GEEK

GEneralized Elementary Kinetics

Implements the GEEK analysis as described in : Daniel R. Weilandt and Vassily Hatzimanikatis. "Particle-based simulation reveals macromolecular crowding effects on the Michaelis-Menten mechanism", bioRxiv 429316; doi: `https://doi.org/10.1101/429316`_

Setup

Container-based install

We recommend to use this package inside of the provided DOCKER container. See docker/ for the setup and use of the container.

Source-based install

This step is not required if you're using the container, which bundles all this.

If you wish not to use the container based install you can install the package from source

git clone https://github.com/EPFL-LCSB/geek.git /path/to/geek
pip3 install -e /path/to/geek

Requirements

This module was developed in Python 3.5, and it is recommended to run Python 3.5. The module also was tested in Python 3.6.

This module requires OPENBReaD to work properly.

Further the following pip-python packages are required

• sympy >= 1.1.
• pytest
• scipy
• pandas
• statsmodels

Examples and Validation

You find examples of the analysis performed in the paper:

geek
├── data
└── paper
    ├── geek_example_analysis_pgm.py
    ├── geek_qssa_example.py
    └── geek_validation_dissociation_association.py

License

The software in this repository is put under an APACHE-2.0 licensing scheme - please see the LICENSE file for more details.