AMGDTI: drug–target interaction prediction based on adaptive meta-graph learning in heterogeneous network

Prediction of drug–target interactions (DTIs) is essential in medicine field, since it benefits the identification of molecular structures potentially interacting with drugs and facilitates the discovery and reposition of drugs. Recently, much attention has been attracted to network representation l...

Full description

Saved in:

Bibliographic Details
Published in:	Briefings in bioinformatics Vol. 25; no. 1
Main Authors:	Su, Yansen, Hu, Zhiyang, Wang, Fei, Bin, Yannan, Zheng, Chunhou, Li, Haitao, Chen, Haowen, Zeng, Xiangxiang
Format:	Journal Article
Language:	English
Published:	England Oxford Publishing Limited (England) 01.01.2024 Oxford University Press
Subjects:	Algorithms Drug discovery Drugs Learning Machine learning Molecular structure Network topologies Predictions Problem Solving Protocol Representations Semantics Topology adaptive meta-graph drug–target interaction graph convolutional networks heterogeneous network
ISSN:	1467-5463, 1477-4054, 1477-4054
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!