MSCHLMDA: Multi-Similarity Based Combinative Hypergraph Learning for Predicting MiRNA-Disease Association

MSCHLMDA: Multi-Similarity Based Combinative Hypergraph Learning for Predicting MiRNA-Disease Association

Accumulating biological and clinical evidence has confirmed the important associations between microRNAs (miRNAs) and a variety of human diseases. Predicting disease-related miRNAs is beneficial for understanding the molecular mechanisms of pathological conditions at the miRNA level, and facilitatin...

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Bibliographic Details
Main Authors: Qingwen Wu, Yutian Wang, Zhen Gao, Jiancheng Ni, Chunhou Zheng
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Genetics
Subjects:
microRNA
disease
miRNA-disease association
K-nearest neighbor
K-means
combinative hypergraph learning
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2020.00354/full

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https://www.frontiersin.org/article/10.3389/fgene.2020.00354/full

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