SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information

被引：985
作者：
Duhrkop, Kai [1 ]
Fleischauer, Markus [1 ]
Ludwig, Marcus [1 ]
Aksenov, Alexander A. [2 ,3 ]
Melnik, Alexey V. [2 ,3 ]
Meusel, Marvin [1 ,4 ]
Dorrestein, Pieter C. [2 ,3 ]
Rousu, Juho [5 ]
Bocker, Sebastian [1 ]
机构：
[1] Friedrich Schiller Univ, Chair Bioinformat, Jena, Germany
[2] Univ Calif San Diego, Skaggs Sch Pharm & Pharmaceut Sci, Collaborat Mass Spectrometry Innovat Ctr, La Jolla, CA 92093 USA
[3] Univ Calif San Diego, Skaggs Sch Pharm & Pharmaceut Sci, La Jolla, CA 92093 USA
[4] Saarland Univ, Helmholtz Ctr Infect Res & Pharmaceut Biotechnol, Helmholtz Inst Pharmaceut Res Saarland, Dept Microbial Nat Prod, Saarbrucken, Germany
[5] Aalto Univ, Dept Comp Sci, Helsinki Inst Informat Technol, Espoo, Finland
来源：
NATURE METHODS | 2019年 / 16卷 / 04期
基金：
芬兰科学院;
关键词：
SPECTROMETRY DATA; IDENTIFICATION; FRAGMENTATION; PREDICTION; DATABASES; PRODUCTS;
D O I：
10.1038/s41592-019-0344-8
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
Mass spectrometry is a predominant experimental technique in metabolomics and related fields, but metabolite structural elucidation remains highly challenging. We report SIRIUS 4 (https://bio.informatik.uni-jena.de/sirius/), which provides a fast computational approach for molecular structure identification. SIRIUS 4 integrates CSI:FingerID for searching in molecular structure databases. Using SIRIUS 4, we achieved identification rates of more than 70% on challenging metabolomics datasets.
引用
收藏
页码：299 / +
页数：8
相关论文
共 44 条
  • [31] Finding Maximum Colorful Subtrees in Practice
    Rauf, Imran
    Rasche, Florian
    Nicolas, Francois
    Boecker, Sebastian
    [J]. JOURNAL OF COMPUTATIONAL BIOLOGY, 2013, 20 (04) : 311 - 321
  • [32] Röst HL, 2016, NAT METHODS, V13, P741, DOI [10.1038/nmeth.3959, 10.1038/NMETH.3959]
  • [33] Extended-Connectivity Fingerprints
    Rogers, David
    Hahn, Mathew
    [J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2010, 50 (05) : 742 - 754
  • [34] Critical Assessment of Small Molecule Identification 2016: automated methods
    Schymanski, Emma L.
    Ruttkies, Christoph
    Krauss, Martin
    Brouard, Celine
    Kind, Tobias
    Duehrkop, Kai
    Allen, Felicity
    Vaniya, Arpana
    Verdegem, Dries
    Boecker, Sebastian
    Rousu, Juho
    Shen, Huibin
    Tsugawa, Hiroshi
    Sajed, Tanvir
    Fiehn, Oliver
    Ghesquiere, Bart
    Neumann, Steffen
    [J]. JOURNAL OF CHEMINFORMATICS, 2017, 9
  • [35] Senior JK., 1951, AM J MATH, V73, P663, DOI [10.2307/2372318, DOI 10.2307/2372318]
  • [36] Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning
    Shen, Huibin
    Szedmak, Sandor
    Brouard, Celine
    Rousu, Juho
    [J]. DISCOVERY SCIENCE, (DS 2016), 2016, 9956 : 427 - 441
  • [37] Metabolite identification through multiple kernel learning on fragmentation trees
    Shen, Huibin
    Duhrkop, Kai
    Bocker, Sebastian
    Rousu, Juho
    [J]. BIOINFORMATICS, 2014, 30 (12) : 157 - 164
  • [38] XCMS: Processing mass spectrometry data for metabolite profiling using Nonlinear peak alignment, matching, and identification
    Smith, CA
    Want, EJ
    O'Maille, G
    Abagyan, R
    Siuzdak, G
    [J]. ANALYTICAL CHEMISTRY, 2006, 78 (03) : 779 - 787
  • [39] The Chemistry Development Kit (CDK): An open-source Java']Java library for chemo- and bioinformatics
    Steinbeck, C
    Han, YQ
    Kuhn, S
    Horlacher, O
    Luttmann, E
    Willighagen, E
    [J]. JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2003, 43 (02): : 493 - 500
  • [40] MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis
    Tsugawa, Hiroshi
    Cajka, Tomas
    Kind, Tobias
    Ma, Yan
    Higgins, Brendan
    Ikeda, Kazutaka
    Kanazawa, Mitsuhiro
    VanderGheynst, Jean
    Fiehn, Oliver
    Arita, Masanori
    [J]. NATURE METHODS, 2015, 12 (06) : 523 - +
12345