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
Built Distribution
Close
Hashes for equilibrator-pathway-0.4.6b1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8c58d84bb376ea2825cce19886c9dd072dd723e1fe016732995920777dc5beec |
|
MD5 | 2b232948113859cd924cc613c882144a |
|
BLAKE2b-256 | 861455339708f1b9afe37d71e872fad406c924253e7bcef027fe2ace8a84e683 |
Close
Hashes for equilibrator_pathway-0.4.6b1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2bb3464c91da06b6853a6d1bc7d851153dc78e82c0917ea828dded82e2adf8bf |
|
MD5 | 5fc334f036df7f1aafebb5d89227b8da |
|
BLAKE2b-256 | 379037eccb08961ea967b52cabd7fcaa9020ab8a4c7e12a80fc1e2cd961b29ae |