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-0.4.1.tar.gz
(42.2 kB
view hashes)
Built Distribution
Close
Hashes for equilibrator-pathway-0.4.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 242a1a0215e57e02d1b7c981a130de7f56bbcde9232ad63e186c5a548dec2fac |
|
MD5 | 4712d5e906b1834a7fd83cf84b1ff6d7 |
|
BLAKE2b-256 | 6f34bbe0b0306b57493a10c015d4a08f86264ed11c5feee5a4d5baf17a2b7e06 |
Close
Hashes for equilibrator_pathway-0.4.1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3140b71a9185ed677985d79100538dd21a226a6692626d00f6039906f36aace0 |
|
MD5 | cec1ab3af82a91481a35c0b38441bd21 |
|
BLAKE2b-256 | 5ee86e82813aea86dc82e8c0e3876c3198fcb93dd2b8e00bde89c9c651c56920 |