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Pathway analysis tools by eQuilibrator

Project description

equilibrator-pathway

PyPI version Anaconda-Server Badge Python version MIT license

pipeline status codecov Join our Google group Documentation Status

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

  1. 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
  2. https://www.metabolic-economics.de/enzyme-cost-minimization/
  3. 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
  4. Flamholz, E. Noor, A. Bar-Even, R. Milo (2012) eQuilibrator - the biochemical thermodynamics calculator, Nucleic Acids Res, DOI: 10.1093/nar/gkr874

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