GSAMDA: a computational model for predicting potential microbe-drug associations based on graph attention network and sparse autoencoder.
Yaqin TanJuan ZouLinai KuangXiangyi WangBin ZengZhen ZhangLei WangPublished in: BMC Bioinform. (2022)
Keyphrases
- computational model
- computational models
- computational framework
- cognitive modeling
- language acquisition
- cognitive architecture
- spanning tree
- wireless sensor networks
- pharmaceutical industry
- computational modeling
- random graphs
- working memory
- small world
- graph theory
- random walk
- weighted graph
- focus of attention
- directed graph
- complex networks
- visual processing
- fully connected
- short term memory
- graph mining
- graph structure
- visual attention
- network structure
- peer to peer