SSAM-lite: A Light-Weight Web App for Rapid Analysis of Spatially Resolved Transcriptomics Data.
- Published in:
- Frontiers in Genetics, 2022, v. 13, p. 1, doi. 10.3389/fgene.2022.785877
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- Publication type:
- Article
Works by Tiesmeyer, Sebastian
Results: 7
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Cell segmentation-free inference of cell types from in situ transcriptomics data.
- Published in:
- Nature Communications, 2021, v. 12, p. 1, doi. 10.1038/s41467-021-23807-4
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- Publication type:
- Article
3
Author Correction: Cell segmentation-free inference of cell types from in situ transcriptomics data.
- Published in:
- 2021
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- Publication type:
- Correction Notice
4
Cell segmentation-free inference of cell types from in situ transcriptomics data.
- Published in:
- Nature Communications, 2021, v. 12, n. 1, p. 1, doi. 10.1038/s41467-021-23807-4
- By:
- Publication type:
- Article
5
Cell segmentation-free inference of cell types from in situ transcriptomics data.
- Published in:
- Nature Communications, 2021, v. 12, n. 1, p. 1, doi. 10.1038/s41467-021-23807-4
- By:
- Publication type:
- Article
6
Sainsc: A Computational Tool for Segmentation‐Free Analysis of In Situ Capture Data (Small Methods 5/2025).
- Published in:
- Small Methods, 2025, v. 9, n. 5, p. 1, doi. 10.1002/smtd.202570036
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- Publication type:
- Article
7
Sainsc: A Computational Tool for Segmentation‐Free Analysis of In Situ Capture Data.
- Published in:
- Small Methods, 2025, v. 9, n. 5, p. 1, doi. 10.1002/smtd.202401123
- By:
- Publication type:
- Article