MAVGAE: a multimodal framework for predicting asymmetric drug–drug interactions based on variational graph autoencoder
Author:
Affiliation:
1. School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China
2. School of Information Science and Engineering, Qufu Normal University, Rizhao, China
Funder
Natural Science Foundation of Shandong Province
the National Natural Science Foundation of China
Publisher
Informa UK Limited
Subject
Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/10255842.2024.2311315
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4. Sequential Therapy of Acute Kidney Injury with a DNA Nanodevice
5. A multimodal deep learning framework for predicting drug–drug interaction events
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