Publications & Citations
SIRIUS by the numbers
SIRIUS is widely recognized and trusted across the global scientific community, powering high-throughput small molecule identification.
How to Cite
When using SIRIUS please cite the following paper:
SIRIUS4: a rapid tool for turning tandem mass spectra into metabolite structure information
Kai Dührkop, Markus Fleischauer, Marcus Ludwig, Alexander A. Aksenov, Alexey V. Melnik, Marvin Meusel, Pieter C. Dorrestein, Juho Rousu and Sebastian Böcker
Nature Methods 2019, 16(4):299-302
Depending on the modules used, please also cite the following:
Molecular formula annotation
Fragmentation trees reloaded
Sebastian Böcker and Kai Dührkop
J Cheminform 2016, 8:5
SIRIUS: Decomposing isotope patterns for metabolite identification
Sebastian Böcker, Matthias Letzel, Zsuzsanna Lipták and Anton Pervukhin
Bioinformatics, 2009, 25(2):218-24
BUDDY: molecular formula discovery via bottom-up MS/MS interrogation.
Shipei Xing, Sam Shen, Banghua Xu, Xiaoxiao Li, Tao Huan
Nat Methods, 2023, 20(6):881-890
Database-independent molecular formula annotation using Gibbs sampling through ZODIAC
Marcus Ludwig, Louis-Félix Nothias, Kai Dührkop, Irina Koester, Markus Fleischauer, Martin A. Hoffmann, Daniel Petras, Fernando Vargas, Mustafa Morsy, Lihini Aluwihare, Pieter C. Dorrestein, and Sebastian Böcker
Nat Mach Intell, 2020, 2:629–641
Molecular structure annotation
Searching molecular structure databases with tandem mass spectra using CSI:FingerID
Kai Dührkop, Huibin Shen, Marvin Meusel, Juho Rousu and Sebastian Böcker
Proc Natl Acad Sci USA, 2015, 112(41):12580-5
High-confidence structural annotation of metabolites absent from spectral libraries
Martin A. Hoffmann, Louis-Félix Nothias, Marcus Ludwig, Markus Fleischauer, Emily C. Gentry, Michael Witting, Pieter C. Dorrestein, Kai Dührkop, and Sebastian Böcker
Nat Biotechnol, 2022, 40(3):411-421
Compound classification
Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra
Kai Dührkop, Louis-Félix Nothias, Markus Fleischauer, Raphael Reher, Marcus Ludwig, Martin A. Hoffmann, Daniel Petras, William H. Gerwick, Juho Rousu, Pieter C. Dorrestein and Sebastian Böcker
Nat Biotechnol, 2021, 39(4):462-471
ClassyFire: automated chemical classification with a comprehensive, computable taxonomy
Yannick Djoumbou Feunang, Roman Eisner, Craig Knox, Leonid Chepelev, Janna Hastings, Gareth Owen, Eoin Fahy, Christoph Steinbeck, Shankar Subramanian, Evan Bolton, Russell Greiner, David S. Wishart
J Cheminform, 2016, 8:61
NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products
Hyun Woo Kim, Mingxun Wang, Christopher A. Leber, Louis-Félix Nothias, Raphael Reher, Kyo Bin Kang, Justin J. J. van der Hooft, Pieter C. Dorrestein, William H. Gerwick, and Garrison W. Cottrell
J Nat Prod, 2021, 84(11):2795-2807
De novo structure prediction
MSNovelist: de novo structure generation from mass spectra
Michael A Stravs, Kai Dührkop, Sebastian Böcker, and Nicola Zamboni
Nat Methods, 2022, 19(7):865-870
Transformation product generation
BioTransformer 3.0—a web server for accurately predicting metabolic transformation products
David S Wishart, Siyang Tian, Dana Allen, Eponine Oler, Harrison Peters, Vicki W Lui, Vasuk Gautam, Yannick Djoumbou-Feunang, Russell Greiner, and Thomas O Metz
Nucleic Acids Res, 2022, 50(W1):W115-W123
Benchmarking
Critical Assessment of Small Molecule Identification (CASMI) provides standardized blind LC-MS/MS datasets to evaluate how accurately different computational workflows can identify unknown small molecules.
Best Automatic Structural Identification – In Silico Fragmentation Only with by far the most correct IDs.
E. L. Schymanski et al. J. Cheminform. (2017) doi: 10.1186/s13321-017-0207-1
SIRIUS secured top honors in three out of four categories, winning Best Structure Identification on Natural Products, Best Automatic Structural Identification – In Silico Fragmentation Only, and Best Automatic Candidate Ranking.
Again, SIRIUS secured top honors in three out of four categories, winning Correct elemental formulas, Correct compound structure classes, and Correct 2D chemical structures. Moreover, six contestants used SIRIUS in their workflow.
Discoveries
SIRIUS is widely recognized and trusted within the scientific community. We maintain a list of discoveries made by independent research groups using SIRIUS for mass spectrometry-based small molecule annotation. Exciting discoveries and major breakthroughs are highlighted on our blog.
