Boosting annotation in nutrimetabolomics by Feature-Based Molecular Networking: analytical and computational strategies applied to human urine samples from an untargeted LC-MS/MS based bilberry-blueberry intervention study.
Lapo Renai, Marynka Ulaszewska, Fulvio Mattivi, Riccardo Bartoletti, Massimo DEL BUBBA, Justin J. J. van der Hooft
This paper improves metabolite annotation in human urine using Feature-Based Molecular Networking and spectral libraries, identifying 65 berry-related metabolites and enhancing annotation coverage by 72%.
bioRxiv · Dec 20, 2021 · PreprintBioinformatics