ReviewNature reviews. Genetics2026
Spatial architecture of development and disease.
Review in Nature reviews. Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- SpatialZoomer: multi-scale feature analysis of spatial transcriptomics.Nature biomedical engineering · 2026Article
- Unveiling the role of spatial transcriptomics in the analysis of the tumor immune microenvironment (Review).International journal of molecular medicine · 2026Review
- Computational approaches for multimodal lineage tracing.Nature reviews. Genetics · 2026Review
- SpaCEy links spatial tissue patterns to clinical outcomes using explainable graph neural networks.Nature communications · 2026Article
- RNA-aware tissue preservation workflows for high-quality spatial transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- DPAS-Graph: adaptive spatial-feature relation learning for spatial RNA-to-protein prediction and virtual protein profiling.Briefings in bioinformatics · 2026Article
- DNA Methylation as a Programmable Information Layer: From Molecular Marks to Disease State Engineering.International journal of molecular sciences · 2026Review
- NicheProt: Cell-type-resolved proteomics of tissue compartments.Science advances · 2026Article
- Structural-information guided fusion for spatial domain identification from spatial transcriptomics.Bioinformatics (Oxford, England) · 2026Article
- Spatiotemporal cell type deconvolution leveraging tissue structure.Research square · 2026Article
- Kinemomics: spatiotemporal morphodynamic mapping of ventricular kinematic subpopulations in organotypic fetal heart slices.bioRxiv : the preprint server for biology · 2026Article
- DNA Methylation Dynamics in Development and Disease: Insights from Zebrafish Models.Biomedicines · 2026Review
- Uncovering Immune Niches in Health and Disease Using Spatial Transcriptomics.European journal of immunology · 2026Review
- MINGL Quantifies Borders, Gradients, and Heterogeneity in Multicellular Tissue Organization.bioRxiv : the preprint server for biology · 2026Article
- Spatiotemporal cell type deconvolution leveraging tissue structure.bioRxiv : the preprint server for biology · 2026Article
- Spatially resolved gene expression analysis illuminates location-specific functions in the reef-building coral Pocillopora acuta.PloS one · 2026Article
- Bioinks in systems biology: integrating biomaterial design with cellular network modelling for predictive biofabrication.Frontiers in bioengineering and biotechnology · 2026Review
- Hydrogel array patterning using 3D-printed microfluidic inserts to control cell-cell and cell-ECM interactions.bioRxiv : the preprint server for biology · 2025Article
- Query-driven generative AI synthesizes multi-modal spatial omics from histology.bioRxiv : the preprint server for biology · 2025Article
- Reproducibility of digital pathology features extracted from deep learning and foundational AI models on sequential tissue slides.Scientific reports · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tissue architecture is a product of a multilayered molecular landscape, where even subtle disruptions in the spatial context can initiate or reflect disease processes. Recent advances in high-throughput spatial omics technologies have enabled the investigation of this complexity in stunning detail, providing groundbreaking insights into how spatial molecular organization shapes health and disease. Spatial analysis empowers the discovery of developmental and disease-associated molecular signatures, cell states and multicellular niches, as well as the evaluation of disease heterogeneity within and across organs. This Review examines spatially resolved pathological molecular alterations in a wide range of disease processes, such as developmental disorders, tumorigenesis, fibrosis and injury responses, neurodegeneration, infection and inflammation, through the lens of these universal biological frameworks. We discuss challenges, opportunities and promising examples in advancing these technologies to clinical applications, including the increasing importance of artificial intelligence. Finally, we explore possible avenues for a more comprehensive, multidimensional assessment of tissues.
Indexed as
Identifiers
41028908What 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.