Knowledge Graph Information Bottleneck for Drug-Drug Interaction Prediction-Reference-Cited by-同舟云学术

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Knowledge Graph Information Bottleneck for Drug-Drug Interaction Prediction

Published:2024-06-30 Issue: Volume:33 Page:1-8
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Liu Shun¹,He Gaoqi¹,Zhang Kai²,Li Honglin³

Affiliation:

1. East China Normal University,School of Computer Science and Technology

2. East China Normal University,School of Computer Science and Technology, Innovation Center for AI and Drug Discovery

3. East China University of Science and Technology Innovation Center for AI and Drug Discovery, East China Normal University,Shanghai Key Laboratory of New Drug Design

Funder

National Natural Science Foundation of China

Research and Development

Natural Science Foundation of Chongqing

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10651537.pdf?arnumber=10651537

Reference40 articles.

1. FP-GNN: a versatile deep learning architecture for enhanced molecular property prediction

2. MUFFIN: multi-scale feature fusion for drug–drug interaction prediction

3. node2vec

4. Systematic integration of biomedical knowledge prioritizes drugs for repurposing

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