/KerasNeuralFingerprint

Keras-based implementation of neural fingerprints, operating on molecular graphs of arbitrary size

Primary LanguagePythonMIT LicenseMIT

Keras-based implementation of neural fingerprints

A convolutional neural network operating on molecular graphs (SMILES) of arbitrary size for chemical property prediction (e.g. solubility).

Requirements:

Python, Numpy -- preferrably using Anaconda

Either Theano or Tensorflow

RDkit -- the easiest way to install it when using Anaconda is "conda install -c https://conda.anaconda.org/rdkit rdkit"

Paper describing the method: Convolutional Networks on Graphs for Learning Molecular Fingerprints

The original implementation using numpy/autograd can be found at (https://github.com/HIPS/neural-fingerprint)