Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data

Drug screening data from massive bulk gene expression databases can be analyzed to determine the optimal clinical application of cancer drugs. The growing amount of single-cell RNA sequencing (scRNA-seq) data also provides insights into improving therapeutic effectiveness by helping to study the het...

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Detalles Bibliográficos
Autores principales: Chen, Junyi, Wang, Xiaoying, Ma, Anjun, Wang, Qi-En, Liu, Bingqiang, Li, Lang, Xu, Dong, Ma, Qin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618578/
https://www.ncbi.nlm.nih.gov/pubmed/36310235
http://dx.doi.org/10.1038/s41467-022-34277-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618578/
https://www.ncbi.nlm.nih.gov/pubmed/36310235
http://dx.doi.org/10.1038/s41467-022-34277-7

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