Evidence map›Paper›PMID 31180188›Full record

ArticleCurrent protocols in protein science2019

Proteome Analysis Using Gel-LC-MS/MS.

Aaron R Goldman, Lynn A Beer, Hsin-Yao Tang, Peter Hembach, Delaine Zayas-Bazan, David W Speicher

Abstract read
In one paragraph

Article in Current protocols in protein science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Qualitative Proteomic Profiling ofFoods (Basel, Switzerland) · 2025
    Article
  4. Article
  5. Article
  6. Biomarker insights · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Soft rot pathogenFrontiers in microbiology · 2023
    Article
  19. Review
  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

6 authors.

Aaron R GoldmanProteomics and Metabolomics Facility, The Wistar Institute, Philadelphia, Pennsylvania.
Lynn A BeerCenter for Systems and Computational Biology and Molecular and Cellular Oncogenesis Program, The Wistar Institute, Philadelphia, Pennsylvania.
Hsin-Yao TangProteomics and Metabolomics Facility, The Wistar Institute, Philadelphia, Pennsylvania.
Peter HembachCenter for Systems and Computational Biology and Molecular and Cellular Oncogenesis Program, The Wistar Institute, Philadelphia, Pennsylvania.
Delaine Zayas-BazanCenter for Systems and Computational Biology and Molecular and Cellular Oncogenesis Program, The Wistar Institute, Philadelphia, Pennsylvania.
David W SpeicherCenter for Systems and Computational Biology and Molecular and Cellular Oncogenesis Program, The Wistar Institute, Philadelphia, Pennsylvania.

Funding

Tumor Microenvironment and MetastasisP30CA010815 · NCI · WISTAR INSTITUTE · PI Luis J Montaner · 1985 to 2026
$75.9M
TRAINING PROGRAM IN BASIC CANCER RESEARCHT32CA009171 · NCI · WISTAR INSTITUTE · PI Alessandro Gardini · 1985 to 2026
$15.3M
Role of Runx2 in prostate tumorigenesis and metastasisP01CA140043 · NCI · WISTAR INSTITUTE · PI ALTIERI, DARIO C · 2010 to 2021
$12.2M
Targeted Combination Therapy for MelanomaP50CA174523 · NCI · WISTAR INSTITUTE · PI HERLYN, MEENHARD F · 2014 to 2018
$11.1M
STRUCTURAL BIOLOGY TRAINING PROGRAMT32GM008275 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI WAND, A. JOSHUA · 1988 to 2018
$6.0M
Identification of Ovarian Cancer Plasma BiomarkersR01CA131582 · NCI · WISTAR INSTITUTE · PI SPEICHER, DAVID W. · 2009 to 2018
$4.1M
Development of a serum biosignature for ectopic pregnancy.R01HD076279 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI BARNHART, KURT T · 2014 to 2018
$3.4M
Advancing Cancer Research through Comprehensive Proteomics and Metabolomics AnalysesR50CA221838 · NCI · WISTAR INSTITUTE · PI Hsin-Yao Tang · 2017 to 2026
$2.1M
NCI NIH HHS P01 CA140043NCI NIH HHS P30 CA010815NCI NIH HHS P50 CA174523NCI NIH HHS R01 CA131582NCI NIH HHS R50 CA221838NCI NIH HHS T32 CA009171NICHD NIH HHS R01 HD076279NIGMS NIH HHS T32 GM008275
6 · The paper itself

Abstract

This article describes processing of protein samples using 1D SDS gels prior to protease digestion for proteomics workflows that subsequently utilize reversed-phase nanocapillary ultra-high-pressure liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS). The resulting LC-MS/MS data are used to identify peptides and thereby infer proteins present in samples ranging from simple mixtures to very complex proteomes. Bottom-up proteome studies usually involve quantitative comparisons across several or many samples. For either situation, 1D SDS gels represent a simple, widely available technique that can be used to either fractionate complex proteomes or rapidly clean up low microgram samples with minimal losses. After gel separation and staining/destaining, appropriate gel slices are excised, and in-gel reduction, alkylation, and protease digestion are performed. Digests are then processed for LC-MS/MS analysis. Protocols are described for either sample fractionation with high-throughput processing of many samples or simple cleanup without fractionation. An optional strategy is to conduct in-solution reduction and alkylation prior to running gels, which is advantageous when a large number of samples will be separated into large numbers of fractions. Optimization of trypsin digestion parameters and comparison to in-solution protease digestion are also described. © 2019 by John Wiley & Sons, Inc.

Indexed as

Electrophoresis, Polyacrylamide GelTandem Mass SpectrometryChemical FractionationChromatography, High Pressure LiquidHigh-Throughput Screening AssaysPeptidesProteomePeptidesProteomegel-LC-MS/MSin-gel digestionLC-MS/MSmass spectrometryproteome fractionationproteomicsSDS gels

Identifiers

PMID31180188
PMCPMC6653605

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.