ArticleJournal of the American Society for Mass Spectrometry2025
Multispectrum ModiFinder Site Localization Performance.
Article in Journal of the American Society for Mass Spectrometry, 2025. 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
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Who cites it
1 citing paper in PubMed.
- Agentic AI for Structural Elucidation and Discovery of Drug Metabolites from Mass Spectrometry Data.bioRxiv : the preprint server for biology · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
Tandem mass spectrometry (MS/MS) is a powerful technique for structural identification of small molecules, yet a significant portion of MS/MS spectra from untargeted experiments remain unidentifiable through spectrum library matching. ModiFinder, a computational tool, tackles this issue by predicting the site of chemical modifications on known analogs of the unidentified compounds using MS/MS data. However, ModiFinder's performance is limited by insufficient peak data and fragmentation annotation ambiguities. In this study, we investigate how incorporating MS/MS spectra from multiple collision energies and mass spectrometry adducts can enhance ModiFinder's localization accuracy. Using a data set from Agilent Technologies comprising 2150 data-rich compounds (five times larger than previously available data sets), we evaluated the impact of complementary spectral information. Our results show that combining spectra from different adducts and collision energies expands ModiFinder's localization abilities to more compounds and improves the overall performance.
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Registered trials
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