Evidence map›Paper›PMID 26667783›Full record

ReviewProteomics2016

Common errors in mass spectrometry-based analysis of post-translational modifications.

Min-Sik Kim, Jun Zhong, Akhilesh Pandey

Open access · greenAbstract readReview
In one paragraph

Review in Proteomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
5.3field-weighted citation impact, top 3% 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

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 143 citations in OpenAlex.

  1. Pooled it
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  15. Origins, Technological Advancement, and Applications of Peptidomics.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
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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

3 authors at 2 institutions in 1 country.

Min-Sik KimMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jun ZhongMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Akhilesh PandeyMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Johns Hopkins University · USJohns Hopkins Medicine · US

Funding

Translational Research Enhancement CoreP30DK089502 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI ZACHOS, NICHOLAS CONSTANTINE · 2011 to 2020
$12.0M
Proteome Characterization Center: A Genoproteomics Pipeline for Cance ResearchU24CA160036 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI, ZHANG, HUI · 2011 to 2016
$10.7M
Personalized Therapy of Hormone Refractory Breast CancerR01CA184165 · NCI · MAYO CLINIC ROCHESTER · PI PANDEY, AKHILESH · 2015 to 2019
$1.8M
NCI NIH HHS CA184165NCI NIH HHS R01 CA184165NCI NIH HHS U24 CA160036NCI NIH HHS U24CA160036NIDDK NIH HHS P30 DK089502
6 · The paper itself

Abstract

Mass spectrometry (MS) is a powerful tool to analyze complex mixtures of proteins in a high-throughput fashion. Proteome analysis has already become a routine task in biomedical research with the emergence of proteomics core facilities in most research institutions. Post-translational modifications (PTMs) represent a mechanism by which complex biological processes are orchestrated dynamically at the systems level. MS is rapidly becoming popular to discover new modifications and novel sites of known PTMs, revolutionizing the current understanding of diverse signaling pathways and biological processes. However, MS-based analysis of PTMs has its own caveats and pitfalls that can lead to erroneous conclusions. Here, we review the most common errors in MS-based PTM analyses with the goal of adopting strategies that maximize correct interpretation in the context of biological questions that are being addressed. Finally, we provide suggestions that should help mass spectrometrists, bioinformaticians and biologists to perform and interpret MS-based PTM analyses more accurately.

Indexed as

Observer VariationProtein Processing, Post-TranslationalAlgorithmsHumansProteomeProteomicsTandem Mass SpectrometryProteomeImmoniumLocalizationPTMSignatureSUMOTechnologyUbiquitin

Identifiers

PMID26667783
PMCPMC5548100
OpenAlexW2205194111

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.