ReviewFrontiers in genetics2021
Analysis and Visualization of Spatial Transcriptomic Data.
Review in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 69 citations in OpenAlex.
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
- Applications of large-scale artificial intelligence models in bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Advances in Spatial Transcriptomics in Bone.Current osteoporosis reports · 2026Review
- Deciphering immunosuppressive niches by spatial single-cell proteomics: spatial interaction networks and translational opportunities.Frontiers in immunology · 2026Review
- Mapping safety in space: the emerging role of spatial transcriptomics in safe drug development.Frontiers in toxicology · 2026Review
- AINR: attention-guided implicit neural representations for spatial domain identification in spatial transcriptomics.Bioinformatics advances · 2026Article
- Transforming multi-omics data into images for disease classification: A review of techniques and tools.Journal of pathology informatics · 2026Review
- Spatial transcriptomics reveal heterogeneous cell‒cell interactions among brain regions in cuprizone model consistent with multiple sclerosis lesions.Frontiers in bioinformatics · 2026Article
- Spatial Transcriptomics of Adipose Tissue: Technologies, Applications, and Challenges.Journal of obesity & metabolic syndrome · 2025Review
- The xIV-LDDMM toolkit of image-varifold based technologies for mapping 3D images and spatial-omics across scales.Communications biology · 2025Article
- CytoSpatio: Learning cell type spatial relationships using multirange, multitype point process models.PLoS computational biology · 2025Article
- SOAR elucidates biological insights and empowers drug discovery through spatial transcriptomics.Science advances · 2025Article
- spatialGE Is a User-Friendly Web Application That Facilitates Spatial Transcriptomics Data Analysis.Cancer research · 2025Article
- Batch correcting single-cell spatial transcriptomics count data with Crescendo improves visualization and detection of spatial gene patterns.Genome biology · 2025Article
- A quantitative spatial cell-cell colocalizations framework enabling comparisons between in vitro assembloids and pathological specimens.Nature communications · 2025Article
- Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics.Nature communications · 2025Article
- Histopathologic Analysis of Human Kidney Spatial Transcriptomics Data: Toward Precision Pathology.The American journal of pathology · 2025Article
- Spatial Transcriptomics: Integrating Morphology and Molecular Mechanisms of Kidney Diseases.The American journal of pathology · 2025Review
- Computational Strategies and Algorithms for Inferring Cellular Composition of Spatial Transcriptomics Data.Genomics, proteomics & bioinformatics · 2024Review
- SpatialOne: end-to-end analysis of visium data at scale.Bioinformatics (Oxford, England) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent technological innovation that measures transcriptomic information while preserving spatial information. Spatial transcriptomic data can be generated in several ways. RNA molecules are measured by
Indexed as
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What OpenQuestion holds
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.