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Article

Predicting multiple types of miRNA-disease associations using adaptive weighted nonnegative tensor factorization with self-paced learning and hypergraph regularization.

Briefings in bioinformatics - 19 Nov 2022

Ouyang Dong, Liang Yong, Wang Jianjun, Liu Xiaoying, Xie Shengli, Miao Rui, Ai Ning, Li Le, Dang Qi

Abstract excerpt

More and more evidence indicates that the dysregulations of microRNAs (miRNAs) lead to diseases through various kinds of underlying mechanisms. Identifying the multiple types of disease-related miRNAs plays an important role in studying the molecular mechanism of miRNAs in diseases. Moreover, compared with traditional biological experiments, computational models are time-saving and cost-minimized. However, most...

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PMID: 36168938
DOI: 10.1093/bib/bbac390

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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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