Skip to main content
Fig. 1 | Journal of Cheminformatics

Fig. 1

From: DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach

Fig. 1

Block diagram of our basic system. A molecule is generated by the Reinforcement Learning (RL) pathway using a Graph Convolutional Policy Networks. This molecule is then used as an input for the property prediction module which outputs the property score as predicted by the module. This score is then used as the reward feedback for the RL pathway and the cycle restarts

Back to article page

Journal of Cheminformatics

ISSN: 1758-2946

Contact us