ArticleJournal of proteome research2014
PSEA-Quant: a protein set enrichment analysis on label-free and label-based protein quantification data.
Article in Journal of proteome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03800342 (Recovery, Fatigability, and Proteomic Response to Aerobic Exercise Training in Healthy Individuals), which is not on this map. Cited by 33 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.
Recovery, Fatigability, and Proteomic Response to Aerobic Exercise Training in Healthy Individuals
Who cites it
33 citing papers in PubMed, 64 citations in OpenAlex.
- Sex-Dependent Responses in the Retina Proteome to Ocular Hypertension in a Mouse Model of Glaucoma.International journal of molecular sciences · 2026Article
- Prebiotic intervention changes host and microbe proteomes in plasma extracellular vesicles of Parkinson's disease.Scientific reports · 2026Article
- Article
- Muscle Organoids Reveal Exercise-Like Contractions Rapidly Promote Muscle Health Via Lamtor1's Signaling to Both AMPK and mTOR.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Engineered Proteins and Chemical Tools to Probe the Cell Surface Proteome.Chemical reviews · 2025Review
- Serum/Plasma Proteome in Non-Malignant Liver Disease.International journal of molecular sciences · 2024Review
- Proteomic interrogation of the meninges reveals the molecular identities of structural components and regional distinctions along the CNS axis.Fluids and barriers of the CNS · 2023Article
- Critical contributions of protein cargos to the functions of macrophage-derived extracellular vesicles.Journal of nanobiotechnology · 2023Article
- Article
- SETD2 regulates the methylation of translation elongation factor eEF1A1 in clear cell renal cell carcinoma.Kidney cancer journal : official journal of the Kidney Cancer Association · 2022Article
- Data-Independent Acquisition Mass Spectrometry of the Human Lens Enhances Spatiotemporal Measurement of Fiber Cell Aging.Journal of the American Society for Mass Spectrometry · 2021Article
- PIGNON: a protein-protein interaction-guided functional enrichment analysis for quantitative proteomics.BMC bioinformatics · 2021Article
- Proteomic Analyses of Vitreous in Proliferative Diabetic Retinopathy: Prior Studies and Future Outlook.Journal of clinical medicine · 2021Review
- Proteomic characterization of the human lens and Cataractogenesis.Expert review of proteomics · 2021Review
- Differential Gene Set Enrichment Analysis: a statistical approach to quantify the relative enrichment of two gene sets.Bioinformatics (Oxford, England) · 2021Article
- Simple Targeted Assays for Metabolic Pathways and Signaling: A Powerful Tool for Targeted Proteomics.Analytical chemistry · 2020Article
- Article
- Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis.International journal of molecular sciences · 2020Review
- Redox Systems Biology: Harnessing the Sentinels of the Cysteine Redoxome.Antioxidants & redox signaling · 2020Review
- Proteomics INTegrator (PINT): An Online Tool To Store, Query, and Visualize Large Proteomics Experiment Results.Journal of proteome research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights.
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.