ArticleCommunications biology2023
Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics.
Article in Communications biology, 2023. 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
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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.
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Who cites it
3 citing papers in PubMed, 10 citations in OpenAlex.
- Assessment of false discovery rate control in tandem mass spectrometry analysis using entrapment.Nature methods · 2025Article
- Interpreting biologically informed neural networks for enhanced proteomic biomarker discovery and pathway analysis.Nature communications · 2023Article
- Unravelling potential biomarkers for acute and chronic brucellosis through proteomic and bioinformatic approaches.Frontiers in cellular and infection microbiology · 2023Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.
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Registered trials
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