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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Dührkop, Kai Fleischauer, Markus Ludwig, Marcus Aksenov, Alexander A. Melnik, Alexey V. Meusel, Marvin Dorrestein, Pieter C. Rousu, Juho Böcker, Sebastian 2019-05-06T09:13:44Z 2019-05-06T09:13:44Z 2019-04-01
dc.identifier.citation Dührkop , K , Fleischauer , M , Ludwig , M , Aksenov , A A , Melnik , A V , Meusel , M , Dorrestein , P C , Rousu , J & Böcker , S 2019 , ' SIRIUS 4 : a rapid tool for turning tandem mass spectra into metabolite structure information ' Nature Methods , vol. 16 , no. 4 , pp. 299-302 . en
dc.identifier.issn 1548-7091
dc.identifier.other PURE UUID: 6d8bc33b-5968-4824-8542-2183b9ff886d
dc.identifier.other PURE ITEMURL:
dc.identifier.other PURE LINK:
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dc.description.abstract Mass spectrometry is a predominant experimental technique in metabolomics and related fields, but metabolite structural elucidation remains highly challenging. We report SIRIUS 4 (, 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. en
dc.format.extent 4
dc.format.extent 299-302
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Nature Publishing Group
dc.relation.ispartofseries Nature Methods en
dc.relation.ispartofseries Volume 16, issue 4 en
dc.rights openAccess en
dc.subject.other Biotechnology en
dc.subject.other Biochemistry en
dc.subject.other Molecular Biology en
dc.subject.other Cell Biology en
dc.subject.other 113 Computer and information sciences en
dc.title SIRIUS 4 en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Friedrich Schiller University Jena
dc.contributor.department UC-San-Diego
dc.contributor.department Helsinki Institute for Information Technology HIIT
dc.contributor.department Department of Computer Science en
dc.subject.keyword Biotechnology
dc.subject.keyword Biochemistry
dc.subject.keyword Molecular Biology
dc.subject.keyword Cell Biology
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201905062808
dc.identifier.doi 10.1038/s41592-019-0344-8 info:eu-repo/date/embargoEnd/2019-10-01

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