SPACEL: deep learning-based characterization of spatial transcriptome architectures
SPACEL: deep learning-based characterization of spatial transcriptome architectures
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Author / Creator
Xu, Hao , Wang, Shuyan , Fang, Minghao , Luo, Songwen , Chen, Chunpeng , Wan, Siyuan , Wang, Rirui , Tang, Meifang , Xue, Tian , Li, Bin , Lin, Jun and Qu, Kun
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publication information
Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
Spatial transcriptomics (ST) technologies detect mRNA expression in single cells/spots while preserving their two-dimensional (2D) spatial coordinates, allowing researchers to study the spatial distribution of the transcriptome in tissues; however, joint analysis of multiple ST slices and aligning them to construct a three-dimensional (3D) stack of...
Alternative Titles
Full title
SPACEL: deep learning-based characterization of spatial transcriptome architectures
Authors, Artists and Contributors
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_d549905629d7462bac28a9cbcda15663
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d549905629d7462bac28a9cbcda15663
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-023-43220-3
