Miscell: An efficient self-supervised learning approach for dissecting single-cell transcriptome

We developed Miscell, a self-supervised learning approach with deep neural network as latent feature encoder for mining information from single-cell transcriptomes. We demonstrated the capability of Miscell with canonical single-cell analysis tasks including delineation of single-cell clusters and i...

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Detalles Bibliográficos
Autores principales: Shen, Hongru, Li, Yang, Feng, Mengyao, Shen, Xilin, Wu, Dan, Zhang, Chao, Yang, Yichen, Yang, Meng, Hu, Jiani, Liu, Jilei, Wang, Wei, Zhang, Qiang, Song, Fangfang, Yang, Jilong, Chen, Kexin, Li, Xiangchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529514/
https://www.ncbi.nlm.nih.gov/pubmed/34712916
http://dx.doi.org/10.1016/j.isci.2021.103200

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529514/
https://www.ncbi.nlm.nih.gov/pubmed/34712916
http://dx.doi.org/10.1016/j.isci.2021.103200

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