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NGCICM: A Novel Deep Learning-Based Method for Predicting circRNA-miRNA Interactions

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成果类型:
期刊论文
作者:
Ma, Zhihao;Kuang, Zhufang;Deng, Lei
通讯作者:
Kuang, ZF
作者机构:
[Kuang, Zhufang; Ma, Zhihao] Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha 410004, Hunan, Peoples R China.
[Deng, Lei] Cent South Univ, Sch Comp Sci & Engn, Changsha 410083, Hunan, Peoples R China.
通讯机构:
[Kuang, ZF ] C
Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha 410004, Hunan, Peoples R China.
语种:
英文
关键词:
CircRNA-disease;deep learning;graph con- volutional network;heterogenous network
期刊:
IEEE/ACM Transactions on Computational Biology and Bioinformatics
ISSN:
1545-5963
年:
2023
卷:
20
期:
5
页码:
3080-3092
基金类别:
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62072477, 61309027, 61702562 and 61702561) 10.13039/501100004735-Natural Science Foundation of Hunan Province (Grant Number: 2018JJ3888) Scientific Research Fund of Hunan Provincial Education Department (Grant Number: 18B197) National Key R&D Program of China (Grant Number: 2018YFB1700200) Hunan Key Laboratory of Intelligent Logistics Technology (Grant Number: 2019TP1015)
机构署名:
本校为第一且通讯机构
院系归属:
计算机与信息工程学院
摘要:
The circRNAs and miRNAs play an important role in the development of human diseases, and they can be widely used as biomarkers of diseases for disease diagnosis. In particular, circRNAs can act as sponge adsorbers for miRNAs and act together in certain diseases. However, the associations between the vast majority of circRNAs and diseases and between miRNAs and diseases remain unclear. Computational-based approaches are urgently needed to discover the unknown interactions between circRNAs and miRNAs. In this paper, we propose a novel deep learning algorithm based on Node2vec and Graph ATtention...

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