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Predicting lincRNA-Disease Association in Heterogeneous Networks Using Co-regularized Non-negative Matrix Factorization

Long intergenic non-coding ribonucleic acids (lincRNAs) are critical regulators for many complex diseases, and identification of disease-lincRNA association is both costly and time-consuming. Therefore, it is necessary to design computational approaches to predict the disease-lincRNA associations th...

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Detalles Bibliográficos
Autores principales: Lin, Yong, Ma, Xiaoke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835800/
https://www.ncbi.nlm.nih.gov/pubmed/33510774
http://dx.doi.org/10.3389/fgene.2020.622234

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