<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Chen Z</submitter><funding>NSF</funding><funding>National Center for Research Resources</funding><funding>NCRR NIH HHS</funding><funding>National Institute of General Medical Sciences</funding><funding>NIH HHS</funding><funding>NIGMS NIH HHS</funding><pagination>436-445</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9149727</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>33(3)</volume><pubmed_abstract>Glycan structure identification is essential to understanding the roles of glycans in various biological processes. Previously, we developed GlycoDeNovo, a &lt;i>de novo&lt;/i> algorithm for reconstructing glycan topologies from tandem mass spectra (MS/MS). In this work, we introduce GlycoDeNovo2 that contains two major improvements to GlycoDeNovo. First, we use the precursor mass measured for a peak that likely corresponds to a glycan to determine its potential compositions, which are used to constrain the search space, enable parallel computation, and hence speed up topology reconstruction. Second, we developed a procedure to calculate the empirical &lt;i>p&lt;/i>-value of a reconstructed topology candidate. Experimental results are provided to demonstrate the effectiveness of GlycoDeNovo2.</pubmed_abstract><journal>Journal of the American Society for Mass Spectrometry</journal><pubmed_title>GlycoDeNovo2: An Improved MS/MS-Based &lt;i>De Novo&lt;/i> Glycan Topology Reconstruction Algorithm.</pubmed_title><pmcid>PMC9149727</pmcid><funding_grant_id>NIH R24 GM134210</funding_grant_id><funding_grant_id>R24 GM134210</funding_grant_id><funding_grant_id>S10 RR025082</funding_grant_id><funding_grant_id>S10 OD021728</funding_grant_id><funding_grant_id>NIH R01 GM132675</funding_grant_id><funding_grant_id>R01 GM132675</funding_grant_id><funding_grant_id>NIH S10 RR025082</funding_grant_id><funding_grant_id>NSF OAC 1920147</funding_grant_id><pubmed_authors>Lin C</pubmed_authors><pubmed_authors>Chen Z</pubmed_authors><pubmed_authors>Costello CE</pubmed_authors><pubmed_authors>Wei J</pubmed_authors><pubmed_authors>Hong P</pubmed_authors><pubmed_authors>Tang Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>GlycoDeNovo2: An Improved MS/MS-Based &lt;i>De Novo&lt;/i> Glycan Topology Reconstruction Algorithm.</name><description>Glycan structure identification is essential to understanding the roles of glycans in various biological processes. Previously, we developed GlycoDeNovo, a &lt;i>de novo&lt;/i> algorithm for reconstructing glycan topologies from tandem mass spectra (MS/MS). In this work, we introduce GlycoDeNovo2 that contains two major improvements to GlycoDeNovo. First, we use the precursor mass measured for a peak that likely corresponds to a glycan to determine its potential compositions, which are used to constrain the search space, enable parallel computation, and hence speed up topology reconstruction. Second, we developed a procedure to calculate the empirical &lt;i>p&lt;/i>-value of a reconstructed topology candidate. Experimental results are provided to demonstrate the effectiveness of GlycoDeNovo2.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Mar</publication><modification>2025-04-05T14:19:55.16Z</modification><creation>2025-04-05T14:19:55.16Z</creation></dates><accession>S-EPMC9149727</accession><cross_references><pubmed>35157458</pubmed><doi>10.1021/jasms.1c00288</doi></cross_references></HashMap>