Cargando…
TranSynergy: Mechanism-driven interpretable deep neural network for the synergistic prediction and pathway deconvolution of drug combinations
Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the experimental investigation of all drug combinations to become costly and time-consuming. Computationa...
Autores principales: | Liu, Qiao, Xie, Lei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906476/ https://www.ncbi.nlm.nih.gov/pubmed/33577560 http://dx.doi.org/10.1371/journal.pcbi.1008653 |
Ejemplares similares
-
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning
por: Preuer, Kristina, et al.
Publicado: (2018) -
Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis
por: Chen, Yanshuo, et al.
Publicado: (2022) -
SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets
por: Zheng, Shuyu, et al.
Publicado: (2022) -
DeepTraSynergy: drug combinations using multimodal deep learning with transformers
por: Rafiei, Fatemeh, et al.
Publicado: (2023) -
DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra
por: Li, Da-Wei, et al.
Publicado: (2021)