ReviewCells2023
Spatial Transcriptomic Technologies.
Review in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 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
79 citing papers in PubMed, 100 citations in OpenAlex.
- Spatial Proteomics as a Potential Decision-Support Layer for Early Melanoma: A Narrative Review.International journal of dermatology · 2026Review
- CoexpressDeconvolve enables reference-free single-cell-resolution deconvolution from spot-based spatial transcriptomics.iScience · 2026Article
- Deep Learning-Assisted Prioritization of Candidate Drug Targets in Tumors Using Spatial Multi-Omics.Biology · 2026Review
- Reprogramming Autophagy to Strengthen Antitumour Immunity: Advances in Immunotherapeutic Strategies.Immunology · 2026Review
- Spatial transcriptomic profiling reveals fibroblast and inflammatory signatures in calcinosis of chronic cutaneous lupus.JID innovations : skin science from molecules to population health · 2026Article
- Amplification bias in sequencing-based spatial transcriptomics: sources, mechanisms, impacts, and mitigation strategies.Briefings in bioinformatics · 2026Review
- Review
- Multi-Omics-Guided Design and Safety Engineering of Nucleic Acid Therapeutics: From Molecular Perturbation to Predictive Toxicology and Precision Translation.Chemical biology & drug design · 2026Review
- Review
- Spatial transcriptomics in ovarian biology technologies: computational challenges, and biological insights.Reproduction (Cambridge, England) · 2026Review
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- A Counterfactual Framework for Directional Cell-Cell Interaction Analysis in Spatial Transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Diet-Microbiota-Immune Interactions in Hepatocellular Carcinoma: An Immunometabolic and Spatial Perspective.Nutrients · 2026Review
- Imaging-Guided Omics Technologies for Resolving Rare Cancer States and Advancing Nanomedicine.Nano letters · 2026Review
- Review
- Review
- Zebrafish Models of Parkinson's Disease: From Pathogenesis to Drug Discovery.International journal of molecular sciences · 2026Review
- Artificial Intelligence for Spatial Immunometabolic Analysis of the Tumor Microenvironment: Current Evidence and Future Directions.Current issues in molecular biology · 2026Review
- Defining the tumor microenvironment of non-small cell lung cancer.Immunology and cell biology · 2026Review
- Global scientific growth and thematic development of spatial transcriptomics in oncology research.Discover oncology · 2026Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a range of diseases, including cancer. A variety of spatial technologies have been developed and/or commercialized, differing in spatial resolution, sensitivity, multiplexing capability, throughput and coverage. In this paper, we review key enabling spatial transcriptomic technologies and their applications as well as the perspective of the techniques and new emerging technologies that are developed to address current limitations of spatial methodologies. In addition, we describe how spatial transcriptomics data can be integrated with other omics modalities, complementing other methods in deciphering cellar interactions and phenotypes within tissues as well as providing novel insight into tissue organization.
Indexed as
Identifiers
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.