MESSAR: Automated recommendation of metabolite substructures from tandem mass spectra.

ABSTRACT: Despite the increasing importance of non-targeted metabolomics to answer various life science questions, extracting biochemically relevant information from metabolomics spectral data is still an incompletely solved problem. Most computational tools to identify tandem mass spectra focus on a limited set of molecules of interest. However, such tools are typically constrained by the availability of reference spectra or molecular databases, limiting their applicability of generating structural hypotheses for unknown metabolites. In contrast, recent advances in the field illustrate the possibility to expose the underlying biochemistry without relying on metabolite identification, in particular via substructure prediction. We describe an automated method for substructure recommendation motivated

SUBMITTER: Liu Y 

PROVIDER: S-EPMC6964822 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature