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</div> </a> <ul id="toc-Data-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Features" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Features"> <div class="vector-toc-text"> <span class="vector-toc-numb">3</span> <span>Features</span> </div> </a> <button aria-controls="toc-Features-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle Features subsection</span> </button> <ul id="toc-Features-sublist" class="vector-toc-list"> <li id="toc-SIRIUS:_Molecular_formula_identification" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#SIRIUS:_Molecular_formula_identification"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.1</span> <span>SIRIUS: Molecular formula identification</span> </div> </a> <ul id="toc-SIRIUS:_Molecular_formula_identification-sublist" class="vector-toc-list"> <li id="toc-Decomposition_of_mass" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Decomposition_of_mass"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.1.1</span> <span>Decomposition of mass</span> </div> </a> <ul id="toc-Decomposition_of_mass-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Isotope_pattern_analysis" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Isotope_pattern_analysis"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.1.2</span> <span>Isotope pattern analysis</span> </div> </a> <ul id="toc-Isotope_pattern_analysis-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Fragmentation_tree_computation" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Fragmentation_tree_computation"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.1.3</span> <span>Fragmentation tree computation</span> </div> </a> <ul id="toc-Fragmentation_tree_computation-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-ZODIAC:_Improved_molecular_formula_identification" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#ZODIAC:_Improved_molecular_formula_identification"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.2</span> <span>ZODIAC: Improved molecular formula identification</span> </div> </a> <ul id="toc-ZODIAC:_Improved_molecular_formula_identification-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-CSI:FingerID:_Structure_database_search" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#CSI:FingerID:_Structure_database_search"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.3</span> <span>CSI:FingerID: Structure database search</span> </div> </a> <ul id="toc-CSI:FingerID:_Structure_database_search-sublist" class="vector-toc-list"> <li id="toc-Molecular_fingerprints" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Molecular_fingerprints"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.3.1</span> <span>Molecular fingerprints</span> </div> </a> <ul id="toc-Molecular_fingerprints-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Predicting_molecular_fingerprints" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Predicting_molecular_fingerprints"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.3.2</span> <span>Predicting molecular fingerprints</span> </div> </a> <ul id="toc-Predicting_molecular_fingerprints-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Comparing_molecular_fingerprints" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Comparing_molecular_fingerprints"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.3.3</span> <span>Comparing molecular fingerprints</span> </div> </a> <ul id="toc-Comparing_molecular_fingerprints-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-COSMIC:_Identification_confidence" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#COSMIC:_Identification_confidence"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.4</span> <span>COSMIC: Identification confidence</span> </div> </a> <ul id="toc-COSMIC:_Identification_confidence-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-CANOPUS:_compound_class_prediction" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#CANOPUS:_compound_class_prediction"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.5</span> <span>CANOPUS: compound class prediction</span> </div> </a> <ul id="toc-CANOPUS:_compound_class_prediction-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Areas_of_application" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Areas_of_application"> <div class="vector-toc-text"> <span class="vector-toc-numb">4</span> <span>Areas of application</span> </div> </a> <button aria-controls="toc-Areas_of_application-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle Areas of application subsection</span> </button> <ul id="toc-Areas_of_application-sublist" class="vector-toc-list"> <li id="toc-Examples_of_application" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Examples_of_application"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.1</span> <span>Examples of application</span> </div> </a> <ul id="toc-Examples_of_application-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Limitations" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Limitations"> <div class="vector-toc-text"> <span class="vector-toc-numb">5</span> <span>Limitations</span> </div> </a> <button aria-controls="toc-Limitations-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle Limitations subsection</span> </button> <ul id="toc-Limitations-sublist" class="vector-toc-list"> <li id="toc-Limitation_of_the_measurement_method" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Limitation_of_the_measurement_method"> <div class="vector-toc-text"> <span class="vector-toc-numb">5.1</span> <span>Limitation of the measurement method</span> </div> </a> <ul id="toc-Limitation_of_the_measurement_method-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Limitation_of_structure_databases" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Limitation_of_structure_databases"> <div class="vector-toc-text"> <span class="vector-toc-numb">5.2</span> <span>Limitation of structure databases</span> </div> </a> <ul id="toc-Limitation_of_structure_databases-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Independent_evaluation_of_the_software" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Independent_evaluation_of_the_software"> <div class="vector-toc-text"> <span class="vector-toc-numb">6</span> <span>Independent evaluation of the software</span> </div> </a> <ul id="toc-Independent_evaluation_of_the_software-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Awards_and_recognition" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Awards_and_recognition"> <div class="vector-toc-text"> <span class="vector-toc-numb">7</span> <span>Awards and recognition</span> </div> </a> <ul id="toc-Awards_and_recognition-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Licences" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Licences"> <div class="vector-toc-text"> <span class="vector-toc-numb">8</span> <span>Licences</span> </div> </a> <ul id="toc-Licences-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Alternatives" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Alternatives"> <div class="vector-toc-text"> <span class="vector-toc-numb">9</span> <span>Alternatives</span> </div> </a> <ul id="toc-Alternatives-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-See_also" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#See_also"> <div class="vector-toc-text"> <span class="vector-toc-numb">10</span> <span>See also</span> </div> </a> <ul id="toc-See_also-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-References" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#References"> <div class="vector-toc-text"> <span class="vector-toc-numb">11</span> <span>References</span> </div> </a> <ul id="toc-References-sublist" class="vector-toc-list"> </ul> </li> </ul> </div> </div> </nav> </div> </div> <div class="mw-content-container"> <main id="content" class="mw-body"> <header class="mw-body-header vector-page-titlebar"> <nav aria-label="Contents" class="vector-toc-landmark"> <div id="vector-page-titlebar-toc" class="vector-dropdown vector-page-titlebar-toc vector-button-flush-left" > <input type="checkbox" id="vector-page-titlebar-toc-checkbox" role="button" aria-haspopup="true" data-event-name="ui.dropdown-vector-page-titlebar-toc" class="vector-dropdown-checkbox " aria-label="Toggle the table of contents" > <label id="vector-page-titlebar-toc-label" 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searchaux" style="display:none">Mass spectrometry software</div> <style data-mw-deduplicate="TemplateStyles:r1236090951">.mw-parser-output .hatnote{font-style:italic}.mw-parser-output div.hatnote{padding-left:1.6em;margin-bottom:0.5em}.mw-parser-output .hatnote i{font-style:normal}.mw-parser-output .hatnote+link+.hatnote{margin-top:-0.5em}@media print{body.ns-0 .mw-parser-output .hatnote{display:none!important}}</style><div role="note" class="hatnote navigation-not-searchable">For other uses, see <a href="/wiki/Sirius_(disambiguation)" class="mw-disambig" title="Sirius (disambiguation)">Sirius (disambiguation)</a>.</div> <style data-mw-deduplicate="TemplateStyles:r1251242444">.mw-parser-output .ambox{border:1px solid #a2a9b1;border-left:10px solid #36c;background-color:#fbfbfb;box-sizing:border-box}.mw-parser-output .ambox+link+.ambox,.mw-parser-output .ambox+link+style+.ambox,.mw-parser-output .ambox+link+link+.ambox,.mw-parser-output .ambox+.mw-empty-elt+link+.ambox,.mw-parser-output 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.infobox-table{display:table!important}body.skin--responsive .mw-parser-output .infobox-table>caption{display:table-caption!important}body.skin--responsive .mw-parser-output .infobox-table>tbody{display:table-row-group}body.skin--responsive .mw-parser-output .infobox-table tr{display:table-row!important}body.skin--responsive .mw-parser-output .infobox-table th,body.skin--responsive .mw-parser-output .infobox-table td{padding-left:inherit;padding-right:inherit}}</style><table class="infobox vevent"><caption class="infobox-title summary">SIRIUS</caption><tbody><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="/wiki/Programmer" title="Programmer">Developer(s)</a></th><td class="infobox-data">Böcker Group at FSU Jena & Bright Giant GmbH</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Initial release</th><td class="infobox-data">2009</td></tr><tr style="display: none;"><td colspan="2" class="infobox-full-data"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1257001546"></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="/wiki/Software_release_life_cycle" title="Software release life cycle">Stable release</a></th><td class="infobox-data"><div style="margin:0px;">5.8.5 / 8 November 2023</div></td></tr><tr style="display:none"><td colspan="2"> </td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="/wiki/Repository_(version_control)" title="Repository (version control)">Repository</a></th><td class="infobox-data"><a rel="nofollow" class="external free" href="https://github.com/boecker-lab/sirius">https://github.com/boecker-lab/sirius</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Written in</th><td class="infobox-data">Java</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="/wiki/Operating_system" title="Operating system">Operating system</a></th><td class="infobox-data">Linux, Windows, MacOS</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Available in</th><td class="infobox-data">English</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="/wiki/Software_categories#Categorization_approaches" title="Software categories">Type</a></th><td class="infobox-data"><a href="/wiki/Mass_spectrometry" title="Mass spectrometry">mass spectrometry</a>,<br /> <a href="/wiki/Structure_elucidation" class="mw-redirect" title="Structure elucidation">structure elucidation</a>,<br /> <a href="/wiki/Chemistry" title="Chemistry">chemistry</a>,<br /> <a href="/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="/wiki/Software_license" title="Software license">License</a></th><td class="infobox-data">GNU Affero General Public License v3.0 for client software,<br /> web-services free for non-commercial use,<br /> commercial subscription offered by Bright Giant GmbH</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Website</th><td class="infobox-data"><a rel="nofollow" class="external free" href="https://bio.informatik.uni-jena.de/software/sirius/">https://bio.informatik.uni-jena.de/software/sirius/</a></td></tr></tbody></table> <p><b>SIRIUS</b> is a <a href="/wiki/Java_(programming_language)" title="Java (programming language)">Java</a>-based <a href="/wiki/Open-source_software" title="Open-source software">open-source software</a> for the identification of <a href="/wiki/Small_molecule" title="Small molecule">small molecules</a> from <a href="/wiki/Fragmentation_(mass_spectrometry)" title="Fragmentation (mass spectrometry)">fragmentation</a> <a href="/wiki/Mass_spectrometry" title="Mass spectrometry">mass spectrometry</a> data without the use of spectral libraries. It combines the analysis of <a href="/w/index.php?title=Isotope_pattern&action=edit&redlink=1" class="new" title="Isotope pattern (page does not exist)">isotope patterns</a> in MS1 spectra with the analysis of <a href="/wiki/Tandem_mass_spectrometry" title="Tandem mass spectrometry">fragmentation patterns in MS2 spectra</a>. SIRIUS is the umbrella application comprising CSI:FingerID, CANOPUS, COSMIC and ZODIAC. </p><p>SIRIUS, including its web services for <a href="/wiki/Structural_elucidation" class="mw-redirect" title="Structural elucidation">structural elucidation</a>, is freely available to use for academic research. Bright Giant GmbH offers subscription-based access to the SIRIUS web services for commercial users. </p><p>SIRIUS is not suitable for analyzing <a href="/wiki/Proteomics" title="Proteomics">proteomics</a> MS data. </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="History">History</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=1" title="Edit section: History"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The SIRIUS software is developed by the group of <a href="/w/index.php?title=Sebastian_B%C3%B6cker&action=edit&redlink=1" class="new" title="Sebastian Böcker (page does not exist)">Sebastian Böcker</a> at the <a href="/wiki/University_of_Jena" title="University of Jena">Friedrich Schiller University Jena</a>, Germany and since 2019 together with Bright Giant GmbH. SIRIUS development started in 2009 as a software for identification of the <a href="/wiki/Chemical_formula#Molecular_formula" title="Chemical formula">molecular formula</a> by decomposing high-resolution isotope patterns (also called MS1 data).<sup id="cite_ref-SIRIUSdecomp_1-0" class="reference"><a href="#cite_note-SIRIUSdecomp-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> The name is an akronym resulting from this original purpose: Sum formula Identification by Ranking Isotope patterns Using mass Spectrometry. </p><p>In 2008 the group introduced the concept of <a href="/w/index.php?title=Fragmentation_trees&action=edit&redlink=1" class="new" title="Fragmentation trees (page does not exist)">fragmentation trees</a><sup id="cite_ref-fragmentation_trees_2-0" class="reference"><a href="#cite_note-fragmentation_trees-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> for identification of the molecular formula based on fragmentation mass spectrometry data, also called <a href="/wiki/Tandem_mass_spectrometry" title="Tandem mass spectrometry">tandem MS or MS2 data</a>. Back then, identification of small molecules was approached by searching in a reference spectral library.<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> Examples of such libraries include <a href="/wiki/MassBank_(database)" class="mw-redirect" title="MassBank (database)">MassBank</a>,<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> METLIN,<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> or <a href="/wiki/National_Institute_of_Standards_and_Technology" title="National Institute of Standards and Technology">NIST</a>/<a href="/wiki/United_States_Environmental_Protection_Agency" title="United States Environmental Protection Agency">EPA</a>/<a href="/wiki/National_Institutes_of_Health" title="National Institutes of Health">NIH</a> EI-MS Library.<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup> However, this is limited to known molecules with available standards that have been measured and put in a reference spectral library. For unknown molecules, identification of the molecular formula is a crucial step.<sup id="cite_ref-fragmentation_trees_2-1" class="reference"><a href="#cite_note-fragmentation_trees-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> In 2011/2012, the group conceived fragmentation trees as a means of structural elucidation by automatically comparing these fragmentation trees.<sup id="cite_ref-fragmentation_trees_AnalChem_7-0" class="reference"><a href="#cite_note-fragmentation_trees_AnalChem-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-tree_alignment_8-0" class="reference"><a href="#cite_note-tree_alignment-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> Fragmentation pattern similarities are strongly correlated with the <a href="/wiki/Chemical_similarity" title="Chemical similarity">chemical similarity</a> of molecules.<sup id="cite_ref-tree_alignment_8-1" class="reference"><a href="#cite_note-tree_alignment-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> Thus, aligning the fragmentation tree of an unknown molecule to a set of known molecules helps to elucidate its structure. Fragmentation trees were introduced in SIRIUS 2.<sup id="cite_ref-fragmentation_trees_AnalChem_7-1" class="reference"><a href="#cite_note-fragmentation_trees_AnalChem-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> </p><p>Also in 2012, the group of <a href="/w/index.php?title=Juho_Rousu&action=edit&redlink=1" class="new" title="Juho Rousu (page does not exist)">Juho Rousu</a> at <a href="/wiki/University_of_Helsinki" title="University of Helsinki">University of Helsinki</a>, Finland, introduced a machine learning method to predict molecular properties from tandem MS data.<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> This concept was brought together with the fragmentation tree concept in 2015 resulting in CSI:FingerID,<sup id="cite_ref-CSI:FingerID_10-0" class="reference"><a href="#cite_note-CSI:FingerID-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> being introduced in SIRIUS 3. The fragmentation tree is used to predict a <a href="/w/index.php?title=Molecular_fingerprint&action=edit&redlink=1" class="new" title="Molecular fingerprint (page does not exist)">molecular fingerprint</a> of the unknown molecule using <a href="/wiki/Machine_learning" title="Machine learning">machine learning</a>, which in turn is used to search a molecular structure database such as <a href="/wiki/PubChem" title="PubChem">PubChem</a>. Molecular structure databases are orders of magnitude larger than reference spectra libraries (PubChem containing ~111 million compounds in 2021<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup> compared to NIST Tandem Mass Spectral Library containing ~50.000 compounds in 2023<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup>). This kind of structure identification refers to the identity and connectivity (with <a href="/wiki/Chemical_bond" title="Chemical bond">bond</a> multiplicities) of the <a href="/wiki/Atom" title="Atom">atoms</a>, but not <a href="/wiki/Stereochemistry" title="Stereochemistry">stereochemistry</a> information. Elucidation of stereochemistry is currently beyond the power of automated search engines. </p><p>SIRIUS 3 also introduced the <a href="/wiki/Graphical_User_Interface" class="mw-redirect" title="Graphical User Interface">Graphical User Interface</a> (GUI). </p><p>In 2020, in cooperation with the group of <a href="/w/index.php?title=Pieter_Dorrestein&action=edit&redlink=1" class="new" title="Pieter Dorrestein (page does not exist)">Pieter C Dorrestein</a> at <a href="/wiki/UC_San_Diego" class="mw-redirect" title="UC San Diego">UC San Diego</a>, USA, molecular formula identification was improved based on derivative networks from complete biological datasets to rank molecular formula candidates.<sup id="cite_ref-ZODIAC_13-0" class="reference"><a href="#cite_note-ZODIAC-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> This method is called ZODIAC and has been integrated into SIRIUS 4.<sup id="cite_ref-SIRIUS4_14-0" class="reference"><a href="#cite_note-SIRIUS4-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> </p><p>Also in 2020, in cooperation with Rousu's and Dorrestein's groups, CANOPUS for systematic compound class annotation was introduced to SIRIUS 4.<sup id="cite_ref-CANOPUS_15-0" class="reference"><a href="#cite_note-CANOPUS-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> </p><p>In 2022, the COSMIC confidence score was added to the CSI:FingerID structure identification workflow in SIRIUS 4, allowing users to determine the trustworthiness of the identification.<sup id="cite_ref-COSMIC_16-0" class="reference"><a href="#cite_note-COSMIC-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Data">Data</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=2" title="Edit section: Data"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>SIRIUS is using data from <a href="/wiki/Liquid_chromatography" class="mw-redirect" title="Liquid chromatography">liquid-chromatography</a> <a href="/wiki/Tandem_mass_spectrometry" title="Tandem mass spectrometry">tandem mass spectrometry</a> (<a href="/wiki/Liquid_chromatography%E2%80%93mass_spectrometry" title="Liquid chromatography–mass spectrometry">LC-MS</a>/MS). It requires high-<a href="/wiki/Resolution_(mass_spectrometry)" title="Resolution (mass spectrometry)">resolution</a>, high mass accuracy MS1 and MS2 data as input. LC is not mandatory for SIRIUS, however is often required to separate individual compounds in complex samples. </p> <ul><li>MS1 data refers mainly to the <a href="/w/index.php?title=Isotope_pattern&action=edit&redlink=1" class="new" title="Isotope pattern (page does not exist)">isotope pattern</a> of the compound. Due to the <a href="/wiki/Isotope" title="Isotope">natural isotopic distributions</a> of the <a href="/wiki/Chemical_element" title="Chemical element">elements</a>, several peaks in the mass spectrum correspond to the same type of sample molecule, reflecting its isotope pattern.<sup id="cite_ref-SIRIUSdecomp_1-1" class="reference"><a href="#cite_note-SIRIUSdecomp-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup></li> <li>MS2 data refers to the fragmentation pattern of the compound. MS2 is also known as <a href="/wiki/Tandem_mass_spectrometry" title="Tandem mass spectrometry">tandem mass spectrometry or MS/MS</a>. The <a href="/wiki/Statistical_model" title="Statistical model">statistical model</a> of SIRIUS and the <a href="/wiki/Machine_learning" title="Machine learning">machine learning</a> model of CSI:FingerID were trained on MS2 spectra created by <a href="/wiki/Collision-induced_dissociation" title="Collision-induced dissociation">collision-induced dissociation</a> (CID), as commonly applied in LC-MS/MS experiments.<sup id="cite_ref-SIRIUS4_review_17-0" class="reference"><a href="#cite_note-SIRIUS4_review-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup></li></ul> <p>SIRIUS expects both, MS1 and MS2 spectra, as input. Omitting the MS1 data is possible, but it will make the analysis more time-consuming and can lead to poorer results. </p><p>SIRIUS and CSI:FingerID have been trained on a wide variety of data, including data from different instrument types. Certain aspects of the mass spectra are important to successfully process the data: </p> <ul><li><b>High mass accuracy:</b> The <a href="/w/index.php?title=Mass_deviation&action=edit&redlink=1" class="new" title="Mass deviation (page does not exist)">mass deviation</a> of the input spectra should be within 20 <a href="/wiki/Parts_per_million" class="mw-redirect" title="Parts per million">ppm</a>. Mass spectrometry devices such as <a href="/wiki/Time-of-flight_mass_spectrometry" title="Time-of-flight mass spectrometry">TOF</a>, <a href="/wiki/Orbitrap" title="Orbitrap">Orbitrap</a> and <a href="/wiki/Fourier-transform_ion_cyclotron_resonance" title="Fourier-transform ion cyclotron resonance">FT-ICR</a> usually provide data with high mass accuracy, as do <a href="/wiki/Hybrid_mass_spectrometer" title="Hybrid mass spectrometer">coupled devices</a> such as Q-TOF, IT-TOF or IT-Orbitrap. Spectra measured with a <a href="/wiki/Quadrupole_mass_analyzer" title="Quadrupole mass analyzer">quadrupole</a> or linear trap do not provide the required accuracy for data analysis with SIRIUS.</li> <li><b>Rich fragmentation spectra:</b> It is not possible to deduce the structure or even the molecular formula from an MS2 spectrum that contains almost no peaks. Prior noise filtering of the spectra is not necessary and not favorable. SIRIUS considers up to 60 peaks in the fragmentation spectrum and decides for itself which of these peaks are regarded as noise.</li> <li><b>Centroided MS data:</b> SIRIUS does not contain routines for peak picking from profile-mode spectra. msConvert in <a href="/wiki/ProteoWizard" title="ProteoWizard">ProteoWizard</a> can be used to convert to centroided data. Additionally, there are several tools specialized for the preprocessing task, such as <a href="/wiki/OpenMS" title="OpenMS">OpenMS</a>, <a href="/w/index.php?title=MZmine&action=edit&redlink=1" class="new" title="MZmine (page does not exist)">MZmine</a> or <a href="/wiki/XCMS_Online" title="XCMS Online">XCMS</a>. OpenMS<sup id="cite_ref-18" class="reference"><a href="#cite_note-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup> and MZmine 3<sup id="cite_ref-19" class="reference"><a href="#cite_note-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup> both provide export functions tailored to the needs for SIRIUS.</li></ul> <p>Different common <a href="/wiki/Mass_spectrometry_data_format" title="Mass spectrometry data format">MS file formats</a>, such as .csv, .ms or .mgf files, can be imported to SIRIUS. SIRIUS can import full LC-MS-runs (.mzML) or single compounds. At present, SIRIUS only handles single-charged compounds.<sup id="cite_ref-SIRIUS4_review_17-1" class="reference"><a href="#cite_note-SIRIUS4_review-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Features">Features</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=3" title="Edit section: Features"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>SIRIUS identifies small molecules in a two step approach:<sup id="cite_ref-SIRIUS4_review_17-2" class="reference"><a href="#cite_note-SIRIUS4_review-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> </p> <ul><li>First, the molecular formula of the molecule is determined.</li> <li>Second, a molecular fingerprint is predicted to search against a structure database to identify the most likely candidate.</li></ul> <p>The following algorithms are implemented in SIRIUS: </p> <div class="mw-heading mw-heading3"><h3 id="SIRIUS:_Molecular_formula_identification">SIRIUS: Molecular formula identification</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=4" title="Edit section: SIRIUS: Molecular formula identification"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>SIRIUS is the name of the umbrella application, but (for historic reasons) also the name for the identification of the molecular formula. <a href="/wiki/Chemical_formula#Molecular_formula" title="Chemical formula">Molecular formula</a> refers to the elemental composition of the molecule. The mere mass of a molecule is not sufficient to determine the correct molecular formula.<sup id="cite_ref-SIRIUS4_review_17-3" class="reference"><a href="#cite_note-SIRIUS4_review-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> Even with very high mass accuracy, many molecular formulas can explain a mass measured in a spectrum, in particular in higher mass regions. In SIRIUS, molecular formula identification is done using isotope pattern analysis on the MS1 data as well as fragmentation tree computation on the MS2 data. The score of a molecular formula candidate is a combination of the isotope pattern score and the fragmentation tree score. </p><p>To identify the molecular formula, SIRIUS is considering all possible molecular formulas for a set of elements. The elements most abundant in living beings are <a href="/wiki/Hydrogen" title="Hydrogen">hydrogen</a> (H), <a href="/wiki/Carbon" title="Carbon">carbon</a> (C), <a href="/wiki/Nitrogen" title="Nitrogen">nitrogen</a> (N), <a href="/wiki/Oxygen" title="Oxygen">oxygen</a> (O), and <a href="/wiki/Phosphor" title="Phosphor">phosphor</a> (P). This is the default set of elements in SIRIUS. Some less common elements result in very characteristic isotope pattern changes and can be automatically detected.<sup id="cite_ref-20" class="reference"><a href="#cite_note-20"><span class="cite-bracket">[</span>20<span class="cite-bracket">]</span></a></sup> Detectable elements are <a href="/wiki/Sulfur" title="Sulfur">sulfur</a> (S), <a href="/wiki/Chlorine" title="Chlorine">chlorine</a> (Cl), <a href="/wiki/Bromine" title="Bromine">bromine</a> (Br), <a href="/wiki/Boron" title="Boron">boron</a> (B) and <a href="/wiki/Selenium" title="Selenium">selenium</a> (Se). The current version of SIRIUS uses a <a href="/wiki/Deep_neural_network" class="mw-redirect" title="Deep neural network">deep neural network</a> for auto-detection of elements from the isotope and fragmentation pattern of the query molecule.<sup id="cite_ref-SIRIUS4_14-1" class="reference"><a href="#cite_note-SIRIUS4-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> </p><p>For very large molecules or in case of missing data (e.g., a missing isotope pattern), it is possible to restrict SIRIUS to molecular formulas found in a database, such as PubChem. </p> <div class="mw-heading mw-heading4"><h4 id="Decomposition_of_mass">Decomposition of mass</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=5" title="Edit section: Decomposition of mass"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>In order to quickly generate a manageable number of molecular formula candidates, the monoisotopic mass is decomposed into all possible molecular formulas that would lead to this mass. There are two definitions of the monoisotopic mass:<sup id="cite_ref-Algo_MS_book_21-0" class="reference"><a href="#cite_note-Algo_MS_book-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup> (1) the sum of the masses of the most abundant naturally occurring stable isotope of each atom (i.e. the highest peak of the isotope pattern) (2) the sum of the masses of the lightest naturally occurring stable isotope of each atom (i.e. the peak of the isotope pattern with the lowest mass). For small molecules, the lightest peak is also mostly the highest peak of the isotope pattern. However, in the computational context of SIRIUS, the second definition is used. </p><p>Decomposing the monoisotopic mass into all possible molecular formulas requires a mass interval taking into account the measurement inaccuracy of the instrument. This <a href="/wiki/Real_number" title="Real number">real-valued</a> decomposition is transformed into a problem instance with <a href="/wiki/Integer" title="Integer">integer</a> masses by using a blowup factor. The resulting problem is known as <a href="/wiki/Change-making_problem" title="Change-making problem">Change-making problem</a> which is well-studied and can be solved in runtime linear in the size of the output.<sup id="cite_ref-22" class="reference"><a href="#cite_note-22"><span class="cite-bracket">[</span>22<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading4"><h4 id="Isotope_pattern_analysis">Isotope pattern analysis</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=6" title="Edit section: Isotope pattern analysis"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Isotope patterns of the candidate molecular formulas are simulated starting with the isotopic distributions of the individual elements, and then combining these distributions by folding.<sup id="cite_ref-23" class="reference"><a href="#cite_note-23"><span class="cite-bracket">[</span>23<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-SIRIUSdecomp_1-2" class="reference"><a href="#cite_note-SIRIUSdecomp-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> </p><p>The simulated isotope pattern is compared with the measured pattern by assigning probabilities to the observed masses and intensities.<sup id="cite_ref-SIRIUSdecomp_1-3" class="reference"><a href="#cite_note-SIRIUSdecomp-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading4"><h4 id="Fragmentation_tree_computation">Fragmentation tree computation</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=7" title="Edit section: Fragmentation tree computation"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>A <a href="/w/index.php?title=Fragmentation_tree&action=edit&redlink=1" class="new" title="Fragmentation tree (page does not exist)">fragmentation tree</a> is a representation of the fragmentation process similar to “fragmentation diagrams” created by experts. The fragmentation tree annotates the MS2 spectrum by providing a molecular formula for each fragment peak. Peaks that do not receive an annotation are considered noise peaks. The fragmentation tree also predicts the fragmentation reactions (called losses) leading to the fragment peaks. Fragmentation trees are a valuable tool for deducing information about the fragmentation but are not a precise depiction of the actual fragmentation process.<sup id="cite_ref-fragmentation_trees_AnalChem_7-2" class="reference"><a href="#cite_note-fragmentation_trees_AnalChem-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> </p><p>To identify the molecular formula of an unknown molecule, a separate fragmentation tree is computed for every molecular formula candidate. In other words, the method attempts to reconstruct the fragmentation process that led to this MS2 spectrum for each candidate molecular formula. This allows to compare the different hypotheses that a particular candidate is actual the correct molecular formula. The best-scoring fragmentation tree (i.e. the fragmentation process that is best explaining the spectrum) corresponds to the most likely molecular formula explanation. </p> <div class="mw-heading mw-heading3"><h3 id="ZODIAC:_Improved_molecular_formula_identification">ZODIAC: Improved molecular formula identification</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=8" title="Edit section: ZODIAC: Improved molecular formula identification"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>ZODIAC improves the ranking of the formula candidates provided by SIRIUS.<sup id="cite_ref-ZODIAC_13-1" class="reference"><a href="#cite_note-ZODIAC-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> Organisms produce related metabolites derived from multiple but limited <a href="/wiki/Biosynthesis" title="Biosynthesis">biosynthetic</a> pathways. For a full LC-MS/MS run that is derived from a biological sample or any other set of <a href="/wiki/Derivative_(chemistry)" title="Derivative (chemistry)">derivatives</a> the relation of the <a href="/wiki/Metabolite" title="Metabolite">metabolites</a> is reflected in their similarity. Those similarities are in turn reflected in joint fragments and losses between the fragmentation trees and can be leveraged to improve molecular formula identification of the individual molecules. </p><p>ZODIAC uses the top X molecular formula candidates for each molecule from SIRIUS to build a similarity network, and uses <a href="/wiki/Bayesian_statistics" title="Bayesian statistics">Bayesian statistics</a> to re-rank those candidates. Prior <a href="/wiki/Probability" title="Probability">probabilities</a> are derived from fragmentation tree similarity. Finding an optimal solution to the resulting computational problem is <a href="/wiki/NP-hardness" title="NP-hardness">NP-hard</a>, therefore <a href="/wiki/Gibbs_sampling" title="Gibbs sampling">Gibbs sampling</a> is used. </p><p>ZODIAC stands for <i>ZODIAC: Organic compound Determination by Integral Assignment of elemental Compositions</i>. </p> <div class="mw-heading mw-heading3"><h3 id="CSI:FingerID:_Structure_database_search">CSI:FingerID: Structure database search</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=9" title="Edit section: CSI:FingerID: Structure database search"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>CSI:FIngerID identifies the structure of a molecule by predicting its molecular fingerprint and using this fingerprint to search in a molecular structure database.<sup id="cite_ref-CSI:FingerID_10-1" class="reference"><a href="#cite_note-CSI:FingerID-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading4"><h4 id="Molecular_fingerprints">Molecular fingerprints</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=10" title="Edit section: Molecular fingerprints"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>A molecular fingerprint is a binary <a href="/wiki/Row_and_column_vectors" title="Row and column vectors">vector</a>, where each position corresponds to a specific <a href="/wiki/Molecular_property" title="Molecular property">molecular property</a>. In this representation, a given position X may encode the presence or absence of a particular substructure, with '1' indicating presence and '0' indicating absence. Various types of molecular fingerprints exist, including <a href="/wiki/PubChem" title="PubChem">PubChem</a> CACTVS fingerprints, Klekota-Roth fingerprints,<sup id="cite_ref-24" class="reference"><a href="#cite_note-24"><span class="cite-bracket">[</span>24<span class="cite-bracket">]</span></a></sup> MACCS fingerprints, and Extended-Connectivity Fingerprints (ECFP).<sup id="cite_ref-25" class="reference"><a href="#cite_note-25"><span class="cite-bracket">[</span>25<span class="cite-bracket">]</span></a></sup> A molecular fingerprint can be deterministically computed from a given molecular structure. Different molecular structures may yield the same molecular fingerprint. </p> <div class="mw-heading mw-heading4"><h4 id="Predicting_molecular_fingerprints">Predicting molecular fingerprints</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=11" title="Edit section: Predicting molecular fingerprints"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>CSI:FingerID predicts a probabilistic fingerprint with a variety of molecular properties from several fingerprint types. The fingerprint is predicted from the given spectrum and its corresponding fragmentation tree using deep kernel learning,<sup id="cite_ref-26" class="reference"><a href="#cite_note-26"><span class="cite-bracket">[</span>26<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-CSI:FingerID_10-2" class="reference"><a href="#cite_note-CSI:FingerID-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> which is a combination of <a href="/wiki/Kernel_method" title="Kernel method">kernel methods</a> and <a href="/wiki/Deep_learning" title="Deep learning">deep neural networks</a>. Not only the top scoring molecular formula but multiple high-scoring molecular formula candidates are considered. </p> <div class="mw-heading mw-heading4"><h4 id="Comparing_molecular_fingerprints">Comparing molecular fingerprints</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=12" title="Edit section: Comparing molecular fingerprints"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>To search in a molecular structure database requires a <a href="/wiki/Metric_space" title="Metric space">metric</a> to compare and score the molecular fingerprints. <a href="/wiki/Jaccard_index" title="Jaccard index">Tanimoto similarity (Jaccard index)</a> is a commonly employed metric. A similarity value of 1 signifies identical fingerprints, while a value of 0 indicates structures that do not share any molecular properties. The calculated similarity value depends on the choice of fingerprint type. </p><p>CSI:FingerID employs a <a href="/wiki/Logarithm" title="Logarithm">logarithmic</a> <a href="/wiki/Posterior_probability" title="Posterior probability">posterior probability</a> to rank the structure candidates, where scores are represented as negative numbers, and zero is the optimum.<sup id="cite_ref-27" class="reference"><a href="#cite_note-27"><span class="cite-bracket">[</span>27<span class="cite-bracket">]</span></a></sup> This scoring function results in a higher number of correct identifications.<sup id="cite_ref-CSI:FingerID_10-3" class="reference"><a href="#cite_note-CSI:FingerID-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> Tanimoto similarities are also given. </p> <div class="mw-heading mw-heading3"><h3 id="COSMIC:_Identification_confidence">COSMIC: Identification confidence</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=13" title="Edit section: COSMIC: Identification confidence"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The COSMIC confidence score assigns a confidence to CSI:FingerID structure identifications.<sup id="cite_ref-COSMIC_16-1" class="reference"><a href="#cite_note-COSMIC-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> The idea is similar to <a href="/wiki/False_discovery_rate" title="False discovery rate">False Discovery Rates</a>: All molecules in a large dataset are analysed using CSI:FingerID, the top-ranked hit for each molecule will be evaluated by COSMIC and the most trustworthy identifications can be selected for further analysis. COSMIC does not re-rank structure candidates of a particular molecule nor does it discard any identifications. </p><p>COSMIC employs a confidence score that combines <a href="/wiki/E-values" title="E-values">E-value</a> estimation and a linear <a href="/wiki/Support_vector_machine" title="Support vector machine">support vector machine</a> (SVM) with enforced directionality. Calibration of CSI:FingerID scores is achieved using E-value estimates.<sup id="cite_ref-28" class="reference"><a href="#cite_note-28"><span class="cite-bracket">[</span>28<span class="cite-bracket">]</span></a></sup> Generating decoys for small molecule structures is a non-trivial task, that is why candidates in PubChem serve as a proxy for decoys here. </p><p>The score distribution is modeled as a <a href="/wiki/Mixture_distribution" title="Mixture distribution">mixture distribution</a> of <a href="/wiki/Log-normal_distribution" title="Log-normal distribution">log-normal distributions</a>, and the <a href="/wiki/P-value" title="P-value">P-value</a> and <a href="/wiki/E-values" title="E-values">E-value</a> of a hit score are estimated using the kernel density estimate of PubChem candidate scores. The SVM is employed to classify whether a hit is correct, utilizing features such as the calibrated score, score differences to other candidates, the total peak intensity explained by the fragmentation tree, and the cardinality of molecular fingerprints. Learning is constrained to a linear SVM to mitigate the risk of overfitting, and the directionality of features is enforced. This involves making upfront decisions about whether high or low values of a feature should enhance the confidence in an identification. For instance, a high CSI:FingerID score of a hit should increase but never decrease the confidence that the hit is correct. Some features necessitate the existence of at least two candidates for comparison, and separate SVMs are trained for single instances. The decision values of the SVM are mapped to <a href="/wiki/Posterior_probability" title="Posterior probability">posterior probability</a> estimates using <a href="/wiki/Platt_scaling" title="Platt scaling">Platt scaling</a>.<sup id="cite_ref-29" class="reference"><a href="#cite_note-29"><span class="cite-bracket">[</span>29<span class="cite-bracket">]</span></a></sup> This comprehensive approach ensures a robust and nuanced assessment of the confidence in molecule identifications.<sup id="cite_ref-COSMIC_16-2" class="reference"><a href="#cite_note-COSMIC-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="CANOPUS:_compound_class_prediction">CANOPUS: compound class prediction</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=14" title="Edit section: CANOPUS: compound class prediction"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>CANOPUS is short for <i>class assignment and ontology prediction using mass spectrometry</i>.<sup id="cite_ref-CANOPUS_15-1" class="reference"><a href="#cite_note-CANOPUS-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> It predicts the compound classes from the molecular fingerprint predicted by CSI:FingerID. This approach is completely database-free, i.e. it is not even limited to molecules that are listed in structure databases. </p><p>CANOPUS employs a <a href="/wiki/Deep_learning" title="Deep learning">deep neural network</a> (DNN)<sup id="cite_ref-30" class="reference"><a href="#cite_note-30"><span class="cite-bracket">[</span>30<span class="cite-bracket">]</span></a></sup> to predict 2,497 compound classes. The DNN was trained on 4.10 million compound structures with compound classes assigned by ClassyFire.<sup id="cite_ref-31" class="reference"><a href="#cite_note-31"><span class="cite-bracket">[</span>31<span class="cite-bracket">]</span></a></sup> No MS/MS data was used for training, but instead simulated ‘realistic’ probabilistic fingerprints for the training molecular structures were used. The DNN predicts all compound classes simultaneously. </p><p>For full biological datasets, CANOPUS provides a comprehensive overview of compound classes present in the sample and allows for comparisons between different cohorts at compound class level. </p> <div class="mw-heading mw-heading2"><h2 id="Areas_of_application">Areas of application</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=15" title="Edit section: Areas of application"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Small molecules are essential components found throughout nature, playing a significant role in various fields such as <a href="/wiki/Drug_discovery" title="Drug discovery">drug discovery</a>, <a href="/wiki/Diagnosis" title="Diagnosis">diagnostics</a>, <a href="/wiki/Food_science" title="Food science">food science</a>, <a href="/wiki/Environmental_monitoring" title="Environmental monitoring">environmental monitoring</a>, and more. Effectively addressing many <a href="/wiki/Global_challenges" class="mw-redirect" title="Global challenges">global challenges</a> hinges on the comprehensive identification of small molecules in complex samples. These complex mixtures contain thousands of different molecules measurable in a single mass spectrometry run. </p><p>The identification of unknown small molecules is considered a critical bottleneck in <a href="/wiki/Metabolomics" title="Metabolomics">metabolomics</a>, <a href="/wiki/Natural_product" title="Natural product">natural product</a> research, and related fields, given that widely over 90% of all small molecules remain unknown.<sup id="cite_ref-32" class="reference"><a href="#cite_note-32"><span class="cite-bracket">[</span>32<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-33" class="reference"><a href="#cite_note-33"><span class="cite-bracket">[</span>33<span class="cite-bracket">]</span></a></sup> Commonly, analyses were based on targeted approaches that are limited to the rediscovery of known molecules. In contrast, untargeted analysis is a top-down strategy that avoids the need for a prior specific <a href="/wiki/Hypothesis" title="Hypothesis">hypothesis</a> on expected small molecules. The focus shifts from asking, "Is molecule X present in the sample?" to "Which (unknown) molecules are present in the sample and might be relevant for downstream analysis?" </p><p>SIRIUS is designed for the untargeted structural elucidation of unknown molecules, addressing various challenges: </p> <ul><li>The correct molecular structure is prominently ranked from an extensive list of candidates. This can be compared to a Google search where the optimal answer is expected to be among the top three.<sup id="cite_ref-CSI:FingerID_10-4" class="reference"><a href="#cite_note-CSI:FingerID-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup></li> <li>It can be assessed whether the top candidate is indeed correct.<sup id="cite_ref-COSMIC_16-3" class="reference"><a href="#cite_note-COSMIC-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup></li> <li>Structural information is available even for molecules absent in extensive structure databases, including details on compound class and substructure information.<sup id="cite_ref-CANOPUS_15-2" class="reference"><a href="#cite_note-CANOPUS-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup></li></ul> <div class="mw-heading mw-heading3"><h3 id="Examples_of_application">Examples of application</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=16" title="Edit section: Examples of application"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Neonatal" class="mw-redirect" title="Neonatal">Neonatal</a> <a href="/wiki/Dried_blood_spot" title="Dried blood spot">dried blood spots</a> are important for <a href="/wiki/Newborn_screening" title="Newborn screening">newborn screening</a> and a powerful source for investigating the potential metabolic <a href="/wiki/Etiologies" class="mw-redirect" title="Etiologies">etiologies</a> of various diseases using untargeted LC-MS-based metabolomics. Researchers used SIRIUS to investigate the stability of metabolites and classes of molecules in neonatal dried blood spot biobanks.<sup id="cite_ref-34" class="reference"><a href="#cite_note-34"><span class="cite-bracket">[</span>34<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Marine_microorganisms" title="Marine microorganisms">Marine microorganisms</a> offer a rich source of <a href="/wiki/Biological_activity" title="Biological activity">bioactive compounds</a> with unique structures and remarkable biological activity. This makes them an important resource for the search for new <a href="/wiki/Pharmacology" title="Pharmacology">therapeutic compounds</a>. Researchers are using SIRIUS, to narrow down the search to the most promising microorganisms.<sup id="cite_ref-35" class="reference"><a href="#cite_note-35"><span class="cite-bracket">[</span>35<span class="cite-bracket">]</span></a></sup></li> <li>Pediatric <a href="/wiki/Asthma" title="Asthma">asthma</a> poses diagnostic challenges due to its variable presentation. <a href="/wiki/Breath_analysis" title="Breath analysis">Breath analysis</a> could be a game-changer in pediatric allergic asthma management. By identifying unique exhaled metabolic signatures using SIRIUS, researchers developed an approach to diagnose children with allergic asthma.<sup id="cite_ref-36" class="reference"><a href="#cite_note-36"><span class="cite-bracket">[</span>36<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Thiacloprid" title="Thiacloprid">Thiacloprid</a> is a first-generation, widely used, <a href="/wiki/Neonicotinoid" title="Neonicotinoid">neonicotinoid</a> <a href="/wiki/Insecticide" title="Insecticide">insecticide</a>. Its persistence in the environment and potential adverse effects on human health have raised significant concerns. Elucidating the impurity profile of pesticides is crucial for assessing their environmental impact and potential risks, and setting acceptable limits for impurities. Using SIRIUS, researchers demonstrated an approach for identifying structurally related impurities in pesticides.<sup id="cite_ref-37" class="reference"><a href="#cite_note-37"><span class="cite-bracket">[</span>37<span class="cite-bracket">]</span></a></sup></li> <li>Under certain conditions, two <a href="/wiki/Bacteria" title="Bacteria">bacterial species</a> can thrive together in a dual-species <a href="/wiki/Biofilm" title="Biofilm">biofilm</a>. The cooperation between <a href="/wiki/P._aeruginosa" class="mw-redirect" title="P. aeruginosa">P. aeruginosa</a> and <a href="/wiki/Staphylococcus_aureus" title="Staphylococcus aureus">S. aureus</a> in <a href="/wiki/Cystic_fibrosis" title="Cystic fibrosis">cystic fibrosis</a> leads to increased disease severity. Using SIRIUS, researchers identified a metabolite that could be related to the increased <a href="/wiki/Pathogenesis" title="Pathogenesis">pathogenesis</a> of this dual-species biofilm in cystic fibrosis.<sup id="cite_ref-38" class="reference"><a href="#cite_note-38"><span class="cite-bracket">[</span>38<span class="cite-bracket">]</span></a></sup></li> <li>Our skin hosts a diverse community of <a href="/wiki/Microorganisms" class="mw-redirect" title="Microorganisms">microorganisms</a> known as the <a href="/wiki/Skin_microbiota" class="mw-redirect" title="Skin microbiota">skin microbiota</a>. Using SIRIUS, researchers identified changes in the skin metabolome that are more pronounced than changes in the microbial composition, suggesting that even subtle shifts in microbial abundance can lead to significant effects on the skin.<sup id="cite_ref-39" class="reference"><a href="#cite_note-39"><span class="cite-bracket">[</span>39<span class="cite-bracket">]</span></a></sup></li></ul> <div class="mw-heading mw-heading2"><h2 id="Limitations">Limitations</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=17" title="Edit section: Limitations"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-heading mw-heading3"><h3 id="Limitation_of_the_measurement_method">Limitation of the measurement method</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=18" title="Edit section: Limitation of the measurement method"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Mass spectra alone lack sufficient information to unambiguously identify every molecule. Some molecules produce almost indistinguishable spectra – even more similar than the same molecule measured on two different instruments.<sup id="cite_ref-Algo_MS_book_21-1" class="reference"><a href="#cite_note-Algo_MS_book-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup> Extensive follow-up experiments are required for unambiguous identification. </p><p>Based thereon, it is impossible to always correctly identify a molecular structure merely from a mass spectrum. Thus, CSI:FingerID as well as other methods for structure database search, cannot guarantee finding the correct molecular structure as first hit. That is why it is important to have the correct structure ranked very high from an extensive list of candidates and to assess the confidence in the top hit. </p> <div class="mw-heading mw-heading3"><h3 id="Limitation_of_structure_databases">Limitation of structure databases</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=19" title="Edit section: Limitation of structure databases"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Structure databases are orders of magnitude larger than spectral libraries but still incomplete.<sup id="cite_ref-40" class="reference"><a href="#cite_note-40"><span class="cite-bracket">[</span>40<span class="cite-bracket">]</span></a></sup> It is understood that not every existing biomolecule is or will be contained in structure databases. </p><p>For these instances, SIRIUS offers several solutions: </p> <ul><li>SIRIUS can search in databases of hypothetical structures.<sup id="cite_ref-COSMIC_16-4" class="reference"><a href="#cite_note-COSMIC-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> This could be for example interesting for finding derivatives.</li> <li>The predicted molecular fingerprint offers structural information about, e.g., substructures.<sup id="cite_ref-CSI:FingerID_10-5" class="reference"><a href="#cite_note-CSI:FingerID-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup></li> <li>CANOPUS predicts the compound classes of a molecule without searching in a database.<sup id="cite_ref-CANOPUS_15-3" class="reference"><a href="#cite_note-CANOPUS-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup></li></ul> <div class="mw-heading mw-heading2"><h2 id="Independent_evaluation_of_the_software">Independent evaluation of the software</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=20" title="Edit section: Independent evaluation of the software"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>CASMI (Critical Assessment of Small Molecule Identification)<sup id="cite_ref-41" class="reference"><a href="#cite_note-41"><span class="cite-bracket">[</span>41<span class="cite-bracket">]</span></a></sup> is an open contest on the identification of small molecules from mass spectrometry data, and was launched in 2012 by <a href="/wiki/Emma_Schymanski" title="Emma Schymanski">Emma Schymanski</a> and <a href="/w/index.php?title=Steffen_Neumann&action=edit&redlink=1" class="new" title="Steffen Neumann (page does not exist)">Steffen Neumann</a>.<sup id="cite_ref-42" class="reference"><a href="#cite_note-42"><span class="cite-bracket">[</span>42<span class="cite-bracket">]</span></a></sup> </p><p>In CASMI 2016, CSI:FingerID and a derivative of CSI:FingerID, in which the Böcker Group was also involved, won first and second place in the category “Best Automatic Structural Identification - In Silico Fragmentation Only”. Also, CSI:FingerID had the best result for ranking the correct molecule structure at position one (70 out of 127, positive mode).<sup id="cite_ref-43" class="reference"><a href="#cite_note-43"><span class="cite-bracket">[</span>43<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-44" class="reference"><a href="#cite_note-44"><span class="cite-bracket">[</span>44<span class="cite-bracket">]</span></a></sup> </p><p>In CASMI 2017, SIRIUS plus CSI:FingerID won in 3 of 4 categories: “Best Structure Identification on Natural Products”, “Best Automatic Structural Identification - In Silico Fragmentation Only”, “Best Automatic Candidate Ranking”.<sup id="cite_ref-45" class="reference"><a href="#cite_note-45"><span class="cite-bracket">[</span>45<span class="cite-bracket">]</span></a></sup> </p><p>In CASMI 2022, six out of 16 contestants used SIRIUS in their workflow to identify the best molecular structure candidates. SIRIUS won in the categories “Correct elemental formulas”, “Correct compound structure classes” and “Correct 2D chemical structures”. CASMI 2022 included compounds that were not even contained in PubChem.<sup id="cite_ref-46" class="reference"><a href="#cite_note-46"><span class="cite-bracket">[</span>46<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Awards_and_recognition">Awards and recognition</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=21" title="Edit section: Awards and recognition"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Sebastian Böcker's group at FSU Jena won the 2022 <a href="/w/index.php?title=Thuringian_Research_Award&action=edit&redlink=1" class="new" title="Thuringian Research Award (page does not exist)">Thuringian Research Award</a> in the Applied Research category for SIRIUS and the underlying methods.<sup id="cite_ref-47" class="reference"><a href="#cite_note-47"><span class="cite-bracket">[</span>47<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-48" class="reference"><a href="#cite_note-48"><span class="cite-bracket">[</span>48<span class="cite-bracket">]</span></a></sup> </p><p>SIRIUS was recognized as a "method to watch" by <a href="/wiki/Nature_Methods" title="Nature Methods">Nature Methods</a> in 2020.<sup id="cite_ref-49" class="reference"><a href="#cite_note-49"><span class="cite-bracket">[</span>49<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Licences">Licences</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=22" title="Edit section: Licences"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>SIRIUS is developed by the group of Sebastian Böcker at the FSU Jena in close collaboration with the Bright Giant GmbH. SIRIUS is provided as a <a href="/wiki/Software-as-a-service" class="mw-redirect" title="Software-as-a-service">software-as-a-service</a> solution. The <a href="/wiki/Client_software" class="mw-redirect" title="Client software">client software</a> is <a href="/wiki/Open-source" class="mw-redirect" title="Open-source">open-source</a> and installed on the users’ computers. Molecular formula annotation using fragmentation trees and isotope pattern analysis is performed on your local computer without <a href="/wiki/Subscription" class="mw-redirect" title="Subscription">subscription</a> requirement. </p><p>The SIRIUS <a href="/wiki/Web_services" class="mw-redirect" title="Web services">web services</a> for structural elucidation, including molecular fingerprint prediction, structure database search, confidence score assessment and compound class prediction, require a user account. The web services are free for academic/<a href="/wiki/Non-commercial" class="mw-redirect" title="Non-commercial">non-commercial</a> use provided/hosted by the FSU Jena. <a href="/wiki/Academic_institutions" class="mw-redirect" title="Academic institutions">Academic institutions</a> are identified by their <a href="/wiki/Email_address" title="Email address">email domain</a> and access will be granted automatically. In some cases, further validation might be required. </p><p>Bright Giant GmbH offers subscription-based access to the SIRIUS web services for structural elucidation for commercial users. </p> <div class="mw-heading mw-heading2"><h2 id="Alternatives">Alternatives</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=23" title="Edit section: Alternatives"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Other <a href="/wiki/Algorithms" class="mw-redirect" title="Algorithms">algorithms</a> and software for searching in structure databases are <a href="/w/index.php?title=CFM-ID&action=edit&redlink=1" class="new" title="CFM-ID (page does not exist)">CFM-ID</a>,<sup id="cite_ref-50" class="reference"><a href="#cite_note-50"><span class="cite-bracket">[</span>50<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-51" class="reference"><a href="#cite_note-51"><span class="cite-bracket">[</span>51<span class="cite-bracket">]</span></a></sup> <a href="/w/index.php?title=ICEBERG_(algorithm)&action=edit&redlink=1" class="new" title="ICEBERG (algorithm) (page does not exist)">ICEBERG</a>,<sup id="cite_ref-52" class="reference"><a href="#cite_note-52"><span class="cite-bracket">[</span>52<span class="cite-bracket">]</span></a></sup> <a href="/w/index.php?title=MetFrag&action=edit&redlink=1" class="new" title="MetFrag (page does not exist)">MetFrag</a>,<sup id="cite_ref-53" class="reference"><a href="#cite_note-53"><span class="cite-bracket">[</span>53<span class="cite-bracket">]</span></a></sup> <a href="/w/index.php?title=MS-FINDER&action=edit&redlink=1" class="new" title="MS-FINDER (page does not exist)">MS-FINDER</a>,<sup id="cite_ref-54" class="reference"><a href="#cite_note-54"><span class="cite-bracket">[</span>54<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-55" class="reference"><a href="#cite_note-55"><span class="cite-bracket">[</span>55<span class="cite-bracket">]</span></a></sup> MetaboScape® (<a href="/wiki/Bruker" title="Bruker">Bruker</a>), MassHunter (<a href="/wiki/Agilent_Technologies" title="Agilent Technologies">Agilent</a>) or Compound Discoverer™ (<a href="/wiki/Thermo_Fisher_Scientific" title="Thermo Fisher Scientific">Thermo Fisher Scientific</a>). </p> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=24" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Tandem_mass_spectrometry" title="Tandem mass spectrometry">Tandem mass spectrometry</a></li> <li><a href="/wiki/Metabolomics" title="Metabolomics">Metabolomics</a></li> <li><a href="/wiki/List_of_mass_spectrometry_software" title="List of mass spectrometry software">List of mass spectrometry software</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SIRIUS_(software)&action=edit&section=25" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}</style><div class="reflist"> <div class="mw-references-wrap mw-references-columns"><ol class="references"> <li id="cite_note-SIRIUSdecomp-1"><span class="mw-cite-backlink">^ <a href="#cite_ref-SIRIUSdecomp_1-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-SIRIUSdecomp_1-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-SIRIUSdecomp_1-2"><sup><i><b>c</b></i></sup></a> <a href="#cite_ref-SIRIUSdecomp_1-3"><sup><i><b>d</b></i></sup></a></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}</style><cite id="CITEREFBöckerLetzelLiptákPervukhin2009" class="citation journal cs1">Böcker, Sebastian; Letzel, Matthias C.; Lipták, Zsuzsanna; Pervukhin, Anton (15 January 2009). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639009">"SIRIUS: decomposing isotope patterns for metabolite identification"</a>. <i>Bioinformatics</i>. <b>25</b> (2): 218–224. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1093%2Fbioinformatics%2Fbtn603">10.1093/bioinformatics/btn603</a>. <a href="/wiki/PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639009">2639009</a></span>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/19015140">19015140</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Bioinformatics&rft.atitle=SIRIUS%3A+decomposing+isotope+patterns+for+metabolite+identification&rft.volume=25&rft.issue=2&rft.pages=218-224&rft.date=2009-01-15&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC2639009%23id-name%3DPMC&rft_id=info%3Apmid%2F19015140&rft_id=info%3Adoi%2F10.1093%2Fbioinformatics%2Fbtn603&rft.aulast=B%C3%B6cker&rft.aufirst=Sebastian&rft.au=Letzel%2C+Matthias+C.&rft.au=Lipt%C3%A1k%2C+Zsuzsanna&rft.au=Pervukhin%2C+Anton&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC2639009&rfr_id=info%3Asid%2Fen.wikipedia.org%3ASIRIUS+%28software%29" class="Z3988"></span></span> </li> <li id="cite_note-fragmentation_trees-2"><span class="mw-cite-backlink">^ <a href="#cite_ref-fragmentation_trees_2-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-fragmentation_trees_2-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFBöckerRasche2008" class="citation journal cs1">Böcker, Sebastian; Rasche, Florian (15 August 2008). 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