ArticleFrontiers in molecular biosciences2023
Simulated-to-real benchmarking of acquisition methods in untargeted metabolomics.
Article in Frontiers in molecular biosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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
5 citing papers in PubMed, 9 citations in OpenAlex.
- Structure-guided parameter optimization of feature-based molecular networking for DIA-HRMS screening of antihistamines in cosmetics.Analytical and bioanalytical chemistry · 2026Article
- Chemical Profiling of Aboveground and Underground Parts ofMolecules (Basel, Switzerland) · 2026Article
- In-depth analysis of data characteristics and comparative evaluation of dda and dia accuracy in label-free quantitative proteomics of biological samples.Clinical proteomics · 2025Article
- TopNEXt: automatic DDA exclusion framework for multi-sample mass spectrometry experiments.Bioinformatics (Oxford, England) · 2023Article
- Recent advances in mass spectrometry-based computational metabolomics.Current opinion in chemical biology · 2023Review
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data-Dependent and Data-Independent Acquisition modes (DDA and DIA, respectively) are both widely used to acquire MS2 spectra in untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS) metabolomics analyses. Despite their wide use, little work has been attempted to systematically compare their MS/MS spectral annotation performance in untargeted settings due to the lack of ground truth and the costs involved in running a large number of acquisitions. Here, we present a systematic
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