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DeepST: identifying spatial domains in spatial transcriptomics by deep learning
Recent advances in spatial transcriptomics (ST) have brought unprecedented opportunities to understand tissue organization and function in spatial context. However, it is still challenging to precisely dissect spatial domains with similar gene expression and histology in situ. Here, we present DeepS...
Autores principales: | Xu, Chang, Jin, Xiyun, Wei, Songren, Wang, Pingping, Luo, Meng, Xu, Zhaochun, Yang, Wenyi, Cai, Yideng, Xiao, Lixing, Lin, Xiaoyu, Liu, Hongxin, Cheng, Rui, Pang, Fenglan, Chen, Rui, Su, Xi, Hu, Ying, Wang, Guohua, Jiang, Qinghua |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825193/ https://www.ncbi.nlm.nih.gov/pubmed/36250636 http://dx.doi.org/10.1093/nar/gkac901 |
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