ArticleProteomics2025
Top-Down Proteomics: Why and When?
Article 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.
- Targeted proteoform degradation for precision drug design, delivery, and therapy.Drug delivery · 2026Review
- The "2DE-Pattern" Database for Inventory of Proteoform Profiles: 2026 Upgrade and Update on Outcomes.Proteomes · 2026Article
- Top-Down versus Bottom-Up Proteomics in Highly Sensitive LC-MS-Based Profiling of Limited Samples.Analytical chemistry · 2026Article
- Integrating Spatial Proteogenomics in Cancer Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Top-Down Mass Spectrometry and Its Current Applications in Biomarker Discovery in Aging and Age-Related Diseases.International journal of molecular sciences · 2026Review
- Recent Developments and Applications of Capillary and Microchip Electrophoresis in Proteomics and Peptidomics (2023-2025).Journal of separation science · 2026Review
- Proteoformics-driven new concept of human growth hormone in clinical endocrinology.Frontiers in endocrinology · 2026Review
- Review
- Guided tour through the small protein landscape ofmicroLife · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Manifold biological processes at all levels of transcription and translation can lead to the formation of a high number of different protein species (i.e., proteoforms), which outnumber the sequences encoded in the genome by far. Due to the large number of protein molecules formed in this way, which span an enormous range of different physicochemical properties, proteoforms are the functional drivers of all biological processes, creating the need for powerful analytical approaches to decipher this language of life. While bottom-up proteomics has become the most widely used approach, providing features such as high sensitivity, depth of analysis, and throughput, it has its limitations when it comes to identifying, quantifying, and characterizing proteoforms. In particular, the major bottleneck is to assign peptide-level information to the original proteoforms. In contrast, top-down proteomics (TDP) targets the direct analysis of intact proteoforms. Despite being characterized by a number of technological challenges, the TDP community has established numerous protocols that allow easy implementation in any proteomics laboratory. In this viewpoint, we compare both approaches, argue that it is worth embedding TDP experiments, and show fields of research in which TDP can be successfully implemented to perform integrative multi-level proteoformics.
Indexed as
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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.