Metadata-Version: 2.4
Name: pycomo
Version: 0.3.0
Summary: PyCoMo is a software package for generating and analysing compartmentalized community metabolic models
Home-page: https://github.com/univieCUBE/PyCoMo
Author: Michael Predl
Author-email: Michael Predl <michael.predl@univie.ac.at>, Marianne Mießkes <marianne.miesskes@univie.ac.at>, Juergen Zanghellini <juergen.zanghellini@univie.ac.at>
Maintainer-email: Michael Predl <michael.predl@univie.ac.at>
License: MIT License
        
        Copyright (c) 2023 Michael Predl
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
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Project-URL: repository, https://github.com/univieCUBE/PyCoMo
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cobra>=0.23.0
Requires-Dist: pandas>=1.5.3
Requires-Dist: python-libsbml>=5.20.1
Requires-Dist: numpy>=1.22.4
Requires-Dist: sympy
Provides-Extra: efm
Requires-Dist: efmtool; extra == "efm"
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

# PyCoMo
## What is PyCoMo?
PyCoMo is a python 3 package for the creation and analysis of community metabolic models. More specifically, PyCoMo generates compartmentalized community metabolic models with a structure allowing simulations under fixed growth rate, but variable abundance profile, or fixed abundance profile and variable community growth rate. The community metabolic models generated by PyCoMo can switch between these two structures and retain the original reaction bounds of the input member models. As also all metabolites, reactions, genes and compartments are directly attributable to their member of origin, PyCoMo community metabolic models are fully reusable.

The community models can be analysed with PyCoMo to predict all feasible exchange metabolites and cross-feeding interactions, for the whole space of growth rate and abundance profiles. The community models are COBRApy models and can therefor be directly used by other COBRA methods. It is also possible to save and load the community models in SBML format, allowing to share and reuse the models built with PyCoMo.

## Documentation
Documentation, tutorials and examples are available at [univiecube.github.io/PyCoMo](https://univiecube.github.io/PyCoMo/)

## Installation
PyCoMo can be installed via pip:
```
pip install pycomo
```
Or via conda:
```
conda install -c conda-forge -c bioconda pycomo
```
Alternatively PyCoMo can be installed from the GitHub repository. First clone the repository to your machine.
```
git clone https://github.com/univieCUBE/PyCoMo
```
Next run pip install on the folder containing the PyCoMo repository.
```
pip install path/to/PyCoMo
```

## Usage guide
PyCoMo can be imported in Python as any other package. Please look through the tutorial for a walkthrough of all the options generating and analysing community metabolic models (available as ipython notebook, python file and pdf).

PyCoMo can also be used via its command line interface. After installation, run ```pycomo -h``` or ```pycomo --help``` to see all options.
## Citing PyCoMo
Michael Predl, Marianne Mießkes, Thomas Rattei, Jürgen Zanghellini, PyCoMo: a python package for community metabolic model creation and analysis, _Bioinformatics_, Volume 40, Issue 4, April 2024, btae153, [https://doi.org/10.1093/bioinformatics/btae153](https://doi.org/10.1093/bioinformatics/btae153)
