RPI-GGCN: Prediction of RNA–Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders-Reference-Cited by-同舟云学术

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RPI-GGCN: Prediction of RNA–Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders

Published:2024 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Wang Yifei¹^ORCID,Ding Pengju²^ORCID,Wang Congjing¹,He Shiyue²,Gao Xin³^ORCID,Yu Bin⁴^ORCID

Affiliation:

1. School of Data Science, College of Mathematics and Physics, Qingdao University of Science and Technology of China, Qingdao, China

2. School of Data Science, Qingdao University of Science and Technology of China, Qingdao, China

3. Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

4. School of Data Science, Qingdao University of Science and Technology, Qingdao, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province of China

King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10520920.pdf?arnumber=10520920

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