Validating and Comparing Component Detection Algorithms for LC-MS Data Assignment

PO-CON1857E Deep learning methods applied to the analysis of metabolomics data ASMS 2019 WP 389 Shinji Kanazawa1,3,4, Yohei Yamada1, Hiroyuki Yasuda1, Akihiro Kunisawa1,3, Toru Shiohama1, Shigeki Kajihara1, Norio Mukai1, Masaki Kakisako2, Go Fujisawa2, Yuzuru Yamakage2, Junko Iida1,3, Eiichiro Fukusaki5, Fumio…

Poster Reprint ASMS 2025 Poster number WP 113 De Novo PFAS Annotation and Classification Using Highly Accurate Formula Prediction and Kaufmann Algorithms Embedded in FluoroMatch Suite Jeremy Koelmel1; Michael Kummer2; David Schiessel2; Olivier Chevallier3; David Godri4; Christian Klein3; Emma E…

Leveraging the MS1 Dimension and Formula Prediction in Non-Targeted Analysis of PFAS using New FluoroMatch Algorithms: Assessing Confidence and Coverage David Schiessel* [1]; Jeremy Koelmel [2]; Michael Kummer [1]; David Godri [3]; Sheng Liu [2]; Elizabeth Z. Lin [2]; John…

Application note | 003883 Environmental Comprehensive non-targeted workflow for confident identification of perfluoroalkyl substances (PFAS) Richard Cochran1, Sarah Choyke2, Application benefits Collin Meyers2, Ralf Tautenhahn3 • High-resolution accurate-mass (HRAM) data acquired using the Thermo Scientific™ Orbitrap Exploris™ mass spectrometer platform…