Spatial Data Alignment
Spatial Data Alignment is a computational method that integrates spatially resolved molecular datasets by establishing precise positional correspondences across multiple tissue sections or modalities, enabling joint analysis of spatial single-cell omics data through geometric transformation and feature matching.
44
Publications
2.2K
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284
Authors
116
Institutions
Publications per year
2017–2026
27
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SpatialData: an open and universal data framework for spatial omics
Luca Marconato, Giovanni Palla, Kevin A. Yamauchi et al. · Nature Methods · 2024 · 186 citations · Full text
High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE
Milad R. Vahid, Erin L. Brown, Chloé B. Steen et al. · Nature Biotechnology · 2023 · 182 citations · Full text
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection
Junjie Yan, Yingfei Liu, Jianjian Sun et al. · 2023 · 138 citations
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Stanford Medicine
Stanford, United States
3 h-index
3 publications
298 citations
Stanford University
Stanford, United States
3 h-index
16 publications
1.7K citations

Helmholtz Zentrum München
Munich, Germany
3 h-index
15 publications
1.7K citations
Princeton University
Princeton, United States
3 h-index
5 publications
248 citations
Technical University of Munich
Munich, Germany
3 h-index
8 publications
832 citations

Wellcome Sanger Institute
Cambridge, United Kingdom
3 h-index
5 publications
494 citations
Aix-Marseille Université
Marseille, France
2 h-index
14 publications
238 citations
ETH Zurich
Zurich, Switzerland
2 h-index
2 publications
218 citations
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Repository · 3 publications · 67 citations
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2 publications · 176 citations
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2 publications · 274 citations
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2 publications · 33 citations
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2 publications · 58 citations
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