Title: Dataset: Machine learning-assisted identification and quantification of hydroxylated metabolites of polychlorinated biphenyls in animal samples

Accession Number: doi: 10.25820/data.006179

Link to Dataset: https://iro.uiowa.edu/esploro/outputs/dataset/9984265745002771

Repository: Iowa Research Online

Data Type(s): Code

Summary: This dataset includes the R workspaces, R scripts, and example data for predicting the relative retention times(RRT) and MS/MS data of methoxylated metabolites of polychlorinated biphenyls (MeO-PCBs) on a gas chromatography-tandem mass spectrometry (GC-MS/MS) system. In addition, molecular descriptors of 124 MeO-PCBs, including 99 cheminformatics-based descriptors and 6 substitution pattern-based descriptors, and the measured and predicted RRT and MS/MS data of 124 MeO-PCBs are provided in separate csv files.

Publication(s) associated with this dataset:

• Zhang C, Li X, Stietz KP, Sethi S, Yang W, Marek RF, Ding X, Lein PJ, Hornbuckle KC, Joachim-Lehmler H. 2022. Machine learning-assisted identification and quantification of hydroxylated metabolites of polychlorinated biphenyls in animal samples. Environ Sci Technol 56(18):13169-13178. doi:10.1021/acs.est.2c02027 PMID:36047920