FastSL-py is an efficient algorithm to identify synthetic lethal gene/reaction sets in genome-scale metabolic models.
Project description
This is the Python implementation of FastSL, an efficient algorithm to identify synthetic lethal gene/reaction sets in genome-scale metabolic models.
This package is based on cobrapy and provides a simple command-line tool.
For documentation, please visit: http://fastsl-py.readthedocs.io
Basic requirement(s):
- Python 3.6 for Gurobi 8 - Python 3.5 for IBM CPLEX and Gurobi 7
Installation:
Use pip to install from PyPI (recommended inside a virtual environment):
pip install fastsl
Contribute:
Issue Tracker: <https://github.com/RamanLab/FastSL-py/issues>
Support:
If you are having issues, please let us know. Contact us at: <fast-sl@ramanlab.groups.io>
License:
The project is licensed under GPL v3 license.
Note:
CPLEX and Gurobi are not included. Both are available for free (for academic purposes). All solvers are supported whose interfaces are provided by optlang.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for fastsl-0.1.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | eb0a43f6c91ef7c4d0be25396002768fabadf14dbca936e0ab13234966b4e86a |
|
MD5 | eb4f0355744fedf7d94e20acdae9288d |
|
BLAKE2b-256 | 8239acceb8619a8872411e6df0cf460a27e25f43e0899ff490230a98a5a4476c |