ArticleProteomics2025
JUMPshiny: A User-Friendly Platform for Comprehensive Analysis and Visualization of Quantitative Proteomics Data.
Article in Proteomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Proteome Responses to Acute Inhibition of De Novo Sphingolipid Synthesis Suggest Cancer Combination Therapies.Cancers · 2026Article
- APOE is a presynaptic protein that accumulates with age and modulates neurotransmitter release.bioRxiv : the preprint server for biology · 2026Article
- Elevated endocytic trafficking mediated by GPRASP2 maintains HSC fidelity.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Mass spectrometry-based quantitative proteomics has revolutionized our understanding of biological processes and unveiled the molecular mechanisms underlying various diseases. The analysis and visualization of quantitative proteomics data remain complex and require user-friendly tools with robust analytical capacities. In this study, we introduce JUMPshiny, a novel, interactive, and comprehensive web-service, that is built on R-Shiny and designed for processing and presenting quantitative proteomics data. JUMPshiny includes a wide range of visualizations and offers a streamlined workflow, including experimental design, data exploration, batch normalization, differential analysis, and enrichment analysis. Through examples, we demonstrate automated quality control, interactive data visualization, and customizable statistical analyses. Built on the R-Shiny framework, JUMPshiny integrates established libraries and packages to ensure computational robustness and reproducibility. Overall, JUMPshiny represents a powerful platform for proteomics data analysis for the research community. JUMPshiny is available at https://jumpshiny.genenetwork.org. The source code is available under MIT license at: https://github.com/Wanglab-UTHSC/JUMP_shiny.
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.