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...

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Veröffentlicht in:	Frontiers in genetics Jg. 12; S. 650821
Hauptverfasser:	Liu, Zhixian, Chen, Qingfeng, Lan, Wei, Pan, Haiming, Hao, Xinkun, Pan, Shirui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media S.A 09.04.2021
Schlagworte:	autoencoder drug-target interaction prediction Genetics graph convolutional network heterogeneous network network embedding random walk graph convolutional network random walk drug-target interaction prediction autoencoder heterogeneous network network embedding
ISSN:	1664-8021, 1664-8021
Online-Zugang:	Volltext
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