Cargando…
A novel computational model for predicting potential LncRNA-disease associations based on both direct and indirect features of LncRNA-disease pairs
BACKGROUND: Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) are closely associated with human diseases, and it is useful for the diagnosis and treatment of diseases to get the relationships between lncRNAs and diseases. Due to the high costs and time complexity of traditio...
Autores principales: | Xiao, Yubin, Xiao, Zheng, Feng, Xiang, Chen, Zhiping, Kuang, Linai, Wang, Lei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709313/ https://www.ncbi.nlm.nih.gov/pubmed/33267800 http://dx.doi.org/10.1186/s12859-020-03906-7 |
Ejemplares similares
-
Cluster correlation based method for lncRNA-disease association prediction
por: Yuan, Qianqian, et al.
Publicado: (2020) -
ICLRBBN: a tool for accurate prediction of potential lncRNA disease associations
por: Wang, Yuqi, et al.
Publicado: (2020) -
A Novel Probability Model for LncRNA–Disease Association Prediction Based on the Naïve Bayesian Classifier
por: Yu, Jingwen, et al.
Publicado: (2018) -
A Novel Approach for Predicting Disease-lncRNA Associations Based on the Distance Correlation Set and Information of the miRNAs
por: Zhao, Haochen, et al.
Publicado: (2018) -
The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs, and Diseases
por: Yang, Haixiu, et al.
Publicado: (2017)