Cargando…
Predict multi-type drug–drug interactions in cold start scenario
BACKGROUND: Prediction of drug–drug interactions (DDIs) can reveal potential adverse pharmacological reactions between drugs in co-medication. Various methods have been proposed to address this issue. Most of them focus on the traditional link prediction between drugs, however, they ignore the cold-...
Autores principales: | Liu, Zun, Wang, Xing-Nan, Yu, Hui, Shi, Jian-Yu, Dong, Wen-Min |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851772/ https://www.ncbi.nlm.nih.gov/pubmed/35172712 http://dx.doi.org/10.1186/s12859-022-04610-4 |
Ejemplares similares
-
Cold-Start Problems in Data-Driven Prediction of Drug–Drug Interaction Effects
por: Dewulf, Pieter, et al.
Publicado: (2021) -
Predicting Drug-Target Interactions via Within-Score and Between-Score
por: Shi, Jian-Yu, et al.
Publicado: (2015) -
Mitigating cold-start problems in drug-target affinity prediction with interaction knowledge transferring
por: Nguyen, Tri Minh, et al.
Publicado: (2022) -
A unified solution for different scenarios of predicting drug-target interactions via triple matrix factorization
por: Shi, Jian-Yu, et al.
Publicado: (2018) -
Multi-type feature fusion based on graph neural network for drug-drug interaction prediction
por: He, Changxiang, et al.
Publicado: (2022)