Evidence map›Paper›PMID 35143156›Full record

ArticleAnalytical chemistry2022

High-Throughput, Comprehensive Single-Cell Proteomic Analysis of

Zhenbin Zhang, Kyle M Dubiak, Evgenia Shishkova, Paul W Huber, Joshua J Coon, Norman J Dovichi

Open access · greenAbstract read
In one paragraph

Article in Analytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Uncovering biology by single-cell proteomics.Communications biology · 2023
    Review
  4. Separation methods in single-cell proteomics: RPLC or CE?International journal of mass spectrometry · 2022
    Article
  5. Article
  6. Article
  7. 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

6 authors at 2 institutions in 1 country.

Zhenbin ZhangDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States.ORCID 0000-0002-8617-6386
Kyle M DubiakDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Evgenia ShishkovaDepartment of Biomolecular Chemistry, Genome Center of Wisconsin, and Department of Chemistry, University of Wisconsin, Madison, Wisconsin 53706, United States.
Paul W HuberDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Joshua J CoonDepartment of Biomolecular Chemistry, Genome Center of Wisconsin, and Department of Chemistry, University of Wisconsin, Madison, Wisconsin 53706, United States.ORCID 0000-0002-0004-8253
Norman J DovichiDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States.ORCID 0000-0002-1331-3191
University of Notre Dame · USUniversity of Wisconsin–Madison · US

Funding

TR&D 2 Metabolic Labels for Ultraplexed Protein Quantification p. 453P41GM108538 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI COON, JOSHUA J · 2016 to 2025
$13.1M
Advances in bioanalysisR35GM136334 · NIGMS · UNIVERSITY OF NOTRE DAME · PI DOVICHI, NORMAN J · 2020 to 2024
$2.0M
NIGMS NIH HHS P41 GM108538NIGMS NIH HHS R35 GM136334
6 · The paper itself

Abstract

We report both the design of a high-throughput MICROFASP (a miniaturized filter aided sample preparation) system and its use for the comprehensive proteomic analysis of single blastomeres isolated from 50-cell stage

Indexed as

ProteomicsTandem Mass SpectrometryAnimalsProteomeSingle-Cell AnalysisXenopus laevisProteome

Identifiers

PMID35143156
PMCPMC8929430
OpenAlexW4211131647

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.