SPLHRNMTF: robust orthogonal non-negative matrix tri-factorization with self-paced learning and dual hypergraph regularization for predicting miRNA-disease associations.

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作者： Dong,Ouyang ^[1] ; Rui,Miao ^[2] ; Juan,Zeng ^[3] ; Xing,Li ^[3] ; Ning,Ai ^[4] ; Panke,Wang ^[3] ; Jie,Hou ^[3] ; Jinqiu,Zheng ^[3]

作者单位： School of Biomedical Engineering, Guangdong Medical University, Dongguan, 523808, China. ouyangdong@gdmu.edu.cn. ^[1] Basic Teaching Department, Zhuhai Campus of Zunyi Medical University, Zhuhai, 519099, China. ^[2] School of Biomedical Engineering, Guangdong Medical University, Dongguan, 523808, China. ^[3] The college of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China. ^[4]

关键词 L2,1 norm Hypergraph regularization MiRNA-disease associations Non-negative matrix tri-factorization Self-paced learning

主题词微RNAs(MicroRNAs);人类(Humans);计算生物学(Computational Biology);算法(Algorithms);疾病遗传易感性(Genetic Predisposition to Disease);肺肿瘤(Lung Neoplasms)

DOI 10.1186/s12864-024-10729-w

PMID 39304826

发布时间 2024-09-23

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