Cargando…
Graph embedding ensemble methods based on the heterogeneous network for lncRNA-miRNA interaction prediction
BACKGROUND: Researchers discover LncRNA–miRNA regulatory paradigms modulate gene expression patterns and drive major cellular processes. Identification of lncRNA-miRNA interactions (LMIs) is critical to reveal the mechanism of biological processes and complicated diseases. Because conventional wet e...
Autores principales: | Zhao, Chengshuai, Qiu, Yang, Zhou, Shuang, Liu, Shichao, Zhang, Wen, Niu, Yanqing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7745483/ https://www.ncbi.nlm.nih.gov/pubmed/33334307 http://dx.doi.org/10.1186/s12864-020-07238-x |
Ejemplares similares
-
Heterogeneous graph inference based on similarity network fusion for predicting lncRNA–miRNA interaction
por: Fan, Yongxian, et al.
Publicado: (2020) -
DeepWalk based method to predict lncRNA-miRNA associations via lncRNA-miRNA-disease-protein-drug graph
por: Yang, Long, et al.
Publicado: (2022) -
Predicting lncRNA-miRNA Interaction via Graph Convolution Auto-Encoder
por: Huang, Yu-An, et al.
Publicado: (2019) -
LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
por: Zhang, Wen, et al.
Publicado: (2019) -
Predicting lncRNA–Protein Interactions by Heterogenous Network Embedding
por: Zhao, Guoqing, et al.
Publicado: (2022)