ArticleNature biotechnology2022
Super-resolved spatial transcriptomics by deep data fusion.
Article in Nature biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers.
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Who cites it
113 citing papers in PubMed.
- Benchmarking segmentation methods for spatial transcriptomics.Nature methods · 2026Article
- Spatial transcriptomics ofiScience · 2026Article
- From descriptive to generative: foundation-model approaches for spatial transcriptomics.Briefings in bioinformatics · 2026Review
- Image-guided spatial omics enhancement reveals hidden spatial microstructures.Bioinformatics (Oxford, England) · 2026Article
- Sequencing-free spatial profiling of post-transcriptional regulation in fresh tissues using nanoneedle arrays.Nature biomedical engineering · 2026Article
- Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging.Cell genomics · 2026Review
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
- DeSpaST: deconvoluting spatial transcriptomics signals to cell-level resolution using histology images.Briefings in bioinformatics · 2026Article
- STRESS: spatial transcriptomics resolution enhancing method based on the state-space model.Briefings in bioinformatics · 2026Article
- MGCL-ST: multi-view graph contrastive learning for spatial transcriptomics imputation.Genome medicine · 2026Article
- Pan-cancer analysis of spatial transcriptomics reveals heterogeneous tumor spatial microenvironment.Cell reports. Medicine · 2026Article
- Decoding spatial transcriptomics across multicellular and subcellular resolutions.Nature communications · 2026Article
- Single-cell spatial transcriptomic analysis of human skin anatomy.Nature genetics · 2026Article
- FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis.Nature communications · 2026Article
- Hist2Cell: Deciphering fine-grained cellular architectures from histology images.Cell genomics · 2026Article
- Application of artificial intelligence in oral potentially malignant disorders: current opinions and future barriers.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Advances in predicting omics profiles from imaging data.Briefings in bioinformatics · 2026Review
- Pixel2Gene enables histology-guided reconstruction and prediction of spatial gene expression.bioRxiv : the preprint server for biology · 2026Article
- Image Fusion for Super-Resolution Mass Spectrometry Imaging of Plant Tissue.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- The interpretable multimodal dimension reduction framework SpaHDmap enhances resolution in spatial transcriptomics.Nature cell biology · 2026Article
53 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.
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Registered trials
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.