ReviewMolecules and cells2020
Mapping Cellular Coordinates through Advances in Spatial Transcriptomics Technology.
Review in Molecules and cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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Who cites it
16 citing papers in PubMed.
- Variational sparse Gaussian-process method for detecting spatially variable genes and cellular interactions in spatial transcriptomics.Briefings in bioinformatics · 2026Article
- Beyond the Cell Atlas: Functional Communities as the Essential Pathologic Units Driving Kidney Disease.Journal of the American Society of Nephrology : JASN · 2026Review
- Fhl1, a new spatially specific protein, regulates vein graft neointimal hyperplasia.Clinical and translational medicine · 2024Article
- A comprehensive overview of graph neural network-based approaches to clustering for spatial transcriptomics.Computational and structural biotechnology journal · 2024Review
- DANCE: a deep learning library and benchmark platform for single-cell analysis.Genome biology · 2024Article
- SiFT: uncovering hidden biological processes by probabilistic filtering of single-cell data.Nature communications · 2024Article
- Robust reconstruction of single-cell RNA-seq data with iterative gene weight updates.Bioinformatics (Oxford, England) · 2023Article
- Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity.Frontiers in cell and developmental biology · 2023Article
- Laser Microdissection-Mediated Isolation of Butterfly Wing Tissue for Spatial Transcriptomics.Methods and protocols · 2022Article
- Unravelling Prostate Cancer Heterogeneity Using Spatial Approaches to Lipidomics and Transcriptomics.Cancers · 2022Review
- The transcriptomic revolution and radiation biology.International journal of radiation biology · 2022Article
- NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport.Nature protocols · 2021Article
- Review
- Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes.Molecules and cells · 2021Review
- Review
- Emerging Technologies to Study the Glomerular Filtration Barrier.Frontiers in medicine · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Complex cell-to-cell communication underlies the basic processes essential for homeostasis in the given tissue architecture. Obtaining quantitative gene-expression of cells in their native context has significantly advanced through single-cell RNA sequencing technologies along with mechanical and enzymatic tissue manipulation. This approach, however, is largely reliant on the physical dissociation of individual cells from the tissue, thus, resulting in a library with unaccounted positional information. To overcome this, positional information can be obtained by integrating imaging and positional barcoding. Collectively, spatial transcriptomics strategies provide tissue architecture-dependent as well as position-dependent cellular functions. This review discusses the current technologies for spatial transcriptomics ranging from the methods combining mechanical dissociation and single-cell RNA sequencing to computational spatial re-mapping.
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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.