Cargando…
DBMDA: A Unified Embedding for Sequence-Based miRNA Similarity Measure with Applications to Predict and Validate miRNA-Disease Associations
MicroRNAs (miRNAs) play a critical role in human diseases. Determining the association between miRNAs and disease contributes to elucidating the pathogenesis of liver diseases and seeking the effective treatment method. Despite great recent advances in the field of the associations between miRNAs an...
Autores principales: | Zheng, Kai, You, Zhu-Hong, Wang, Lei, Zhou, Yong, Li, Li-Ping, Li, Zheng-Wei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Gene & Cell Therapy
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6957846/ https://www.ncbi.nlm.nih.gov/pubmed/31931344 http://dx.doi.org/10.1016/j.omtn.2019.12.010 |
Ejemplares similares
-
Integrative Analysis of miRNA-mRNA and miRNA-miRNA Interactions
por: Guo, Li, et al.
Publicado: (2014) -
Comparative analysis of similarity measurements in miRNAs with applications to miRNA-disease association predictions
por: Chen, Hailin, et al.
Publicado: (2020) -
LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities
por: Wang, Lei, et al.
Publicado: (2019) -
Combined embedding model for MiRNA-disease association prediction
por: Liu, Bailong, et al.
Publicado: (2021) -
A path-based measurement for human miRNA functional similarities using miRNA-disease associations
por: Ding, Pingjian, et al.
Publicado: (2016)