Predicting miRNA-Disease Association Based on Neural Inductive Matrix Completion with Graph Autoencoders and Self-Attention Mechanism

Predicting miRNA-Disease Association Based on Neural Inductive Matrix Completion with Graph Autoencoders and Self-Attention Mechanism

Many studies have clarified that microRNAs (miRNAs) are associated with many human diseases. Therefore, it is essential to predict potential miRNA-disease associations for disease pathogenesis and treatment. Numerous machine learning and deep learning approaches have been adopted to this problem. In...

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Bibliographic Details
Main Authors: Chen Jin, Zhuangwei Shi, Ken Lin, Han Zhang
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Biomolecules
Subjects:
miRNA-disease association
inductive matrix completion
graph autoencoder
self-attention mechanism
Online Access:https://www.mdpi.com/2218-273X/12/1/64

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https://www.mdpi.com/2218-273X/12/1/64

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