Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning
Published in Computational and Structural Biotechnology Journal, 2022
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 zonation often cannot b…
Recommended citation: Yuzhou Chang, Fei He, Juexin Wang, Shuo Chen, Jingyi Li, Jixin Liu, Yang Yu, Li Su, et al.. (2022). "Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning" Computational and Structural Biotechnology Journal.
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