Machine learning methods for compound annotation in non-targeted mass spectrometry-A brief overview of fingerprinting, in silico fragmentation and de novo methods.
- DOI
- 10.1002/rcm.9876
- Published
- 2024 Oct 30
- Container
- Rapid communications in mass spectrometry : RCM
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1002/rcm.9876,
title = {Machine learning methods for compound annotation in non-targeted mass spectrometry-A brief overview of fingerprinting, in silico fragmentation and de novo methods.},
author = {Russo FF and Nowatzky Y and Jaeger C and Parr MK and Benner P and Muth T and Lisec J},
year = {2024},
journal = {Rapid communications in mass spectrometry : RCM},
doi = {10.1002/rcm.9876},
url = {https://doi.org/10.1002/rcm.9876}
}RIS
TY - JOUR TI - Machine learning methods for compound annotation in non-targeted mass spectrometry-A brief overview of fingerprinting, in silico fragmentation and de novo methods. AU - Russo FF AU - Nowatzky Y AU - Jaeger C AU - Parr MK AU - Benner P AU - Muth T AU - Lisec J PY - 2024 JO - Rapid communications in mass spectrometry : RCM DO - 10.1002/rcm.9876 UR - https://doi.org/10.1002/rcm.9876 ER -
APA
FF, R., Y, N., C, J., MK, P., P, B., T, M., & J, L. (2024). Machine learning methods for compound annotation in non-targeted mass spectrometry-A brief overview of fingerprinting, in silico fragmentation and de novo methods.. Rapid communications in mass spectrometry : RCM. https://doi.org/10.1002/rcm.9876
Source records
- pubmed · retrieved 2026-09-25T18:50:15.790Z