Evidence map›Paper›PMID 32847821›Full record

ReviewMolecular & cellular proteomics : MCP2020

Single-cell Proteomics: Progress and Prospects.

Ryan T Kelly

Open access · hybridAbstract readReview
In one paragraph

Review in Molecular & cellular proteomics : MCP, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
184citing papers in PubMed, 1 pooled it
25.5field-weighted citation impact, top 1% of its field
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

184 citing papers in PubMed, 1 synthesis or guideline pooled it, 367 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. MR-SPJournal of proteome research · 2026
    Article
  11. Review
  12. Integrating Spatial Proteogenomics in Cancer Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Future Research Directions on Mycobacterium tuberculosis Proteins.Advances in experimental medicine and biology · 2026
    Review
  19. Article
  20. Review

124 more citing papers are in PubMed but not listed here.

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

1 author at 1 institution in 1 country.

Ryan T KellyDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah, USA. Electronic address: ryan.kelly@byu.edu.
Brigham Young University · US

Funding

Area A: In-Depth Proteome Mapping of the Tumor Microenvironment with Single-Cell ResolutionR33CA225248 · NCI · BRIGHAM YOUNG UNIVERSITY · PI KELLY, RYAN T · 2017 to 2017
$1.7M
NCI NIH HHS R33 CA225248
6 · The paper itself

Abstract

MS-based proteome profiling has become increasingly comprehensive and quantitative, yet a persistent shortcoming has been the relatively large samples required to achieve an in-depth measurement. Such bulk samples, typically comprising thousands of cells or more, provide a population average and obscure important cellular heterogeneity. Single-cell proteomics capabilities have the potential to transform biomedical research and enable understanding of biological systems with a new level of granularity. Recent advances in sample processing, separations and MS instrumentation now make it possible to quantify >1000 proteins from individual mammalian cells, a level of coverage that required an input of thousands of cells just a few years ago. This review discusses important factors and parameters that should be optimized across the workflow for single-cell and other low-input measurements. It also highlights recent developments that have advanced the field and opportunities for further development.

Indexed as

Cells, CulturedChromatography, LiquidHumansMass SpectrometryProteomeProteomicsRNA-SeqSingle-Cell AnalysisProteomeCell biologyCell sortingFAIMSLabel-free quantificationMass SpectrometrynanoLCnanoPOTSsingle-cellTandem Mass SpectrometryTissues*ultrasensitive

Identifiers

PMID32847821
PMCPMC7664119
OpenAlexW3080880059

What OpenQuestion holds

Textmetadata
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.