Cargando…
Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning
BACKGROUND: Development of new drugs is a time-consuming and costly process, and the cost is still increasing in recent years. However, the number of drugs approved by FDA every year per dollar spent on development is declining. Drug repositioning, which aims to find new use of existing drugs, attra...
Autores principales: | Wang, Ran, Li, Shuai, Cheng, Lixin, Wong, Man Hon, Leung, Kwong Sak |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912989/ https://www.ncbi.nlm.nih.gov/pubmed/31839008 http://dx.doi.org/10.1186/s12859-019-3283-6 |
Ejemplares similares
-
NTD-DR: Nonnegative tensor decomposition for drug repositioning
por: Jamali, Ali Akbar, et al.
Publicado: (2022) -
Predicting Drug–Gene–Disease Associations by Tensor Decomposition for Network-Based Computational Drug Repositioning
por: Kim, Yoonbee, et al.
Publicado: (2023) -
Long non-coding RNA pairs to assist in diagnosing sepsis
por: Zheng, Xubin, et al.
Publicado: (2021) -
Deciphering associations between gut microbiota and clinical factors using microbial modules
por: Wang, Ran, et al.
Publicado: (2023) -
iDrug: Integration of drug repositioning and drug-target prediction via cross-network embedding
por: Chen, Huiyuan, et al.
Publicado: (2020)