Machine Learning for Absolute Quantification of Unidentified Compounds in Non-Targeted LC/HRMS.

ABSTRACT: LC/ESI/HRMS is increasingly employed for monitoring chemical pollutants in water samples, with non-targeted analysis becoming more common. Unfortunately, due to the lack of analytical standards, non-targeted analysis is mostly qualitative. To remedy this, models have been developed to evaluate the response of compounds from their structure, which can then be used for quantification in non-targeted analysis. Still, these models rely on tentatively known structures while for most detected compounds, a list of structural candidates, or sometimes only exact mass and retention time are identified. In this study, a quantification approach was developed, where LC/ESI/HRMS descriptors are used for quantification of compounds even if the structure is unknown. The approach was developed based on 92

SUBMITTER: Palm E 

PROVIDER: S-EPMC8840743 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature