Metadata-Version: 2.1
Name: dcFBA
Version: 0.1.0.1
Summary: Python package for Dynamic Community FBA
Author-email: Steven Wijnen <steven.wijnen@icloud.com>, Francesco Moro <f.moro@vu.nl>, Brett Olivier <b.g.olivier@vu.nl>
License: MIT License
        
        Copyright (c) 2023 Steven Wijnen
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Project-URL: Homepage, https://github.com/SystemsBioinformatics/dynamic-community-fba
Project-URL: Bug Tracker, https://github.com/SystemsBioinformatics/dynamic-community-fba/issues
Project-URL: Docs, https://dynamic-community-fba.readthedocs.io/en/latest/index.html
Keywords: Microbial Community,Systems Biology,Dynamic FBA,Genome Scale Models
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: <3.11,>=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cbmpy>=0.8.8
Requires-Dist: pyparsing>=3.0

# Dynamic Community FBA

Welcome to Dynamic Community FBA (dcFBA): The Python package that makes modeling Microbial Communities dynamically a breeze!

This project is licensed under the MIT License - please refer to the [LICENSE](LICENSE) file for more details.

## About

Dynamic Community FBA (dcFBA) is a versatile tool designed for modeling microbial communities as single organisms using Genome Scale Metabolic Models (GSMMs). This package builds upon the solid foundation of [cbmpy](https://github.com/SystemsBioinformatics/cbmpy) and seamlessly integrates with SBML and COBRApy models. dcFBA empowers users with three distinct dynamic modeling methods:

1. **Dynamic Joint FBA** - Incrementally updates the concentrations of biomass and metabolites within the combined stoichiometric matrix of the provided models.

2. **Dynamic Parallel FBA** - Simultaneously updates the concentrations of biomass and metabolites while performing FBA on individual models.

3. **EndPointFBA** - Duplicates the CommunityMatrix N times and performs FBA on the community's time-dependent stoichiometric matrix.

For a comprehensive understanding of these methods and their underlying mathematics, please consult [^1].

Whether you're exploring parasitic interactions or investigating costly cross-feeding behaviors in microbial communities, dcFBA offers an elegant and efficient solution.

## Installation

### Prerequisites

Before installing dcFBA, make sure you have the following prerequisites in place:

- Python >= 3.8, < 3.11
- [cbmpy](https://github.com/SystemsBioinformatics/cbmpy)
- [cplex](https://www.ibm.com/products/ilog-cplex-optimization-studio)

### Installation Steps

To install dcFBA, follow these simple steps:

1. Install using pip:

    ```bash
    pip install dcFBA
    ```

## Usage

For basic usage examples and detailed documentation on both [cbmpy](https://pythonhosted.org/cbmpy/modules_doc.html) and [dcFBA](https://dynamic-community-fba.readthedocs.io/en/latest), please refer to their respective documentation pages.

[^1]: [Cite paper.]
