Enhanced detection and annotation of small molecules in metabolomics using molecular-network-oriented parameter optimization.

ABSTRACT: Metabolomics, especially the large-scale untargeted metabolomics, generates massive amounts of data on a regular basis, which often needs to be filtered, screened, analyzed and annotated via a variety of approaches. Data-dependent-acquisition (DDA) mode including inclusion and exclusion rules for tandem mass spectrometry (MS) is routinely used to perform such analyses. While the parameters of data acquisition are important in these processes, there is a lack of systematic studies on these parameters that can be used in data collection to generate metabolic features for molecular-network (MN) analysis on the Global Natural Products Social Molecular Networking (GNPS) platform. To explore the key parameters that impact the formation and quality of MNs, several data-acquisition paramete

SUBMITTER: Xu R 

PROVIDER: S-EPMC8511212 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature