripts/activate``\n(Use \"\\\\\" in windows.)\n - ``pip install -r requirements.txt``\n - ``deactivate``\n\nTo verify the setup:\n- Return to the ``SBMLKinetics`` directory.\n- ``source kv/Scripts/activate``\n(Use \"\\\\\" in windows.)\n- ``export PYTHONPATH=`pwd` ``\n- ``python tests/test_simple_sbml.py``. The\ntests should run without error.\n(Use \"\\\\\" in windows.)\n\n### Running Codes\n- ``cd SBMLKinetics``\n- ``source kv/bin/activate``\n(Use \"\\\\\" in windows.)\nWhen you're done, use ``deactivate``.\n\n### Documentation\n- ``examples/tutorial.py`` has code illustrating usage\n- ``SBMLKinetics/common/*.py`` has codes for the \nSmpleSBML (``simple_sbml.py``),\nReaction (``reaction.py``),\nand KineticLaw (``kinetic_law.py``).\n\n\n",
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