Simplified, interpretable graph convolutional neural networks for small molecule activity prediction.
Jeffrey K. WeberJoseph A. MorroneSugato BagchiJan D. Estrada PabonSeung-gu KangLeili ZhangWendy D. CornellPublished in: J. Comput. Aided Mol. Des. (2022)
Keyphrases
- convolutional neural networks
- random walk
- prediction accuracy
- graph structure
- convolutional network
- prediction algorithm
- prediction model
- graph matching
- bipartite graph
- prediction error
- small number
- weighted graph
- graph model
- graph partitioning
- protein interaction
- directed graph
- graph theory
- graph mining
- graph theoretic
- activity theory
- seed set
- connected components