ReviewComputational and structural biotechnology journal2023
A guidebook of spatial transcriptomic technologies, data resources and analysis approaches.
Review in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 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
49 citing papers in PubMed, 65 citations in OpenAlex.
- Decoding Skeletal Biology Through Transcriptomics: Insights from Bulk, Single-Cell, Spatial, and Multi-Omics Approaches.International journal of molecular sciences · 2026Review
- Article
- CoexpressDeconvolve enables reference-free single-cell-resolution deconvolution from spot-based spatial transcriptomics.iScience · 2026Article
- Cardiac immunity and heart repair: Mechanism, challenge, and future direction.Chinese medical journal · 2026Review
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Review
- Spatial transcriptomics in epilepsy research: Early successes, opportunities, and challenges.Epilepsia · 2026Article
- Single-Cell and Spatial Omics: Methods and Applications.MedComm · 2026Review
- Transcriptional and functional profiles of muscarinic receptor-expressing neurons in primate lateral prefrontal and anterior cingulate cortices.Communications biology · 2026Article
- Reconstructing 3D transcriptional organization from spatial transcriptomics reveals consistent oncogenic translocations and developmental dynamics.Briefings in bioinformatics · 2026Article
- Single-Cell Multi-Omics Profiling of Human Septal Myectomy Tissue: Toward Precision Medicine in Obstructive Hypertrophic Cardiomyopathy.Journal of personalized medicine · 2026Review
- transFusion: a novel comprehensive platform for integration analysis of single-cell and spatial transcriptomics.Bioinformatics (Oxford, England) · 2026Article
- Spatial omics for profiling the dynamic tumor microenvironment.Clinical & translational immunology · 2026Review
- Protease-Free RNAscope and Sequential Immunofluorescence Methods for Manual Codetection of RNAs and Proteins.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Spatial Modeling of Tissues for Morphogenic Field Analysis.bioRxiv : the preprint server for biology · 2025Article
- Advancing Intervertebral Disc Biology via Omics: Implications for Nucleus Pulposus Progenitor Cell-Based Regeneration.JOR spine · 2025Review
- Spatial Transcriptomics of Adipose Tissue: Technologies, Applications, and Challenges.Journal of obesity & metabolic syndrome · 2025Review
- Efficient integration of spatial omics data for joint domain detection, matching, and alignment with stMSA.Genome research · 2025Article
- Spatial Transcriptomics to Study Virus-Host Interactions.Annual review of virology · 2025Review
- A graph neural network-based spatial multi-omics data integration method for deciphering spatial domains.PLoS computational biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in transcriptomic technologies have deepened our understanding of the cellular gene expression programs of multicellular organisms and provided a theoretical basis for disease diagnosis and therapy. However, both bulk and single-cell RNA sequencing approaches lose the spatial context of cells within the tissue microenvironment, and the development of spatial transcriptomics has made overall bias-free access to both transcriptional information and spatial information possible. Here, we elaborate development of spatial transcriptomic technologies to help researchers select the best-suited technology for their goals and integrate the vast amounts of data to facilitate data accessibility and availability. Then, we marshal various computational approaches to analyze spatial transcriptomic data for various purposes and describe the spatial multimodal omics and its potential for application in tumor tissue. Finally, we provide a detailed discussion and outlook of the spatial transcriptomic technologies, data resources and analysis approaches to guide current and future research on spatial transcriptomics.
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.