Metadata-Version: 2.1
Name: component-contribution
Version: 0.6.0
Summary: A method for estimating the standard reaction Gibbs energy of biochemical reactions
Author: Elad Noor, Moritz E. Beber
License: MIT License
Project-URL: repository, https://gitlab.com/equilibrator/component-contribution/
Project-URL: documentation, https://equilibrator.readthedocs.io/en/latest/
Keywords: component contribution,Gibbs energy,biochemical reaction,eQuilibrator
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: equilibrator-cache ~=0.6.0
Requires-Dist: scipy >=1.12
Requires-Dist: path ~=16.7
Requires-Dist: uncertainties ~=3.1
Provides-Extra: deployment
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Requires-Dist: click-log ; extra == 'deployment'
Requires-Dist: python-dateutil ; extra == 'deployment'
Requires-Dist: requests ; extra == 'deployment'
Requires-Dist: equilibrator-assets ; extra == 'deployment'
Provides-Extra: development
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Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
Requires-Dist: pytest-raises ; extra == 'test'
Requires-Dist: pytest-mock ; extra == 'test'

# Component Contribution

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A method for estimating the standard reaction Gibbs energy of biochemical reactions. 

## Cite us

For more information on the method behind component-contribution, please view our open
access paper:

Noor E, Haraldsdóttir HS, Milo R, Fleming RMT (2013)
[Consistent Estimation of Gibbs Energy Using Component Contributions](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003098),
PLoS Comput Biol 9:e1003098, DOI: 10.1371/journal.pcbi.1003098

Please, cite this paper if you publish work that uses `component-contribution`.

## Installation

* `pip install component-contribution`

## Dependencies

* Python 3.9+
* PyPI dependencies for prediction:
  - equilibrator-cache
  - numpy
  - scipy
  - pandas
  - pint
  - path
  - periodictable
  - uncertainties
* PyPI dependencies for training a new model:
  - openbabel
  - equilibrator-assets

## Data sources

* [Training data for the component contribution method](https://zenodo.org/record/3978440)
* [Chemical group definitions for the component-contribution method](https://zenodo.org/record/4010930)
