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De Novo Molecular Formula Annotation and Structure Elucidation Using SIRIUS 4

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Book cover Computational Methods and Data Analysis for Metabolomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2104))

Abstract

SIRIUS 4 is the best-in-class computational tool for metabolite identification from high-resolution tandem mass spectrometry data. It offers de novo molecular formula annotation with outstanding accuracy. When searching fragmentation spectra in a structure database, it reaches over 70% correct identifications. A predicted fingerprint, which indicates the presence or absence of thousands of molecular properties, helps to deduce information about the compound of interest even if it is not contained in any structure database. Here, we present best practices and describe how to leverage the full potential of SIRIUS 4, how to incorporate it into your own workflow, and how it adds value to the analysis of mass spectrometry data beyond spectral library search.

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Notes

  1. 1.

    ftp://ftp.ncbi.nlm.nih.gov/pubchem/specifications/pubchem_fingerprints.pdf

  2. 2.

    https://www.ncbi.nlm.nih.gov/pubmed

  3. 3.

    http://www.daylight.com/dayhtml/doc/theory/theory.smarts.html

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Authors and Affiliations

  1. Chair for Bioinformatics, Friedrich-Schiller University, Jena, Germany

    Marcus Ludwig, Markus Fleischauer, Kai Dührkop, Martin A. Hoffmann & Sebastian Böcker

  2. International Max Planck Research School “Exploration of Ecological Interactions with Molecular and Chemical Techniques”, Max Planck Institute for Chemical Ecology, Jena, Germany

    Martin A. Hoffmann

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  1. Marcus Ludwig
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  2. Markus Fleischauer
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  3. Kai Dührkop
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  4. Martin A. Hoffmann
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  5. Sebastian Böcker
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Correspondence to Sebastian Böcker .

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  1. Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA

    Shuzhao Li

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Ludwig, M., Fleischauer, M., Dührkop, K., Hoffmann, M.A., Böcker, S. (2020). De Novo Molecular Formula Annotation and Structure Elucidation Using SIRIUS 4. In: Li, S. (eds) Computational Methods and Data Analysis for Metabolomics. Methods in Molecular Biology, vol 2104. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0239-3_11

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  • DOI: https://doi.org/10.1007/978-1-0716-0239-3_11

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