ArticleMolecular systems biology2022
Vesalius: high-resolution in silico anatomization of spatial transcriptomic data using image analysis.
Article in Molecular systems biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 24 citations in OpenAlex.
- Multicellular origins of murine ovarian inflammaging.Communications biology · 2026Article
- Translating spatial transcriptomic signatures in adenosquamous carcinoma into bulk prognostic biomarkers in lung adenocarcinoma: a bottom-up approach.NPJ precision oncology · 2026Article
- Multi-scale and multi-context interpretable mapping of cell states across heterogeneous spatial samples.Nature communications · 2025Article
- SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution.BMC bioinformatics · 2025Article
- Rethinking GWAS: how lessons from genetic screens and artificial intelligence could reveal biological mechanisms.Bioinformatics (Oxford, England) · 2025Article
- Article
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- Discovery and generalization of tissue structures from spatial omics data.Cell reports methods · 2024Article
- Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression.Briefings in bioinformatics · 2024Article
- Technical Advances and Applications of Spatial Transcriptomics.GEN biotechnology · 2023Article
- Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering.Nature communications · 2023Article
- Article
- Vesalius: high-resolution in silico anatomization of spatial transcriptomic data using image analysis.Molecular systems biology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Characterization of tissue architecture promises to deliver insights into development, cell communication, and disease. In silico spatial domain retrieval methods have been developed for spatial transcriptomics (ST) data assuming transcriptional similarity of neighboring barcodes. However, domain retrieval approaches with this assumption cannot work in complex tissues composed of multiple cell types. This task becomes especially challenging in cellular resolution ST methods. We developed Vesalius to decipher tissue anatomy from ST data by applying image processing technology. Vesalius uniquely detected territories composed of multiple cell types and successfully recovered tissue structures in high-resolution ST data including in mouse brain, embryo, liver, and colon. Utilizing this tissue architecture, Vesalius identified tissue morphology-specific gene expression and regional specific gene expression changes for astrocytes, interneuron, oligodendrocytes, and entorhinal cells in the mouse brain.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.