Dataset
Dataset: Machine learning-assisted identification and quantification of hydroxylated metabolites of polychlorinated biphenyls in animal samples
University of Iowa
09/13/2022
DOI: 10.25820/data.006179
Abstract
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.
Details
- Title: Subtitle
- Dataset: Machine learning-assisted identification and quantification of hydroxylated metabolites of polychlorinated biphenyls in animal samples
- Creators
- Chunyun Zhang - University of Iowa, Occupational and Environmental HealthXueshu Li - University of Iowa, Occupational and Environmental HealthKimberly P Keil Stietz - University of California, DavisSunjay Sethi - University of California, DavisWeizhu Yang - University of ArizonaRachel F Marek - University of Iowa, IIHR--Hydroscience and EngineeringXinxin DingPamela J Lein - University of California, DavisKeri C Hornbuckle - University of Iowa, IIHR--Hydroscience and EngineeringHans-Joachim Lehmler - University of Iowa, Occupational and Environmental Health
- Resource Type
- Dataset
- DOI
- 10.25820/data.006179
- Publisher
- University of Iowa
- Grants
- Language
- English
- Date collected
- 12/29/2020–03/16/2021
- Date published
- 09/13/2022
- Academic Unit
- Civil and Environmental Engineering; Occupational and Environmental Health; Iowa Neuroscience Institute; IIHR--Hydroscience and Engineering; Interdisciplinary Graduate Program in Human Toxicology; Iowa Superfund Research Program
- Record Identifier
- 9984265745002771
Metrics
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