| Name | dcFBA JSON |
| Version |
0.1.2
JSON |
| download |
| home_page | https://github.com/SystemsBioinformatics/dynamic-community-fba |
| Summary | Python package for Dynamic Community FBA |
| upload_time | 2023-11-13 15:51:12 |
| maintainer | |
| docs_url | None |
| author | Steven Wijnen, Francesco Moro, Brett Olivier |
| requires_python | <3.11,>=3.8 |
| 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 copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
microbial community
systems biology
dynamic fba
genome scale models
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 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.]
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