ArticleFrontiers in endocrinology2019
A Comparative Peptidomic Characterization of Cultured Skeletal Muscle Tissues Derived From
Article in Frontiers in endocrinology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 6 citations in OpenAlex.
- Identification and Characterization of Glycine- and Proline-Rich Antioxidant Peptides From Antler Residues Based on Peptidomics, Machine Learning, and Molecular Docking.Food science & nutrition · 2025Article
- Label-Free Quantitation of Endogenous Peptides.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Article
- Combining mass spectrometry and machine learning to discover bioactive peptides.Nature communications · 2022Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As an important secretory organ, skeletal muscle has drawn attention as a potential target tissue for type 2 diabetic mellitus (T2DM). Recent peptidomics approaches have been applied to identify secreted peptides with potential bioactive. However, comprehensive analysis of the secreted peptides from skeletal muscle tissues of
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Registered trials
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