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Predicting miRNA-Disease Associations by Combining Graph and Hypergraph Convolutional Network.

Interdisciplinary sciences, computational life sciences - 1 Jun 2024

Liang Xujun, Guo Ming, Jiang Longying, Fu Ying, Zhang Pengfei, Chen Yongheng

Abstract excerpt

miRNAs are important regulators for many crucial biological processes. Many recent studies have shown that miRNAs are closely related to various human diseases and can be potential biomarkers or therapeutic targets for some diseases, such as cancers. Therefore, accurately predicting miRNA-disease associations is of great importance for understanding and curing diseases. However, how to efficiently utilize the...

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PMID: 38286905
DOI: 10.1007/s12539-023-00599-3

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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