Cargando…
Fusing literature and full network data improves disease similarity computation
BACKGROUND: Identifying relatedness among diseases could help deepen understanding for the underlying pathogenic mechanisms of diseases, and facilitate drug repositioning projects. A number of methods for computing disease similarity had been developed; however, none of them were designed to utilize...
Autores principales: | Li, Ping, Nie, Yaling, Yu, Jingkai |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5006367/ https://www.ncbi.nlm.nih.gov/pubmed/27578323 http://dx.doi.org/10.1186/s12859-016-1205-4 |
Ejemplares similares
-
An Effective Method to Identify Shared Pathways and Common Factors among Neurodegenerative Diseases
por: Li, Ping, et al.
Publicado: (2015) -
Mining breast cancer genes with a network based noise-tolerant approach
por: Nie, Yaling, et al.
Publicado: (2013) -
Fused multi-modal similarity network as prior in guiding brain imaging genetic association
por: He, Bing, et al.
Publicado: (2023) -
Fusing similarity rankings in ligand-based virtual screening
por: Willett, Peter
Publicado: (2013) -
An improved fused feature residual network for 3D point cloud data
por: Gezawa, Abubakar Sulaiman, et al.
Publicado: (2023)