Identification of metabolites from tandem mass spectra with a machine learning approach utilizing structural features.

ABSTRACT:

Motivation

Untargeted mass spectrometry (MS/MS) is a powerful method for detecting metabolites in biological samples. However, fast and accurate identification of the metabolites' structures from MS/MS spectra is still a great challenge.

Results

We present a new analysis method, called SubFragment-Matching (SF-Matching) that is based on the hypothesis that molecules with similar structural features will exhibit similar fragmentation patterns. We combine information on fragmentation patterns of molecules with shared substructures and then use random forest models to predict whether a given structure can yield a certain fragmentation pattern. These models can then be used to score candidate molecules for a given mass spectrum. For rapid identification, we pre-compute such scor

SUBMITTER: Li Y 

PROVIDER: S-EPMC7703789 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature