Machine learning applications for chemical fingerprinting

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Description

Machine learning script develloped in python to identify chemical fingerprinting using non-target high-resolution mass spectrometry data.

Implementation details

Getting started

Select exemples use of the code

Joseph, N. T.; Schwichtenberg, T.; Cao, D.; Jones, G. D.; Rodowa, A. E.; Barlaz, M. A.; Charbonnet, J. A.; Higgins, C. P.; Field, J. A.; Helbling, D. E. Target and suspect screening integrated with machine learning to discover Per- and Polyfluoroalkyl substance source fingerprints. Environ. Sci. Technol. 2023. DOI: 10.1021/acs.est.3c03770.

Citing

Davila-Santiago, E.; Shi, C.; Mahadwar, G.; Medeghini, B.; Insinga, L.; Hutchinson, R.; Good, S.; Jones, G. D. Machine learning applications for chemical fingerprinting and environmental source tracking using non-target chemical data. Environ. Sci. Technol. 2022, 56 (7), 4080–4090. DOI: 10.1021/acs.est.1c06655.

License

Copyright 2022 Oregon State University. All rights reserved.

Important

The Chemical Fingerprinting Workflow Software found in this GitHub repository (the "Software") may be freely used for educational and research purposes by non-profit institutions and United States Federal Government agencies only. See license txt file for more detail.