Evidence map›Paper›PMID 41313267›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Single-Cell Profiling: Any Scale, Any Size, All at Once.

Denise Goh, Felicia Wee, Rachel Elizabeth Ann Fincham, Ruisi Li, Joe Yeong

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Single-Cell Profiling: Any Scale, Any Size, All at Once.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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

5 authors.

Denise GohInstitute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore.ORCID https://orcid.org/0000-0003-4598-4181
Felicia WeeInstitute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore.
Rachel Elizabeth Ann FinchamDepartment of Anatomical Pathology, Singapore General Hospital, Singapore, 169856, Singapore.
Ruisi LiInstitute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore.
Joe YeongInstitute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore.ORCID https://orcid.org/0000-0002-6674-7153

Funding

A*STAR GAP Funding I23D1AG121A*STAR GAP Funding I24D1AG059A*STAR GAP Funding I24D1AG082Industry Alignment Fund-Industry Collaboration Fund I2001E0065Industry Alignment Fund-Industry Collaboration Fund I2201E0014Singapore National Medical Research Council OFLCG23may-0039Singapore National Medical Research Council OFLCG24may-0025Singapore National Medical Research Council OFLCG24may-0028
6 · The paper itself

Abstract

Single-cell technologies have revolutionized the understanding of cellular heterogeneity, revealing distinct cell populations and functional states with molecular precision. Traditional approaches, however, are constrained by cellular dimension and throughput scale, in addition to its inability preserve spatial information. Recent innovations now allow high throughput, large-sized cell, and multi-modal profiling of patient samples, overcoming these limitations. In this perspective, three recently developed single-cell technologies is described, highlighting how their enhanced throughput, resolution, and sensitivity provide deeper insights into cellular identity and function.

Indexed as

Single-Cell AnalysisAnimalsHumanscellular heterogeneityhigh‐throughput analysismolecular profilingsingle‐cell technology

Identifiers

PMID41313267
PMCPMC12884710

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.