Drug–drug interaction prediction with Wasserstein Adversarial Autoencoder-based knowledge graph embeddings

Abstract An interaction between pharmacological agents can trigger unexpected adverse events. Capturing richer and more comprehensive information about drug–drug interactions (DDIs) is one of the key tasks in public health and drug development. Recently, several knowledge graph (KG) embedding approa...

Full description

Bibliographic Details

Published in:	Briefings in bioinformatics Vol. 22; no. 4
Main Authors:	Dai, Yuanfei, Guo, Chenhao, Guo, Wenzhong, Eickhoff, Carsten
Format:	Journal Article
Language:	English
Published:	Oxford Oxford University Press 01.07.2021 Oxford Publishing Limited (England)
Subjects:	Classification Drug development Drug interaction Drug interactions Drugs Embedding Knowledge representation Public health Wasserstein distance adversarial learning drug–drug interaction knowledge graph embedding
ISSN:	1467-5463, 1477-4054, 1477-4054
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!