Expanding Urinary Metabolite Annotation through Integrated Mass Spectral Similarity Networking.

ABSTRACT: The urine metabolome constitutes a rich source of functional information reflecting physiological states that are influenced by distinct conditions and biological stresses, such as responses to drug treatments or disease manifestations. Although global liquid chromatography-mass spectrometry (MS) profiling provides the most comprehensive measurement of metabolites in complex biological samples, annotation remains a challenge, and computational approaches are necessary to translate the molecular composition into biological knowledge. Here, we investigated the use of tandem MS-based enhanced molecular networks (MolNetEnhancer) to improve the metabolite annotation of urine extracts. The samples (n = 10) were analyzed by hydrophilic interaction chromatography-quadrupole time-of-flight m

SUBMITTER: Neto FC 

PROVIDER: S-EPMC8530160 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature