ArticleScientific data2026
A Labrador PeptideAtlas and DIA spectral assay library - resources for proteomics research in dogs.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- AData in brief · 2026Article
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Authors and funding
13 authors.
Funding
Abstract
The domestic dog, Canis lupus familiaris, plays a vital role as companion or service animal, and the well-being and healthy aging of dogs is gaining importance. Proteins are key actors in cells, tissues and body fluids, and the ability to measure their composition and abundance is crucial to understand biological processes. We report a mass spectrometry-based proteomics approach analyzing canine tissues, plasma and urine obtained from Labrador retrievers to develop two comprehensive resources to advance the study of the dog proteome. Firstly, we developed a Labrador PeptideAtlas covering 49% of the predicted UniProtKB proteome and secondly, a Labrador spectral assay library for targeted applications by data-independent acquisition that enables the identification and quantification of 11,792 proteins (11,564 protein groups) of the dog proteome (56%). We demonstrate the performance of the library with gradients of different length and quantify 10,140 proteins in tissues and 385 proteins in plasma.
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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 Socratic graph.