Metadata-Version: 2.1
Name: component-contribution
Version: 0.4.2
Summary: Standard reaction Gibbs energy estimation for biochemical reactions.
Home-page: https://gitlab.com/equilibrator/component-contribution
Author: Elad Noor, Moritz E. Beber
Author-email: eladn@weizmann.ac.il, midnighter@posteo.net
License: MIT
Download-URL: https://pypi.org/project/component-contribution/
Project-URL: Source Code, https://gitlab.com/equilibrator/component-contribution
Project-URL: Bug Tracker, https://gitlab.com/equilibrator/component-contribution/-/issues
Description: # Component Contribution
        
        [![pipeline status](https://gitlab.com/elad.noor/component-contribution/badges/develop/pipeline.svg)](https://gitlab.com/elad.noor/component-contribution/commits/develop)
        
        [![coverage report](https://gitlab.com/elad.noor/component-contribution/badges/develop/coverage.svg)](https://gitlab.com/elad.noor/component-contribution/commits/develop)
        
        [![Join the chat at https://gitter.im/equilibrator-devs/component-contribution](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/equilibrator-devs/component-contribution?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
        
        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 3.6+
        * 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)
        
Keywords: component contribution,Gibbs energy,biochemical reaction,eQuilibrator,cache
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
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 :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: development
Provides-Extra: deployment
