Evidence map›Paper›PMID 39696887›Full record

ReviewProteomics2025

Advancements in Global Phosphoproteomics Profiling: Overcoming Challenges in Sensitivity and Quantification.

Gul Muneer, Ciao-Syuan Chen, Yu-Ju Chen

Abstract readReview
In one paragraph

Review in Proteomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  17. Peripheral cytokine distinguish recent fromFrontiers in microbiology · 2026
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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.

Gul MuneerInstitute of Chemistry, Academia Sinica, Taipei, Taiwan.
Ciao-Syuan ChenInstitute of Chemistry, Academia Sinica, Taipei, Taiwan.
Yu-Ju ChenInstitute of Chemistry, Academia Sinica, Taipei, Taiwan.ORCID 0000-0002-3178-6697

Funding

Academia Sinica AS-GC-111-M03National Science and Technology Council 113-2113-M-001-020-MY3
6 · The paper itself

Abstract

Protein phosphorylation introduces post-genomic diversity to proteins, which plays a crucial role in various cellular activities. Elucidation of system-wide signaling cascades requires high-performance tools for precise identification and quantification of dynamics of site-specific phosphorylation events. Recent advances in phosphoproteomic technologies have enabled the comprehensive mapping of the dynamic phosphoproteomic landscape, which has opened new avenues for exploring cell type-specific functional networks underlying cellular functions and clinical phenotypes. Here, we provide an overview of the basics and challenges of phosphoproteomics, as well as the technological evolution and current state-of-the-art global and quantitative phosphoproteomics methodologies. With a specific focus on highly sensitive platforms, we summarize recent trends and innovations in miniaturized sample preparation strategies for micro-to-nanoscale and single-cell profiling, data-independent acquisition mass spectrometry (DIA-MS) for enhanced coverage, and quantitative phosphoproteomic pipelines for deep mapping of cell and disease biology. Each aspect of phosphoproteomic analysis presents unique challenges and opportunities for improvement and innovation. We specifically highlight evolving phosphoproteomic technologies that enable deep profiling from low-input samples. Finally, we discuss the persistent challenges in phosphoproteomic technologies, including the feasibility of nanoscale and single-cell phosphoproteomics, as well as future outlooks for biomedical applications.

Indexed as

PhosphoproteinsProteomeProteomicsAnimalsHumansMass SpectrometryPhosphorylationSingle-Cell AnalysisPhosphoproteinsProteomedata‐independent acquisitionmass spectrometryphosphoproteomicsprotein phosphorylation

Identifiers

PMID39696887
PMCPMC11735659

What OpenQuestion holds

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Registered trials

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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.