Spatial Transcriptomics Deconvolution
Spatial Transcriptomics Deconvolution is a computational method that belongs to the class of cell-type deconvolution techniques and specifically enables the inference of cell-type proportions and their spatial distribution within tissue sections by leveraging gene expression profiles from spatially resolved transcriptomics data.
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14K
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329
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Publications per year
2017–2026
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Cell2location maps fine-grained cell types in spatial transcriptomics
Vitalii Kleshchevnikov, Artem Shmatko, Emma Dann et al. · Nature Biotechnology · 2022 · 1.2K citations
Spatial transcriptomics at subspot resolution with BayesSpace
Edward Zhao, Matthew R. Stone, Xing Ren et al. · Nature Biotechnology · 2021 · 1K citations · Full text
Spatial Transcriptomics and In Situ Sequencing to Study Alzheimer’s Disease
Wei-Ting Chen, Ashley Lu, Katleen Craessaerts et al. · Cell · 2020 · 957 citations · Full text
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KTH Royal Institute of Technology
Stockholm, Sweden
10 h-index
42 publications
16.2K citations
Harvard University
Cambridge, United States
9 h-index
18 publications
1.2K citations
Science for Life Laboratory
Stockholm, Sweden
9 h-index
60 publications
19.7K citations

Karolinska Institutet
Stockholm, Sweden
7 h-index
35 publications
5K citations

Chinese Academy of Sciences
Beijing, China
5 h-index
12 publications
1.6K citations
Heidelberg University
Heidelberg, Germany
5 h-index
14 publications
1.5K citations

Johns Hopkins Medicine
Baltimore, United States
4 h-index
15 publications
2.3K citations
Centre for Genomic Regulation
Barcelona, Spain
4 h-index
11 publications
3.2K citations
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22 publications · 3.7K citations
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Repository · 13 publications · 284 citations
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6 publications · 3.3K citations
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5 publications · 597 citations
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4 publications · 187 citations
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