Molecule Property Prediction Based on Spatial Graph Embedding

Journal of Chemical Information and Modeling 2019 Xiaofeng WangZhen LiMingjian JiangShuang WangShugang ZhangZhiqiang Wei

Accurate prediction of molecular properties is important for new compound design, which is a crucial step in drug discovery. In this paper, molecular graph data is utilized for property prediction based on graph convolution neural networks... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK LEADERBOARD
Graph Regression Lipophilicity C-SGEN+ Fingerprint RMSE 0.650 # 2

Methods used in the Paper