Evidence map›Paper›PMID 40195276›Full record

ReviewJournal of mass spectrometry : JMS2025

Overcoming Analytical Challenges in Proximity Labeling Proteomics.

Haorong Li, Wan Nur Atiqah Binti Mazli, Ling Hao

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of mass spectrometry : JMS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Haorong LiDepartment of Chemistry, The George Washington University, Washington, District of Columbia, USA.
Wan Nur Atiqah Binti MazliDepartment of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, USA.
Ling HaoDepartment of Chemistry, The George Washington University, Washington, District of Columbia, USA.ORCID https://orcid.org/0000-0002-0106-5266

Funding

National Science Foundation, CHEM 2239214Research Corporation for Science Advancement, Cottrell Scholar
6 · The paper itself

Abstract

Proximity labeling (PL) proteomics has emerged as a powerful tool to capture both stable and transient protein interactions and subcellular networks. Despite the wide biological applications, PL still faces technical challenges in robustness, reproducibility, specificity, and sensitivity. Here, we discuss major analytical challenges in PL proteomics and highlight how the field is advancing to address these challenges by refining study design, tackling interferences, overcoming variation, developing novel tools, and establishing more robust platforms. We also provide our perspectives on best practices and the need for more robust, scalable, and quantitative PL technologies.

Indexed as

ProteomicsStaining and LabelingAnimalsHumansMass SpectrometryProtein Interaction MappingProteinsReproducibility of ResultsProteinsbiotinylationmass spectrometryproximity labeling

Identifiers

PMID40195276
PMCPMC11976124

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.