ReviewProteomics2025
Data acquisition approaches for single cell proteomics.
Review in Proteomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Lactylation Remodels Tumorigenesis, Immune Microenvironment, and Therapeutic Response.Current issues in molecular biology · 2026Review
- Artificial Intelligence-Powered Histopathology in Stem Cell Research: Bridging Morphology, Function, and Omics.Current issues in molecular biology · 2026Review
- A Parallel Accumulation-Mobility Aligned Fragmentation Strategy Utilizing High-Resolution Ion Mobility for High-Performance Proteomics Analysis.Molecular & cellular proteomics : MCP · 2026Article
- Classification with Missing Data - AbioRxiv : the preprint server for biology · 2026Article
- Higher-Throughput Proteome Profiling Enabled by Parallelized Pre-Accumulation and Optimized Ion Processing in the Orbitrap Astral Zoom Mass Spectrometer.Molecular & cellular proteomics : MCP · 2026Article
- Improving Proteomic Dynamic Range with Multiple Accumulation Precursor Mass Spectrometry.Journal of proteome research · 2025Article
- Single-cell proteomics using mass spectrometry.Cell genomics · 2025Review
- Slice-PASEF: Maximising Ion Utilisation in LC-MS Proteomics.bioRxiv : the preprint server for biology · 2025Article
- Data acquisition approaches for single cell proteomics.Proteomics · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.