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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
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 |
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