{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T09:30:33Z","timestamp":1784280633367,"version":"3.55.0"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2016,10,3]],"date-time":"2016-10-03T00:00:00Z","timestamp":1475452800000},"content-version":"vor","delay-in-days":845,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space of possible ways in which the metabolite can fragment, and base the metabolite identification on scoring of these fragmentation trees. Machine learning methods have been used to map mass spectra to molecular fingerprints; predicted fingerprints, in turn, can be used to score candidate molecular structures.<\/jats:p>\n               <jats:p>Results: Here, we combine fragmentation tree computations with kernel-based machine learning to predict molecular fingerprints and identify molecular structures. We introduce a family of kernels capturing the similarity of fragmentation trees, and combine these kernels using recently proposed multiple kernel learning approaches. Experiments on two large reference datasets show that the new methods significantly improve molecular fingerprint prediction accuracy. These improvements result in better metabolite identification, doubling the number of metabolites ranked at the top position of the candidates list.<\/jats:p>\n               <jats:p>Contact: \u00a0huibin.shen@aalto.fi<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu275","type":"journal-article","created":{"date-parts":[[2014,6,16]],"date-time":"2014-06-16T21:55:09Z","timestamp":1402955709000},"page":"i157-i164","source":"Crossref","is-referenced-by-count":109,"title":["Metabolite identification through multiple kernel learning on fragmentation trees"],"prefix":"10.1093","volume":"30","author":[{"given":"Huibin","family":"Shen","sequence":"first","affiliation":[{"name":"1 Department of Information and Computer Science, Aalto University, Espoo, Finland, 2Helsinki Institute for Information Technology, Espoo, Finland and 3Chair for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany"},{"name":"1 Department of Information and Computer Science, Aalto University, Espoo, Finland, 2Helsinki Institute for Information Technology, Espoo, Finland and 3Chair for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"D\u00fchrkop","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Aalto University, Espoo, Finland, 2Helsinki Institute for Information Technology, Espoo, Finland and 3Chair for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"B\u00f6cker","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Aalto University, Espoo, Finland, 2Helsinki Institute for Information Technology, Espoo, Finland and 3Chair for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juho","family":"Rousu","sequence":"additional","affiliation":[{"name":"1 Department of Information and Computer Science, Aalto University, Espoo, Finland, 2Helsinki Institute for Information Technology, Espoo, Finland and 3Chair for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany"},{"name":"1 Department of Information and Computer Science, Aalto University, Espoo, Finland, 2Helsinki Institute for Information Technology, Espoo, Finland and 3Chair for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2014,6,11]]},"reference":[{"key":"2023012711065552100_btu275-B1","article-title":"Competitive fragmentation modeling of ESI-MS\/MS spectra for metabolite identification","author":"Allen","year":"2013"},{"key":"2023012711065552100_btu275-B2","doi-asserted-by":"crossref","first-page":"i49","DOI":"10.1093\/bioinformatics\/btn270","article-title":"Towards de novo identification of metabolites by analyzing tandem mass spectra","volume":"24","author":"B\u00f6cker","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012711065552100_btu275-B3","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1093\/bioinformatics\/btn603","article-title":"Sirius: decomposing isotope patterns for metabolite identification","volume":"25","author":"B\u00f6cker","year":"2009","journal-title":"Bioinformatics"},{"key":"2023012711065552100_btu275-B4","first-page":"625","article-title":"Convolution kernels for natural language","volume-title":"Advances in Neural Information Processing Systems 14","author":"Collins","year":"2001"},{"key":"2023012711065552100_btu275-B5","first-page":"795","article-title":"Algorithms for learning kernels based on centered alignment","volume":"13","author":"Cortes","year":"2012","journal-title":"J. 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