GADTI: Graph Autoencoder Approach for DTI Prediction From Heterogeneous Network

GADTI: Graph Autoencoder Approach for DTI Prediction From Heterogeneous Network

Identifying drug–target interaction (DTI) is the basis for drug development. However, the method of using biochemical experiments to discover drug-target interactions has low coverage and high costs. Many computational methods have been developed to predict potential drug-target interactions based o...

Full description

Bibliographic Details
Main Authors: Zhixian Liu, Qingfeng Chen, Wei Lan, Haiming Pan, Xinkun Hao, Shirui Pan
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Genetics
Subjects:
drug-target interaction prediction
network embedding
graph convolutional network
autoencoder
random walk
heterogeneous network
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2021.650821/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2021.650821/full

Similar Items