Evidence map›Paper›PMID 29945450›Full record

ReviewJournal of proteome research2018

Transformative Opportunities for Single-Cell Proteomics.

Harrison Specht, Nikolai Slavov

Abstract readReview
In one paragraph

Review in Journal of proteome research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 1 pooled it
–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

71 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Review
  3. Article
  4. Review
  5. Cell-specific protein expression in Alzheimer's disease prefrontal cortex.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  6. Mass Spectrometry-based Solutions for Single-cell Proteomics.Genomics, proteomics & bioinformatics · 2025
    Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

11 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

2 authors.

Harrison SpechtDepartment of Bioengineering , Northeastern University , Boston , Massachusetts 02115 , United States.
Nikolai SlavovDepartment of Bioengineering , Northeastern University , Boston , Massachusetts 02115 , United States.ORCID 0000-0003-2035-1820

Funding

Ribosome-mediated translational regulation during stem cell differentiationDP2GM123497 · NIGMS · NORTHEASTERN UNIVERSITY · PI SLAVOV, NIKOLAI · 2016 to 2016
$2.4M
NIGMS NIH HHS DP2 GM123497
6 · The paper itself

Abstract

Many pressing medical challenges, such as diagnosing disease, enhancing directed stem-cell differentiation, and classifying cancers, have long been hindered by limitations in our ability to quantify proteins in single cells. Mass spectrometry (MS) is poised to transcend these limitations by developing powerful methods to routinely quantify thousands of proteins and proteoforms across many thousands of single cells. We outline specific technological developments and ideas that can increase the sensitivity and throughput of single-cell MS by orders of magnitude and usher in this new age. These advances will transform medicine and ultimately contribute to understanding biological systems on an entirely new level.

Indexed as

AnimalsDietary ProteinsHumansMass SpectrometryProteomicsSingle-Cell AnalysisSpecimen HandlingDietary Proteinssingle cell proteinscausal inferencecounting noisedisease diagnosisnetwork inferencesample preparationSimpson’s paradoxsingle-cell analysissingle-cell mass-spectrometrysystems biologyultrasensitive proteomics

Identifiers

PMID29945450
PMCPMC6089608

What OpenQuestion holds

Textmetadata
LicenceTDM
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.