https://github.com/wesleybeckner/gains
project that enables molecular design and computational screening of small molecules
https://github.com/wesleybeckner/gains
machine-learning molecular-evolution rdkit
Last synced: about 1 year ago
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project that enables molecular design and computational screening of small molecules
- Host: GitHub
- URL: https://github.com/wesleybeckner/gains
- Owner: wesleybeckner
- License: mit
- Created: 2017-11-14T18:38:07.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2023-05-01T20:19:48.000Z (about 3 years ago)
- Last Synced: 2024-08-10T05:04:41.184Z (almost 2 years ago)
- Topics: machine-learning, molecular-evolution, rdkit
- Language: Python
- Homepage:
- Size: 68.8 MB
- Stars: 6
- Watchers: 5
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README

## Genetic Algorithm for Identifying Novel Structures
[](https://travis-ci.org/wesleybeckner/gains)
[](https://badge.fury.io/py/gains)
[](https://coveralls.io/github/wesleybeckner/gains?branch=master)
========
GAINS — Genetic Algorithm for Identifying Novel Structures — is a project
that enables molecular design and computational screening of
small molecules. Built on the molecular functionality of RDKit, GAINS is employable across a spectrum of small-molecule design problems.
## Installation
### Dependencies
GAINS requires:
* python (>= 3.6)
* scikit-learn (>= 0.19.1)
* rdkit (>= 2017.09.1)
* salty-ilthermo (>= 0.2)
Note that scikit-learn 0.18.1 will raise a warning when loading in property models to the engine.
To take full advantage of rdkit you will also need Matplotlib >= 1.3.1.
#### User installation
You will first need to install [rdkit](http://www.rdkit.org/docs/GettingStartedInPython.html):
```
conda create -n py36 python=3.6 anaconda
# activate the new virtual environment, e.g. on OSX/Linux
source activate py36
# on Windows
# activate py36
conda install -c rdkit rdkit
```
GAINS can then be installed with:
```
pip install gains
```
## Development
GAINS is currently underdevelopment by researchers at the University of Washington. Our research page can be found [here](http://www.prg.washington.edu).
### Testing
After installation, you can launch the test suite from outside the source directory (you will need to have the pytest package installed):
```
pytest gains
```