Drug Interaction Knowledge Graphs
Drug Interaction Knowledge Graphs is a structured semantic network that integrates heterogeneous biomedical data to represent and infer relationships between drugs, their targets, and potential interaction outcomes through a formal ontology of entities and relations.
39
Publications
2.6K
Citations
167
Authors
93
Institutions
Publications per year
2017–2026
37
39
KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction
Xuan Lin, Zhe Quan, Zhijie Wang et al. · 2020 · 316 citations · Full text
Computing, Pharmacology, Data Mining +16
SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization
Yue Yu, Kexin Huang, Chao Zhang et al. · Bioinformatics · 2021 · 173 citations · Full text
Multi-view Graph Contrastive Representation Learning for Drug-Drug Interaction Prediction
Yingheng Wang, Yaosen Min, Xin Chen et al. · 2021 · 165 citations · Full text
1–5 of 39
167
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3
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3
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Xinjiang Technical Institute of Physics & Chemistry, China
3 publications · 279 citations
3
h-index
3
h-index
1–5 of 167
93
Georgia Institute of Technology
Atlanta, United States
3 h-index
4 publications
663 citations

Northwestern Polytechnical University
Xi'an, China
3 h-index
7 publications
403 citations

University of Helsinki
Helsinki, Finland
3 h-index
6 publications
234 citations
The University of Texas Health Science Center at Houston
Houston, United States
3 h-index
18 publications
702 citations
Xinjiang Technical Institute of Physics & Chemistry
Ürümqi, China
2 h-index
10 publications
1.1K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
2 h-index
6 publications
351 citations

King Abdullah University of Science and Technology
Jeddah, Saudi Arabia
2 h-index
2 publications
117 citations
Tongji University
Shanghai, China
2 h-index
2 publications
125 citations
1–8 of 93
5 publications · 372 citations
5
h-index
2 publications · 127 citations
2
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2 publications · 62 citations
2
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2 publications · 137 citations
2
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2 publications · 217 citations
2
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1–5