ReviewProteomics2025
Computational Approaches for Pathway-Centric Analysis of Protein Post-Translational Modifications.
Review 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.
- Phosphoproteomics in Vascular Biology and Disease: Illuminating Signaling in the Vessel.Arteriosclerosis, thrombosis, and vascular biology · 2026Review
- M-GNN: A Topology-Enhanced Multi-Modal Graph Neural Network for Cancer Driver Gene Prediction.Metabolites · 2026Article
- Computational Approaches for Pathway-Centric Analysis of Protein Post-Translational Modifications.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
Protein function is dynamically modulated by post-translational modifications (PTMs). Many different types of PTMs can nowadays be identified and quantified at a large scale using mass spectrometry. It is well known that many PTMs have an effect on protein function and cellular processes, and they should be studied not in isolation, but in the holistic context of cellular pathways. This is increasingly facilitated by a wide variety of computational efforts. This review aims to give a systematic overview of tools for pathway-centric analysis of PTM data and critically evaluate the state of play in this research field. Starting from databases that make up the foundational prior knowledge, we follow typical steps that an analytical workflow might contain, including pathway enrichment analysis, algorithms for pathway reconstruction, and the integration and visualization of results. We then reflect on common limitations of all existing tools and give our opinion on future directions that we think are currently most desirable.
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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.