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-0.4.3.tar.gz
(42.5 kB
view hashes)
Built Distribution
Close
Hashes for equilibrator-pathway-0.4.3.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | b7e620d34ec472c2c92eac0b96e46326bea57a7460a936f42b4253efd0010fa7 |
|
MD5 | 88bc896dacb8c9dddf8a8e0066ee44f3 |
|
BLAKE2b-256 | 403dab9e313e2d44ced8f3212afa3ebd70bcee42dd179d761b679ff36e8dc138 |
Close
Hashes for equilibrator_pathway-0.4.3-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b1bc37392a5c2ed595f69c72b7024bc52e7a80990afcb31d8ecee847a0b34286 |
|
MD5 | 08aa16ab2a4381bef7ac255db2eb8a13 |
|
BLAKE2b-256 | 9d14741aa74c46996160586378267189c1390935f455e265a4ff99e62a716d4b |