Predicting Multiple Types of Associations Between miRNAs and Diseases Based on Graph Regularized Weighted Tensor Decomposition

Many studies have indicated miRNAs lead to the occurrence and development of diseases through a variety of underlying mechanisms. Meanwhile, computational models can save time, minimize cost, and discover potential associations on a large scale. However, most existing computational models based on a...

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Detalles Bibliográficos
Autores principales: Ouyang, Dong, Miao, Rui, Wang, Jianjun, Liu, Xiaoying, Xie, Shengli, Ai, Ning, Dang, Qi, Liang, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Bioengineering and Biotechnology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9335924/
https://www.ncbi.nlm.nih.gov/pubmed/35910021
http://dx.doi.org/10.3389/fbioe.2022.911769

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9335924/
https://www.ncbi.nlm.nih.gov/pubmed/35910021
http://dx.doi.org/10.3389/fbioe.2022.911769

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