Inferring human miRNA–disease associations via multiple kernel fusion on GCNII
Increasing evidence shows that the occurrence of human complex diseases is closely related to the mutation and abnormal expression of microRNAs(miRNAs). MiRNAs have complex and fine regulatory mechanisms, which makes it a promising target for drug discovery and disease diagnosis. Therefore, predicti...
Main Authors: | Shanghui Lu, Yong Liang, Le Li, Shuilin Liao, Dong Ouyang |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-09-01
|
Series: | Frontiers in Genetics |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.980497/full |
Similar Items
-
FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease association
by: Limin Jiang, et al.
Published: (2018-12-01) -
Inferring circRNA-drug sensitivity associations via dual hierarchical attention networks and multiple kernel fusion
by: Shanghui Lu, et al.
Published: (2023-12-01) -
HGSMDA: miRNA–Disease Association Prediction Based on HyperGCN and Sørensen-Dice Loss
by: Zhenghua Chang, et al.
Published: (2024-01-01) -
Predicting Multiple Types of Associations Between miRNAs and Diseases Based on Graph Regularized Weighted Tensor Decomposition
by: Dong Ouyang, et al.
Published: (2022-07-01) -
Corrigendum: Predicting multiple types of associations between miRNAs and diseases based on graph regularized weighted tensor decomposition
by: Dong Ouyang, et al.
Published: (2022-08-01)