Cargando…
Cluster correlation based method for lncRNA-disease association prediction
BACKGROUND: In recent years, increasing evidences have indicated that long non-coding RNAs (lncRNAs) are deeply involved in a wide range of human biological pathways. The mutations and disorders of lncRNAs are closely associated with many human diseases. Therefore, it is of great importance to predi...
Autores principales: | Yuan, Qianqian, Guo, Xingli, Ren, Yang, Wen, Xiao, Gao, Lin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216352/ https://www.ncbi.nlm.nih.gov/pubmed/32393162 http://dx.doi.org/10.1186/s12859-020-3496-8 |
Ejemplares similares
-
A novel computational model for predicting potential LncRNA-disease associations based on both direct and indirect features of LncRNA-disease pairs
por: Xiao, Yubin, et al.
Publicado: (2020) -
A Network Based Method for Analysis of lncRNA-Disease Associations and Prediction of lncRNAs Implicated in Diseases
por: Yang, Xiaofei, et al.
Publicado: (2014) -
Prediction of plant lncRNA by ensemble machine learning classifiers
por: Simopoulos, Caitlin M. A., et al.
Publicado: (2018) -
IDSSIM: an lncRNA functional similarity calculation model based on an improved disease semantic similarity method
por: Fan, Wenwen, et al.
Publicado: (2020) -
A random forest based computational model for predicting novel lncRNA-disease associations
por: Yao, Dengju, et al.
Publicado: (2020)