Searching molecular structure databases with tandem mass spectra using CSI:FingerID
Open accessAbstract
Significance: Untargeted metabolomics experiments usually rely on tandem MS (MS/MS) to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. Recently, several computational approaches were presented for searching molecular structure databases using MS/MS data. Here, we present CSI:FingerID, which combines fragmentation tree computation and machine learning. An in-depth evaluation on two large-scale datasets shows that our method can find 150% more correct identifications than the second-best search method. In comparison with the two runner-up methods, CSI:FingerID reaches 5.4-fold more unique identifications. We also present evaluations indicating that the performance of our method will further improve when more training data become available. CSI:FingerID is publicly available at www.csi-fingerid.org .
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CSI:FingerID and MIST utilize machine learning to predict these fingerprints directly from the MS/MS data.
“CSI:FingerID164 and MIST165 utilize machine learning to predict these fingerprints directly from the MS/MS data.”
From Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products (2024) · cites this paper as [164]
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- Authors
- Dührkop, K., Shen, H., Meusel, M., Rousu, J., & Böcker, S.
- Affiliations
- Friedrich Schiller University Jena (DE)
- Helsinki Institute for Information Technology (FI)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2015-09-21
- Volume
- 112
- Issue
- 41
- Pages
- 12580-12585
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4611636
- OpenAlex
- W2179948434
- Cited by
- 1,190
- References
- 60
- Citations by year
- 2026: 162 · 2025: 182 · 2024: 166 · 2023: 139 · 2022: 132 · 2021: 106 · 2020: 79 · 2019: 79 · 2018: 64 · 2017: 46 · 2016: 33 · 2015: 2
- FWCI
- 21.00
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (BO 1910/16)
- Suomen Akatemia (268874/MIDAS)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- tandem mass spectrometry, molecular structure databases, fragmentation trees, untargeted metabolomics, PubChem, unknown compound identification
- MeSH terms
- Machine Learning, Animals, Humans, Mass Spectrometry, Databases, Protein, Metabolomics
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