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
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
Metadata
Release files for pycomo 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pycomo-0.3.0.tar.gz | 65.8 kB | Without provenance | Details for pycomo-0.3.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pycomo-0.3.0-py3-none-any.whl | Python 3 | none | any | Details for pycomo-0.3.0-py3-none-any.whl |
Total release size: 134.6 kB
Release files / pycomo-0.3.0.tar.gz
| Download URL | pycomo-0.3.0.tar.gz |
|---|---|
| Size | 65.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
634ca528160a0577ccaf3b71e967a11b61231a2deedc1c4b157c744167ca55d1
|
|
BLAKE2b-256 checksum How to use checksums |
dcbbdcc5a1797b91f817603ce0af854efd479fe8b982258b257cdc13efcd6cd7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.7
|
Release files / pycomo-0.3.0-py3-none-any.whl
| Download URL | pycomo-0.3.0-py3-none-any.whl |
|---|---|
| Size | 68.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b50a0b2127297b9eeaca0e77a04d6c294fedc9bc3f5ba296b64f611a1b9e0fc5
|
|
BLAKE2b-256 checksum How to use checksums |
f3465f321c4ba4bfae55797d1a561ab69d56b80aa9dbed1de4f9a6e4108eeefb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.7
|
Security for pycomo 0.3.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.