Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning

Spatially resolved transcriptomics provides a new way to define spatial contexts and understand the pathogenesis of complex human diseases. Although some computational frameworks can characterize spatial context via various clustering methods, the detailed spatial architectures and functional zonati...

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Bibliographic Details

Published in:	Computational and Structural Biotechnology Journal
Main Authors:	Yuzhou Chang, Fei He, Juexin Wang, Shuo Chen, Jingyi Li, Jixin Liu, Yang Yu, Li Su, Anjun Ma, Carter Allen, Yu Lin, Shaoli Sun, Bingqiang Liu, José Javier Otero, Dongjun Chung, Hongjun Fu, Zihai Li, Dong Xu, Qin Ma
Format:	Article
Language:	English
Published:	Elsevier 2022-01-01
Subjects:	Spatial transcriptomics Deep learning Tissue architecture visualization and identification
Online Access:	http://www.sciencedirect.com/science/article/pii/S2001037022003646