GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization

GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization

Abstract Non-coding RNAs (ncRNAs) draw much attention from studies widely in recent years because they play vital roles in life activities. As a good complement to wet experiment methods, computational prediction methods can greatly save experimental costs. However, high false-negative data and insu...

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Bibliographic Details
Main Authors: Ning Ai, Yong Liang, Haoliang Yuan, Dong Ouyang, Shengli Xie, Xiaoying Liu
Format: Article
Language:English
Published: BMC 2023-07-01
Series:BMC Genomics
Subjects:
Non-coding RNA-disease associations
Multi-source heterogenous networks
Contrastive learning
Deep graph learning
Deep matrix factorization
Online Access:https://doi.org/10.1186/s12864-023-09501-3

Internet

https://doi.org/10.1186/s12864-023-09501-3

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