Pathway analysis tools by eQuilibrator
Project description
equilibrator-pathway
Pathway analysis tools based on thermodynamic and kinetic models. This package can run two different pathway analysis methods:
- Max-min Driving Force (MDF)1: objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force.
- Enzyme Cost Minimization (ECM)2, 3: estimating the specific cost in enzymes for sustaining a flux, given a kinetic model.
Installation
The easiest way to install equilibrator-pathway is PyPI (and we recommend using a virtual environment):
virtualenv -p python3 equilibrator
source equilibrator/bin/activate
pip install equilibrator-pathway
or, if you prefer installing with conda:
conda install -c conda-forge equilibrator-pathway
The following example Jupyter notebook can help you get started.
If you only want to try out MDF or ECM without installing anything locally, we have a simple web interface for you at eQuilibrator 4.
References
- E. Noor, A. Bar-Even, A. Flamholz, E. Reznik, W. Liebermeister, R. Milo (2014), Pathway Thermodynamics Highlights Kinetic Obstaclesin Central Metabolism, PLOS Comp. Biol., DOI: 10.1371/journal.pcbi.1003483
- https://www.metabolic-economics.de/enzyme-cost-minimization/
- E. Noor, A. Flamholz, A. Bar-Even, D. Davidi, R. Milo, W. Liebermeister (2016), The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization, PLOS Comp. Biol., DOI: 10.1371/journal.pcbi.1005167
- Flamholz, E. Noor, A. Bar-Even, R. Milo (2012) eQuilibrator - the biochemical thermodynamics calculator, Nucleic Acids Res, DOI: 10.1093/nar/gkr874
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
equilibrator-pathway-0.6.0.tar.gz
(27.7 kB
view hashes)
Built Distribution
Close
Hashes for equilibrator-pathway-0.6.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 827b83ac78e548dace8df5d02583240f4f0fe24a44b86e62a4d503724f7f2cda |
|
MD5 | e8a503e150ac3ec8d02aa83e19c57bef |
|
BLAKE2b-256 | 924785891a0aa1553df500112f981179e32a0fcc5acf9406d7375814ea043749 |
Close
Hashes for equilibrator_pathway-0.6.0-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2596c9447afca7860a38ab5f282a6e161826352d62c47523cbbcc4653f6f4acf |
|
MD5 | f4fff04ad8091cac5af6ff9c861aa264 |
|
BLAKE2b-256 | 63cd21ebb070f4b884bdcaa0035f7b6bf7d6335bde7ca02aec6781771ef5f7c3 |