ACGCN: Graph Convolutional Networks for Activity Cliff Prediction between Matched Molecular Pairs.
Junhui ParkGaeun SungSeunghyun LeeSeungho KangChunkyun ParkPublished in: J. Chem. Inf. Model. (2022)
Keyphrases
- protein function prediction
- protein interaction
- interaction networks
- graph representation
- prediction accuracy
- drug design
- protein interaction networks
- social networks
- average degree
- directed graph
- edge weights
- three dimensional
- graph layout
- graph structures
- molecular interactions
- random walk
- computational methods
- graph mining
- complex networks
- signaling pathways
- pairwise
- dynamic networks
- prediction model
- path length
- neural network ensemble
- graph structure
- small world
- social graphs
- graph theory
- graph model
- betweenness centrality
- human activities
- directed edges
- overlapping communities
- degree distribution
- structured data
- community discovery
- protein structure prediction
- bipartite graph
- biological networks
- network architecture
- prediction error
- weighted graph