Cargando…
A unified frame of predicting side effects of drugs by using linear neighborhood similarity
BACKGROUND: Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been...
Autores principales: | Zhang, Wen, Yue, Xiang, Liu, Feng, Chen, Yanlin, Tu, Shikui, Zhang, Xining |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751767/ https://www.ncbi.nlm.nih.gov/pubmed/29297371 http://dx.doi.org/10.1186/s12918-017-0477-2 |
Ejemplares similares
-
Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information
por: Zhang, Wen, et al.
Publicado: (2017) -
An Iterative Method for Predicting Essential Proteins Based on Multifeature Fusion and Linear Neighborhood Similarity
por: Zhu, Xianyou, et al.
Publicado: (2022) -
Opinion Dynamics and Unifying Principles: A Global Unifying Frame
por: Galam, Serge
Publicado: (2022) -
Prediction of the Drug–Drug Interaction Types with the Unified Embedding Features from Drug Similarity Networks
por: Yan, Xiao-Ying, et al.
Publicado: (2021) -
A neighborhood-regularization method leveraging multiview data for predicting the frequency of drug–side effects
por: Wang, Lin, et al.
Publicado: (2023)