ReviewJournal of translational medicine2023
Advances in spatial transcriptomics and related data analysis strategies.
Review in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers, 1 of them a synthesis that pooled it.
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
129 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Recent developments in omics studies and artificial intelligence in depression and suicide.Translational psychiatry · 2025Pooled it
- SpaCEy links spatial tissue patterns to clinical outcomes using explainable graph neural networks.Nature communications · 2026Article
- SpaDiff denoises sequence-based spatial transcriptomics via diffusion process.Cell reports methods · 2026Article
- Pan-tumor spatial transcriptomics reveals conserved properties of tumor organization.Cell reports. Medicine · 2026Article
- Deep Learning-Assisted Prioritization of Candidate Drug Targets in Tumors Using Spatial Multi-Omics.Biology · 2026Review
- Spatially guided translation from histology images to transcriptomic profiles using foundation model-driven contrastive learning.PLoS computational biology · 2026Article
- RECQL correlates with immune infiltration and serves as a prognostic biomarker and therapeutic predictor in gastric cancer.Translational cancer research · 2026Article
- SPIDER: spatially integrated denoising via embedding regularization with single cell supervision.Bioinformatics (Oxford, England) · 2026Article
- STAID: A Self-Refining Deep Learning Framework for Spatial Cell-Type Deconvolution with Biologically Informed Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
- Integrated Foodomics Reveals Gut Microbiota-Metabolite-Gene Interactions Associated with the Immunoprotective Effects of Ganoderma lucidum Polysaccharide Peptide.Foods (Basel, Switzerland) · 2026Article
- The applications of single-cell and spatial transcriptomics in neuroscience and brain disorders.Neuroscience and biobehavioral reviews · 2026Review
- Quantifying the spatiotemporal mechanical dynamics of engineered cardiac microbundles.PLoS computational biology · 2026Article
- Standardized metrics for assessment and reproducibility of imaging-based spatial transcriptomics datasets.Nature biotechnology · 2026Article
- ResSAT: enhancing spatial transcriptomics prediction from H&E-stained histology images with an interactive spot transformer.Genome biology · 2026Article
- Delta radiomics for predicting early radiation-induced lung injury after thoracic radiotherapy: a retrospective paired-CT study.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- Optimal gene panel selection for targeted spatial transcriptomics experiments.Nucleic acids research · 2026Article
- Systematic clustering alignment and feature characterization for single-cell omics using ACE-OF-Clust.bioRxiv : the preprint server for biology · 2026Article
69 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spatial transcriptomics technologies developed in recent years can provide various information including tissue heterogeneity, which is fundamental in biological and medical research, and have been making significant breakthroughs. Single-cell RNA sequencing (scRNA-seq) cannot provide spatial information, while spatial transcriptomics technologies allow gene expression information to be obtained from intact tissue sections in the original physiological context at a spatial resolution. Various biological insights can be generated into tissue architecture and further the elucidation of the interaction between cells and the microenvironment. Thus, we can gain a general understanding of histogenesis processes and disease pathogenesis, etc. Furthermore, in silico methods involving the widely distributed R and Python packages for data analysis play essential roles in deriving indispensable bioinformation and eliminating technological limitations. In this review, we summarize available technologies of spatial transcriptomics, probe into several applications, discuss the computational strategies and raise future perspectives, highlighting the developmental potential.
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.