The code for the model described in the paper "Conditional molecular design with deep generative models" https://arxiv.org/abs/1805.00108
Modified by Gonzalo Colmenarejo
- run.py : main script
- SSVAE.py - model architecture
- mySSVAE.py - modification of the previous to deal with multiparameter conditioning
- preprocessing.py - functions for preprocessing
- exp0 : default run of CMD with original dataset and analysis of diversity, correctness and novelty of output
- exp1 : analysis of output (cor, div, nov) after training the CMD with increasing subsets of original training dataset
- exp3 : modified CMD for natural products; analyis of cor, div, nov of output
- exp4 : analysis of output (cor, div, nov) after training with orthogonal set vs clustered set
- cix : folder with myfuncs.py, a module created for performing all cheminformatic analyses
- TensorFlow
- NumPy
- RDKit
- chemfp
- scikit-learn
- pandas
- matplotlib
Two Anaconda environments are used to run the code: tf35 to run the CMD, and cix to run the analysis Jupyter notebooks