IGNSCDA: Predicting CircRNA-Disease Associations Based on Improved Graph Convolutional Network and Negative Sampling-Reference-Cited by-同舟云学术

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IGNSCDA: Predicting CircRNA-Disease Associations Based on Improved Graph Convolutional Network and Negative Sampling

Published:2021 Issue: Volume: Page:1-1
ISSN:1545-5963
Container-title:IEEE/ACM Transactions on Computational Biology and Bioinformatics
language:
Short-container-title:IEEE/ACM Trans. Comput. Biol. and Bioinf.

Author:

Lan Wei,Dong Yi,Chen Qingfeng,Liu Jin,Wang Jianxin,Chen Yi-Ping Phoebe,Pan Shirui

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Genetics,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/8857/4359833/09535297.pdf?arnumber=9535297

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Identifying circRNA-disease association based on relational graph attention network and hypergraph attention network;Analytical Biochemistry;2024-11

2. circRNA-disease association prediction with an improved unbalanced Bi-Random walk;Journal of Radiation Research and Applied Sciences;2024-06

3. Bi-SGTAR: A simple yet efficient model for circRNA-disease association prediction based on known association pair only;Knowledge-Based Systems;2024-05

4. SimKG-BERT: A Security Enhancement Approach for Healthcare Models Consisting of Fusing SimBERT and a Knowledge Graph;Applied Sciences;2024-02-18

5. AMPCDA: Prediction of circRNA–disease associations by utilizing attention mechanisms on metapaths;Computational Biology and Chemistry;2024-02

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