ArticleBiophysics reports2022
Spatial transcriptomics: new dimension of understanding biological complexity.
Article in Biophysics reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- Single-cell TCR mapping reveals spatially coordinated T cell states in head and neck cancer.Science immunology · 2026Article
- CTFacTomo: Reconstructing 3D spatial structures of RNA tomography transcriptomes by collapsed tensor factorization.PLoS computational biology · 2026Article
- Spatial Transcriptomics Decodes Breast Cancer Microenvironment Heterogeneity: From Multidimensional Dynamic Profiling to Precision Therapy Blueprint Construction.Biomolecules · 2025Review
- Exploring diet-microbiota interactions and therapeutic nutrition management in inflammatory bowel disease.Biophysics reports · 2025Article
- ST-GEARS: Advancing 3D downstream research through accurate spatial information recovery.Nature communications · 2024Article
- Transcriptome studies of congenital heart diseases: identifying current gaps and therapeutic frontiers.Frontiers in genetics · 2023Review
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
Cells and tissues are exquisitely organized in a complex but ordered manner to form organs and bodies so that individuals can function properly. The spatial organization and tissue architecture represent a keynote property underneath all living organisms. Molecular architecture and cellular composition within intact tissues play a vital role in a variety of biological processes, such as forming the complicated tissue functionality, precise regulation of cell transition in all living activities, consolidation of central nervous system, cellular responses to immunological and pathological cues. To explore these biological events at a large scale and fine resolution, a genome-wide understanding of spatial cellular changes is essential. However, previous bulk RNA sequencing and single-cell RNA sequencing technologies could not obtain the important spatial information of tissues and cells, despite their ability to detect high content transcriptional changes. These limitations have prompted the development of numerous spatially resolved technologies which provide a new dimension to interrogate the regional gene expression, cellular microenvironment, anatomical heterogeneity and cell-cell interactions. Since the advent of spatial transcriptomics, related works that use these technologies have increased rapidly, and new methods with higher throughput and resolution have grown quickly, all of which hold great promise to accelerate new discoveries in understanding the biological complexity. In this review, we briefly discussed the historical evolution of spatially resolved transcriptome. We broadly surveyed the representative methods. Furthermore, we summarized the general computational analysis pipeline for the spatial gene expression data. Finally, we proposed perspectives for technological development of spatial multi-omics.
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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.