A comparison of three liquid chromatography (LC) retention time prediction models.

ABSTRACT: High-resolution mass spectrometry (HRMS) data has revolutionized the identification of environmental contaminants through non-targeted analysis (NTA). However, chemical identification remains challenging due to the vast number of unknown molecular features typically observed in environmental samples. Advanced data processing techniques are required to improve chemical identification workflows. The ideal workflow brings together a variety of data and tools to increase the certainty of identification. One such tool is chromatographic retention time (RT) prediction, which can be used to reduce the number of possible suspect chemicals within an observed RT window. This paper compares the relative predictive ability and applicability to NTA workflows of three RT prediction models: (1) a logP (o

SUBMITTER: McEachran AD 

PROVIDER: S-EPMC6066181 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature