{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T17:16:30Z","timestamp":1788455790352,"version":"build-2803163510"},"reference-count":51,"publisher":"American Chemical Society (ACS)","issue":"9","license":[{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/501100012190","name":"Ministry of Science and Higher Education of the Russian Federation","doi-asserted-by":"publisher","award":["124041900012-4"],"award-info":[{"award-number":["124041900012-4"]}],"id":[{"id":"10.13039\/501100012190","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Despite the increasing use of gas chromatography coupled with electron ionization high-resolution mass spectrometry (GC-EI-HRMS), only a limited amount of GC-EI-HRMS reference data is currently available. Such data are beneficial not only for use with a GC-EI-HRMS instrument but also for computational purposes\u2500for example, for training machine learning models that predict fragmentation under electron ionization conditions. Such models are currently trained and tested on integer m\/z data, although they predict the exact elemental composition of ions. High-quality GC-EI-HRMS data will be able to boost the development of such models even if the end user does not have such an instrument. We present HREI-MSDB: a GC-EI-HRMS mass spectral library with an m\/z range of 40\u2013500, and a resolution (full width at half-maximum) of 30,000. The error in m\/z determination for almost all peaks (except for special cases such as overlapping of intense peaks) does not exceed 0.6 mDa; typical values are 0.1\u20130.4 mDa or 0.5\u20131.5 ppm. The data set includes 329 mass spectra of molecules of various classes (nitrogen-containing heterocycles, aromatic and polyaromatic compounds, alcohols, phenols, and essential oil components). All mass spectra are manually verified, free of intense impurity peaks, and are of high quality. In the future, mass spectra may be posted on MassBank. The data is available online: https:\/\/doi.org\/10.6084\/m9.figshare.29713460<\/jats:p>","DOI":"10.1021\/jasms.6c00114","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T13:09:31Z","timestamp":1785848971000},"page":"2072-2084","source":"Crossref","is-referenced-by-count":0,"title":["HREI-MSDB: Data Science-Ready\nDatabase of High-Resolution\nElectron Ionization Mass Spectra"],"prefix":"10.1021","volume":"37","author":[{"given":"Anastasia Yu.","family":"Sholokhova","sequence":"first","affiliation":[{"name":"Frumkin Institute of Physical Chemistry and Electrochemistry Russian Academy of Sciences , 31-4, Leninsky prospect , ,","place":["Moscow, Russia, 119071"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timur M.","family":"Baygildiev","sequence":"additional","affiliation":[{"name":"Frumkin Institute of Physical Chemistry and Electrochemistry Russian Academy of Sciences , 31-4, Leninsky prospect , ,","place":["Moscow, Russia, 119071"]},{"name":"\u201cMIREA\u2500Russian Technological University\u201d , , ,","place":["Moscow, Russia, 119454"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ekaterina S.","family":"Chichkanova","sequence":"additional","affiliation":[{"name":"Frumkin Institute of Physical Chemistry and Electrochemistry Russian Academy of Sciences , 31-4, Leninsky prospect , ,","place":["Moscow, Russia, 119071"]},{"name":"Lomonosov Moscow State University , , ,","place":["Moscow, Russia, 119991"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Svetlana A.","family":"Borovikova","sequence":"additional","affiliation":[{"name":"Frumkin Institute of Physical Chemistry and Electrochemistry Russian Academy of Sciences , 31-4, Leninsky prospect , ,","place":["Moscow, Russia, 119071"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuriy A.","family":"Ikhalaynen","sequence":"additional","affiliation":[{"name":"Lomonosov Moscow State University , , ,","place":["Moscow, Russia, 119991"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igor A.","family":"Rodin","sequence":"additional","affiliation":[{"name":"\u201cMIREA\u2500Russian Technological University\u201d , , ,","place":["Moscow, Russia, 119454"]},{"name":"Lomonosov Moscow State University , , ,","place":["Moscow, Russia, 119991"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0978-7666","authenticated-orcid":true,"given":"Dmitriy D.","family":"Matyushin","sequence":"additional","affiliation":[{"name":"Frumkin Institute of Physical Chemistry and Electrochemistry Russian Academy of Sciences , 31-4, Leninsky prospect , ,","place":["Moscow, Russia, 119071"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,7,27]]},"reference":[{"key":"2026090311505972800_cit1","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.trac.2015.09.005","article-title":"Mass Spectral Databases for LC\/MS- and GC\/MS-Based Metabolomics:\nState of the Field and Future Prospects","volume":"78","author":"Vinaixa","year":"2016","journal-title":"TrAC,\nTrends Anal. Chem."},{"key":"2026090311505972800_cit2","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1007\/978-3-642-65177-9_12","article-title":"Gas Chromatography-Mass\nSpectrometry","volume-title":"Concepts in Biochemical Pharmacology","author":"Guarino","year":"1971"},{"key":"2026090311505972800_cit3","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1016\/j.trac.2016.04.024","article-title":"Mass Spectral\nLibraries: A Statistical Review of the\nVisible Use","volume":"80","author":"Milman","year":"2016","journal-title":"TrAC, Trends Anal. Chem."},{"key":"2026090311505972800_cit4","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.scitotenv.2019.06.192","article-title":"Assessment of Gas Chromatography\nTime-of-Flight Mass Spectrometry for the Screening of Semi-Volatile\nCompounds in Indoor Dust","volume":"688","author":"Castro","year":"2019","journal-title":"Sci. Total Environ."},{"issue":"21","key":"2026090311505972800_cit5","doi-asserted-by":"publisher","first-page":"6327","DOI":"10.1007\/s00216-021-03810-w","article-title":"Development and Application of an In-House Library and Workflow for\nGas Chromatography\u2013Electron Ionization\u2013Accurate-Mass\/High-Resolution\nMass Spectrometry Screening of Environmental Samples","volume":"414","author":"Castro","year":"2022","journal-title":"Anal. Bioanal. Chem."},{"issue":"22","key":"2026090311505972800_cit6","doi-asserted-by":"publisher","first-page":"6946","DOI":"10.1039\/c3an01237a","article-title":"The Benefits of\nHigh Resolution Mass Spectrometry in Environmental Analysis","volume":"138","author":"Lebedev","year":"2013","journal-title":"Analyst"},{"issue":"9","key":"2026090311505972800_cit7","doi-asserted-by":"publisher","first-page":"3429","DOI":"10.1021\/ac802689c","article-title":"MetaboliteDetector: Comprehensive Analysis Tool for\nTargeted and Nontargeted GC\/MS Based Metabolome Analysis","volume":"81","author":"Hiller","year":"2009","journal-title":"Anal. Chem."},{"issue":"20","key":"2026090311505972800_cit8","doi-asserted-by":"publisher","first-page":"10036","DOI":"10.1021\/ac5014767","article-title":"Development\nof a GC\/Quadrupole-Orbitrap\nMass Spectrometer, Part I: Design and Characterization","volume":"86","author":"Peterson","year":"2014","journal-title":"Anal. 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Mol. Sci."},{"issue":"3","key":"2026090311505972800_cit49","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1021\/acs.jcim.3c01758","article-title":"AIRI: Predicting\nRetention Indices and Their Uncertainties Using Artificial Intelligence","volume":"64","author":"Geer","year":"2024","journal-title":"J. Chem. Inf. Model."},{"issue":"6","key":"2026090311505972800_cit50","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1038\/nmeth.3393","article-title":"MS-DIAL: Data-Independent MS\/MS Deconvolution\nfor Comprehensive Metabolome Analysis","volume":"12","author":"Tsugawa","year":"2015","journal-title":"Nat.\nMethods"},{"issue":"14","key":"2026090311505972800_cit51","doi-asserted-by":"publisher","first-page":"2295","DOI":"10.1134\/S1061934826700061","article-title":"An Evaluation\nof the Identifying Reliability of Nitrogen-Containing Compounds That\nAre Absent from Mass Spectral Databases Using a Combination of Gas\nChromatography\u2013Mass Spectrometry and Deep Learning","volume":"80","author":"Matyushin","year":"2025","journal-title":"J. Anal. Chem."}],"container-title":["Journal of the American\nSociety for Mass Spectrometry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/jasms.6c00114","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/jamsef\/article-pdf\/37\/9\/2072\/66286195\/jasms.6c00114.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/jamsef\/article-pdf\/37\/9\/2072\/66286195\/jasms.6c00114.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T16:25:30Z","timestamp":1788452730000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/jamsef\/article\/37\/9\/2072\/5234315\/HREI-MSDB-Data-Science-Ready-Database-of-High"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,27]]},"references-count":51,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,7,27]]},"published-print":{"date-parts":[[2026,9,2]]}},"URL":"https:\/\/doi.org\/10.1021\/jasms.6c00114","relation":{"has-preprint":[{"id-type":"doi","id":"10.26434\/chemrxiv-2025-30xwb","asserted-by":"object"}]},"ISSN":["1044-0305","1879-1123"],"issn-type":[{"value":"1044-0305","type":"print"},{"value":"1879-1123","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,27]]}}}