One of the most common stationary phases for gas chromatography (GC) is the polyethylene glycol (PEG) or “wax” columns. They ...
Mid-elevation Central European conversion of beech stands to spruce plantations has intensified soil acidification via needle ...
Wallman unpacks how graph-level fragmentation in fragDETR captures internal fragments and neutral losses, with peak and ...
Your talk at ASMS was on “PeptDeepKontext: A Universal Model for Predicting Peptide Properties Across Instruments, Conditions ...
High-performance liquid chromatography (HPLC) reveals how burn pit smoke disrupts blood vessels, lungs, and the brain.
AI promises to solve cost, labor, and regulatory challenges, but a shortage of deployment expertise means it can create more ...
Hydrophilic interaction chromatography-mass spectrometry (HILIC-MS) profiling tied a senescence gene region to chlorophyll ...
Nikoline Juul Nielsen from the University of Copenhagen, Denmark explores deprotomer formation for accurate CCS prediction and metabolite identification and the potential of implementing these ...
Sugar accumulation and organic-acid depletion during ripening jointly determine potential alcohol, perceived sweetness, pH, color stability, and spoilage risk, making their ratio a practical ...
Wallman explains how spectral library accuracy, retention time prediction, and instrument-specific variation make deep learning essential yet difficult in data-independent acquisition proteomics.
Wallman details PeptDeepKontext, a model built to predict peptide properties across diverse instruments and PTMs by embracing rather than eliminating inter-laboratory variability.
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