首页|Navigating the Maze of Mass Spectra: A Machine-Learning Guide to Identifying Dia gnostic Ions in O-Glycan Analysis
Navigating the Maze of Mass Spectra: A Machine-Learning Guide to Identifying Dia gnostic Ions in O-Glycan Analysis
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from bi orxiv.org:“Structural details of oligosaccharides, or glycans, often carry biological rele vance, which is why theyare typically elucidated using tandem mass spectrometry . Common approaches to distinguish isomersrely on diagnostic glycan fragments f or annotating topologies or linkages. Diagnostic fragments areoften only known informally among practitioners or stem from individual studies, with unclear val idityor generalizability, causing annotation heterogeneity and hampering new an alysts. Drawing on a curatedset of 237,000 O-glycomics spectra, we here present a rule-based machine learning workflow to uncoverquantifiably valid and genera lizable diagnostic fragments.
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