ReviewMolecular and cellular biochemistry2026
Advances in the application of spatial transcriptomics in understanding development and disease.
Review in Molecular and cellular biochemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Convergent methodologies in prosthetic joint infection research: integrating transdisciplinary approaches to understand and prevent biofilm-driven failure of orthopaedic prostheses.Journal of medical microbiology · 2026Review
- Transitional cell states at the crossroads of development, disease, and repair-regeneration.Physiological reviews · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Spatial transcriptomics (In this review, 'spatial transcriptomics' (ST) is employed as a overarching term, encompassing two distinct concepts. Firstly, 'tissue-level ST' refers to the capture of tissue samples at a resolution of 10-100 μm, encompassing 1-20 cells. Secondly, 'spatially resolved single-cell transcriptomics' (sc-ST) involves the analysis of individual cells or nuclei, with each sequencing unit measuring ≤ 2 μm) fuses high-throughput sequencing with positional information to map gene expression within intact tissues. By preserving spatial context, the technology uncovers cell types, signaling circuits and regulatory networks that drive organogenesis, differentiation and disease. Here we synthesize recent methodological advances and their application to developmental and clinical questions. The term "Spatial Transcriptomics" as used in this paper comprehensively encompasses all sequencing technologies that preserve spatial coordinates, including multimodal data such as transcriptomics (RNA), genomics (DNA), epigenomics (ATAC, CUT&Tag), and translationalomics (Ribo-seq).
Indexed as
Identifiers
41511721What 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.