<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>412(6)</volume><submitter>Chao A</submitter><pubmed_abstract>High-resolution mass spectrometry (HRMS) enables rapid chemical annotation via accurate mass measurements and matching of experimentally derived spectra with reference spectra. Reference libraries are generated from chemical standards and are therefore limited in size relative to known chemical space. To address this limitation, in silico spectra (i.e., MS/MS or MS2 spectra), predicted via Competitive Fragmentation Modeling-ID (CFM-ID) algorithms, were generated for compounds within the U.S. Environmental Protection Agency's (EPA) Distributed Structure-Searchable Toxicity (DSSTox) database (totaling, at the time of analysis, ~ 765,000 substances). Experimental spectra from EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) mixtures (n = 10) were then used to evaluate the performance </pubmed_abstract><journal>Analytical and bioanalytical chemistry</journal><pagination>1303-1315</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7021669</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>In silico MS/MS spectra for identifying unknowns: a critical examination using CFM-ID algorithms and ENTACT mixture samples.</pubmed_title><pmcid>PMC7021669</pmcid><pubmed_authors>Sobus JR</pubmed_authors><pubmed_authors>Al-Ghoul H</pubmed_authors><pubmed_authors>Grossman JN</pubmed_authors><pubmed_authors>Williams AJ</pubmed_authors><pubmed_authors>Singh RR</pubmed_authors><pubmed_authors>Balabin I</pubmed_authors><pubmed_authors>Ulrich EM</pubmed_authors><pubmed_authors>Transue T</pubmed_authors><pubmed_authors>McEachran AD</pubmed_authors><pubmed_authors>Cathey T</pubmed_authors><pubmed_authors>Chao A</pubmed_authors></additional><is_claimable>false</is_claimable><name>In silico MS/MS spectra for identifying unknowns: a critical examination using CFM-ID algorithms and ENTACT mixture samples.</name><description>High-resolution mass spectrometry (HRMS) enables rapid chemical annotation via accurate mass measurements and matching of experimentally derived spectra with reference spectra. Reference libraries are generated from chemical standards and are therefore limited in size relative to known chemical space. To address this limitation, in silico spectra (i.e., MS/MS or MS2 spectra), predicted via Competitive Fragmentation Modeling-ID (CFM-ID) algorithms, were generated for compounds within the U.S. Environmental Protection Agency's (EPA) Distributed Structure-Searchable Toxicity (DSSTox) database (totaling, at the time of analysis, ~ 765,000 substances). Experimental spectra from EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) mixtures (n = 10) were then used to evaluate the performance </description><dates><release>2020-01-01T00:00:00Z</release><publication>2020 Feb</publication><modification>2025-05-18T12:58:42.195Z</modification><creation>2025-05-18T12:58:42.195Z</creation></dates><accession>S-EPMC7021669</accession><cross_references><pubmed>31965249</pubmed><doi>10.1007/s00216-019-02351-7</doi></cross_references></HashMap>