Cargando…
ILPMDA: Predicting miRNA–Disease Association Based on Improved Label Propagation
MicroRNAs (miRNAs) are small non-coding RNAs that have been demonstrated to be related to numerous complex human diseases. Considerable studies have suggested that miRNAs affect many complicated bioprocesses. Hence, the investigation of disease-related miRNAs by utilizing computational methods is wa...
Autores principales: | Wang, Yu-Tian, Li, Lei, Ji, Cun-Mei, Zheng, Chun-Hou, Ni, Jian-Cheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514753/ https://www.ncbi.nlm.nih.gov/pubmed/34659364 http://dx.doi.org/10.3389/fgene.2021.743665 |
Ejemplares similares
-
WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting
por: Zhang, Zhen-Wei, et al.
Publicado: (2021) -
GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder
por: Li, Lei, et al.
Publicado: (2021) -
Predicting miRNA-Disease Associations Based on Heterogeneous Graph Attention Networks
por: Ji, Cunmei, et al.
Publicado: (2021) -
Improved Pre-miRNAs Identification Through Mutual Information of Pre-miRNA Sequences and Structures
por: Fu, Xiangzheng, et al.
Publicado: (2019) -
Regulation of miRNA 219 and miRNA Clusters 338 and 17-92 in Oligodendrocytes
por: de Faria Jr., Omar, et al.
Publicado: (2012)