Evidence map›Paper›PMID 39544230›Full record

ArticleGEN biotechnology2023

Technical Advances and Applications of Spatial Transcriptomics.

Guohao Liang, Hong Yin, Fangyuan Ding

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in GEN biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Guohao LiangDepartment of Biomedical Engineering, University of California, Irvine, Irvine, California, USA.
Hong YinDepartment of Biomedical Engineering, University of California, Irvine, Irvine, California, USA.
Fangyuan DingCenter for Synthetic Biology, Center for Complex Biological Systems, Department of Developmental and Cell Biology, and Department of Pharmaceutical Sciences, University of California, Irvine, California, USA.

Funding

Universally-applicable RNA mapping at subcellular and single-base resolutionDP2GM149554 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI DING, FANGYUAN · 2022 to 2025
$2.3M
NIGMS NIH HHS DP2 GM149554
6 · The paper itself

Abstract

Transcriptomics is one of the largest areas of research in biological sciences. Aside from RNA expression levels, the significance of RNA spatial context has also been unveiled in the recent decade, playing a critical role in diverse biological processes, from subcellular kinetic regulation to cell communication, from tissue architecture to tumor microenvironment, and more. To systematically unravel the positional patterns of RNA molecules across subcellular, cellular, and tissue levels, spatial transcriptomics techniques have emerged and rapidly became an irreplaceable tool set. Herein, we review and compare current spatial transcriptomics techniques on their methods, advantages, and limitations, as well as applications across a wide range of biological investigations. This review serves as a comprehensive guide to spatial transcriptomics for researchers interested in adopting this powerful suite of technologies.

Identifiers

PMID39544230
PMCPMC11562938

What OpenQuestion holds

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Registered trials

None linked

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.