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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Methods Online
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

Internet

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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