Mapping the transcriptome: Realizing the full potential of spatial data analysis

Zormpas, E., Queen, R., Comber, A. orcid.org/0000-0002-3652-7846 et al. (1 more author) (2023) Mapping the transcriptome: Realizing the full potential of spatial data analysis. Cell, 186 (26). pp. 5677-5689. ISSN 0092-8674

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Item Type: Article
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© 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: spatial data, spatial analysis, omics, spatial transcriptomics, geography, spatial autocorrelation, spatial heterogeneity, modifiable areal unit problem
Dates:
  • Published: 21 December 2023
  • Published (online): 7 December 2023
  • Accepted: 2 November 2023
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 23 Oct 2024 11:05
Last Modified: 23 Oct 2024 11:05
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.cell.2023.11.003
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