AI RESEARCH
Ligandformer: A Graph Neural Network for Predicting Compound Property with Robust Interpretation
arXiv CS.LG
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ArXi:2202.10873v4 Announce Type: replace-cross Robust and efficient interpretation of QSAR methods is quite useful to validate AI prediction rationales with subjective opinion (chemist or biologist expertise), understand sophisticated chemical or biological process mechanisms, and provide heuristic ideas for structure optimization in pharmaceutical industry. For this purpose, we construct a multi-layer self-attention based Graph Neural Network framework, namely Ligandformer, for predicting compound property with interpretation.