Example code of DGL for chemoinformatics task #DGL #chemoinformatics #RDKit #memo

There are many publications about graph based approach for chemoinformatics area. I can’t cover all of them but still have interest these area. I think pytorch_geometric (PyG) and deep graph library (DGL) are very attractive and useful package for chemoinformaticians. I wrote some posts about DGL and PyG. Recent DGL is more chemoinformatics friendly so

New trial of AttentiveFP with new atom feature #DGL #RDKit #Chemoinformatics

Recently I posted an example of AttentiveFP and I found that atom weights doesn’t directly reflect functional groups. And I could get useful suggestion via comment from DGL developper! And I wonder that how about to use functional group feature to train the model. But how can I detect functional groups in the molecule? Because

Visualize atom weight of AttentiveFP #DGL #RDKit #Chemoinformatics

Yesterday, I posted an example of DGL (almost same as original example code). And I could make regression model with my own dataset. Fortunately DGL developer provides a code for visualize atom weights of trained model. It means that, after building the model with AttentiveFP, you can visualize atom weight of the give molecule which

Molecular property regression with Attentive FP #RDKit #Chemoinformatics #DGL #DeepGraphLibrary

Recently Molecular Graph based deep learning is hot are in chemoinformatics.Some months ago, Zhaoping et al. published new graph based QSAR model named ‘Attentive FP’ in JMC. As its name suggests, Attentive FP uses attention mechanism for its architecture. The authors disclosed their code. And fortunately, recent version of DGL is also Attentive FP!Its repository