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Pathway analysis tools by eQuilibrator

Project description

equilibrator-pathway

PyPI version Anaconda-Server Badge Python version MIT license

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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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