SPAM-DFBA
Introduction
SPAM-DFBA is an algoritm for inferring microbial interactions by modeling microbial metabolism in a community as a decision making process, a markov decision process more specifically, where individual agents learn metabolic regulation strategies that lead to their long-term survival by trying different strategies and improve their strategies according to proximal policy optimization algorithm.
More information can be found in the documentation website for this project:
https://chan-csu.github.io/SPAM-DFBA/
Installation
There are multiple ways to install SPAM-DFBA. Before doing any installation it is highly recomended that you create a new environment for this project. After creating the virtual environment and activating it, one way for installation is to clone the ripository and pip install from the source files:
git clone https://github.com/chan-csu/SPAM-DFBA.git
cd SPAM-DFBA
pip install .
Another approach is to directly install this package from pipy:
pip install spamdfba
Examples
The examples used in the manuscript are provided in separated jupyter notebooks in the ./examples directory. Additionally, they are provided in the documentation website for this project under Case Study-* section
Contribution
If you have any suggestions or issues related to this project please open an issue or suggest a pull request for further imrovements!
1 maintainer
Metadata
1 maintainer
Release files for spamdfba 1.1.0
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Source distribution (sdist)
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Built distribution (wheel)
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| spamdfba-1.1.0-py3-none-any.whl | Python 3 | none | any | Details for spamdfba-1.1.0-py3-none-any.whl |
Total release size: 31.1 kB
Release files / spamdfba-1.1.0.tar.gz
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Release files / spamdfba-1.1.0-py3-none-any.whl
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