Genetic Algorithm for Identifying Novel Structures (GAINS)


Keywords
machine-learning, molecular-evolution, rdkit
License
MIT
Install
pip install gains==0.2.1

Documentation

Genetic Algorithm for Identifying Novel Structures

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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:

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.

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