Model balancing¶
Model balancing is a computational method to determine plausible kinetic constants and metabolic states in kinetic metabolic models 1. It integrates flux, metabolite, protein, and kinetic constant data, using prior distributions for all these variables, and computes the joint posterior mode.
Model balancing can be run in Matlab or Python. Data tables can be provided in SBtab format, models can be provided in SBML or SBtab format.
This documentation is for the Python version of Model Balancing only. For balancing your model, generating a JSON input file, or running model balancing in Matlab - see instructions here.
Installation:¶
Clone the repository:
git clone https://gitlab.com/elad.noor/model-balancing.git
Install using the package in a new Virtual Environment using:
cd python
python -m venv venv
source venv/bin/activate
pip install -e .
Obtain a license for MOSEK. For example, you might qualify for a free academic license.
You can then try the example script:
python examples/comparison_with_matlab.py
which runs model balancing on a list of JSON examples and for a fixed set of values for alpha.
The code was tested with Python 3.9 on Ubuntu Linux 21.04.
License:¶
This package is released under the GNU General Public License.
Contact:¶
Please contact Wolfram Liebermeister and Elad Noor with any questions or comments.
References:¶
- 1
Wolfram Liebermeister and Elad Noor. Model balancing: in search of consistent metabolic states and in-vivo kinetic constants. bioRxiv, pages 2019.12.23.887166, March 2021. Publisher: Cold Spring Harbor Laboratory Section: New Results. URL: https://www.biorxiv.org/content/10.1101/2019.12.23.887166v2 (visited on 2021-06-08), doi:10.1101/2019.12.23.887166.