Evidence map›Paper›PMID 34597050›Full record

ArticleJournal of proteome research2021

Driving Single Cell Proteomics Forward with Innovation.

Nikolai Slavov

Open access · greenAbstract read
In one paragraph

Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 2% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Slice-PASEF: Maximising Ion Utilisation in LC-MS Proteomics.bioRxiv : the preprint server for biology · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Single-nucleus proteomics identifies regulators of protein transport.bioRxiv : the preprint server for biology · 2024
    Article
  14. Article
  15. Review
  16. Article
  17. Data-Driven Optimization of DIA Mass Spectrometry by DO-MS.bioRxiv : the preprint server for biology · 2023
    Article
  18. Review
  19. Article
  20. Article
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.

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

Funding

Ribosome-mediated translational regulation during stem cell differentiationDP2GM123497 · NIGMS · NORTHEASTERN UNIVERSITY · PI SLAVOV, NIKOLAI · 2016 to 2016
$2.4M
Single-cell proteomic identification of novel markers of senescenceUG3CA268117 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DOU, ZHIXUN, RAJAGOPAL, JAYARAJ · 2021 to 2022
$1.2M
NCI NIH HHS UG3 CA268117NIGMS NIH HHS DP2 GM123497
6 · The paper itself

Abstract

Current single-cell mass spectrometry (MS) methods can quantify thousands of peptides per single cell while detecting peptide-like features that may support the quantification of 10-fold more peptides. This 10-fold gain might be attained by innovations in data acquisition and interpretation even while using existing instrumentation. This perspective discusses possible directions for such innovations with the aim to stimulate community efforts for increasing the coverage and quantitative accuracy of single proteomics while simultaneously decreasing missing data. Parallel improvements in instrumentation, sample preparation, and peptide separation will afford additional gains. Together, these synergistic routes for innovation project a rapid growth in the capabilities of MS based single-cell protein analysis. These gains will directly empower applications of single-cell proteomics to biomedical research.

Indexed as

ProteomicsTandem Mass SpectrometryPeptidesProteinsSingle-Cell AnalysisPeptidesProteinsdata acquisitiondata interpretationpeptide identity propagationsingle-cell proteomicsultrasensitive proteomics

Identifiers

PMID34597050
PMCPMC8571067
OpenAlexW3204937366

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.