NIH Common Fund Metabolomics Consortium Annual Meeting Agenda 2022

Agenda and Recordings:

PI InstitutionLightning Talk #TitlePresenting AuthorPresenting Author EmailRecording
Tuesday, May 31st
Welcome and Program OverviewJames Anderson and Art, arthur.castle@nih.gov
University of FloridaCoordinating, Engaging and Promoting the ConsortiumRick Yost and Mike, mconlon@ufl.edu
Jackson LaboratoryMummichog 3, aligning mass spectrometry data to biological networksShuzhao LiShuzhao.Li@jax.org
Lightning Talks A  – 12:30-12:45    
University of Georgia/Georgia Tech (CIDC)1Strengths and Current Limitations of Ion Mobility for Unknown Metabolite IdentificationCarter Asefcasef3@gatech.edu
University of Michigan (DTC)2Integrative transcriptome-metabolome analysis of sexual dimorphism in aerobic capacity rat modelGayatri Iyergriyer@umich.edu
Pacific Northwest National Lab/University of Alberta (CIDC)3BioTransformer 3.0—A Web Server for Accurately Predicting Metabolic Transformation ProductsSiyang Tianstian2@ualberta.ca
University of California, DavisIntegrating, MS, MS/MS and retention time modeling in confident annotation of metabolites in the LC-BinBase databaseOliver Fiehnofiehn@ucdavis.edu
Lightning Talks B  – 1:45 – 2:00    
UC Davis (CIDC)4Quantum chemistry and electron ionization mass spectra predictionShunyang Wangsywang@ucdavis.edu
UC San Diego (NMDR)5MetEnpMano Mauryamano@sdsc.edu
Vanderbilt University (DTC)6Elucidating active networks using stable-isotope labeling and untargeted metabolomicsJavier Gomezjavier.d.gomez@vanderbilt.edu
Working Group ReportsQM Modeling and Terminology in MetabolomicsArt Edison and Gary, gjpattij@wustl.edu
Lightning Talks C  – 2:30 to 2:45    
University of Colorado (DTC)7DisCo P-ad: Distance Correlation-Based Adjusted P-value Boosts Multiple-Testing Corrections in Metabolomics AnalysesDebmalya Nandydebmalya.nandy@cuanschutz.edu
University of Michigan (CIDC)8LC-MS Strategies for Additional Metabolite IdentificationBrady Andersonanderbra@umich.edu
Jackson Laboratory/Scripps (DTC)95 minutes • 5 years • 5 METLIN downloadsGary Siuzdaksiuzdak@scripps.edu
University of North Carolina, CharlotteADAP-BIG: A cross-platform and graphical software tool for preprocessing metabolomics big dataXiuxia Duxiuxia.du@uncc.edu
Lightning Talks D  – 3:30 to 3:50    
Pacific Northwest National Lab/University of Alberta (CIDC)10CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound IdentificationFei Wangfw4@ualberta.ca
Washington University (DTC)11
UC San Diego (NMDR)12MetGeneSumana Srinivasansusrinivasan@eng.ucsd.edu
University of Florida (M3C)13Open, Published, RDF Metadata for Datasets, Studies, Publications, and Investigators of the Metabolomics Workbench and Related WorkMike Conlonmconlon@ufl.edu
Working Group ReportsUnknown Lipids and Unknown PolarsCharles Evanschevans@umich.edu
Wednesday June 1st
Washington UniversityDatabase-Assisted MS/MS Deconvolution for Metabolite IdentificationGary Pattigjpattij@wustl.edu
Lightning Talks E  – 1:00 to 1:15    
Jackson Laboratory/McGill University (DTC)14Comprehensive investigation of pathway enrichment methods for LC-MS-based untargeted metabolomics dataYao Luyao.lu5@mail.mcgill.ca
University of Michigan (CIDC)15Disparate LC-MS Alignment of Common Fund Metabolomics Consortium Inter-laboratory Unknown Lipids DatasetsHani Habrahhani@umich.edu
University of Colorado (DTC)16MSCAT v2.0: Updates and new features on the Metabolomics Software DatabaseWladimir LabeikovskyWladimir.Labeikovsky@cuanschutz.edu
Emory UniversityDevelopment of biological criteria to enhance mass spectrometry-based metabolite identificationDean Jonesdpjones@emory.edu
Collaborative Projects ReportsThe National Metabolomics Data Repository and integrated resources on the Metabolomics Workbench and Common Datasets for BenchmarkingShankar Subramaniam and Corey, Corey.Broeckling@colostate.edu
MD AndersonMetaBatch Omic Browser update: a web resource for dynamic visualization, analysis, and correction of batch effects in MWB dataJohn Weinsteinjweinste@mdanderson.org
Lightning Talks F  – 3:30 to 3:45    
Jackson Laboratory (DTC)17Trackable and scalable LC-MS metabolomics data processing using asariAmnah SiddiqaAmnah.Siddiqa@jax.org
University of Georgia (CIDC)18Addressing Batch Effects in Large-Scale MetabolomicsAmanda Shaveramanda.shaver@uga.edu
University of Michigan (DTC)19Bayesian methodology for estimating differential networks with applications to metabolomicsGeorge Michailidisgmichail@ufl.edu
Collaborative Project ReportADAP-KDB: Tracking known and unknown mass spectral features in NMDRXiuxia Duxiuxia.du@uncc.edu
Pacific Northwest National LabExploiting the ‘curse of dimensionality’ for metabolite identificationTom Metzthomas.metz@pnnl.gov
Thursday June 2nd
University of California, San DiegoMetabolomics Tools and Resources for the Research CommunityShankar Subramaniamshankar@sdsc.edu
Lightning Talks G  – 11:30 to 11:45 
Washington University (DTC)20
University of North Carolina Charlotte (DTC)21Approaches to optimize speed and memoryAleksandr Smirnovasmirno1@uncc.edu
Pacific Northwest National Lab (CIDC)22MS2 Drift Time Offset in IMS-QTOF Data ProcessingJessica Badejessica.bade@pnnl.gov
University of MichiganApplications of data-driven network analysis for metabolomics and gene expressionAlla Karnovskyakarnovs@umich.edu
Lightning Talks H  – 12:15 to 12:30    
Vanderbilt University/Danforth Center (DTC)23Insights into plant lipid metabolism using stable isotopes and high-resolution mass spectrometryShrikaar KambhampatiSKambhampati@danforthcenter.org
Jackson Laboratory (DTC)24Simultaneous metabolomics and lipidomics profiling reveals intracellular pathways in trophectoderm differentiation altered by metabolic environmentsMaheshwor ThapaMaheshwor.Thapa@jax.org
Emory University (CIDC)25Xenobiotic biotransformation networking for identification of undocumented xenobiotic exposuresGrant Singergrant.matthew.singer@emory.edu
Vanderbilt UniversityTools for Leveraging High-Resolution MS Detection of Stable Isotopes for Metabolomics ApplicationsJamey Youngj.d.young@vanderbilt.edu
University of MichiganChromatographic strategies to enhance compound identification, and software tools to line up IDs, assess confidence, and keep track of it allCharles Evanschevans@umich.edu
Lightning Talks I  – 2:00 to 2:15    
Pacific Northwest National Lab (CIDC)26An Automated Process for Expanding Experimental CCS Reference LibrariesChristine Changchristine.chang@pnnl.gov
Jackson Laboratory/McGill University (DTC)27COVID Metabolomics Explorer: collaborative exploration of public COVID-19 metabolomics data within MetaboAnalystZhiqiang Pangzhiqiang.pang@mail.mcgill.ca
University of North Carolina Charlotte (DTC)28Towards prediction of unknown lipidsCiara Conwaycconwa10@uncc.edu
University of Colorado, DenverAddressing Sparsity in Metabolomics Data AnalysisKaterina Kechriskaterina.kechris@cuanschutz.edu
Lightning Talks J  – 3:00 to 3:15    
Jackson Laboratory (DTC)29JSON’s Metabolite Services to bridge genome-scale metabolic models and metabolomicsMinghao GongMinghao.Gong@jax.org
UC Davis (CIDC)30Creation of tandem mass spectra (MS/MS) with density functional theory (DFT)Tobias Kindtkind@ucdavis.edu
MD Anderson (DTC)31MetaBatch Omic Browser: a web resource for visualization and analysis of batch effects in MWBJohn Weinsteinjweinste@mdanderson.org
University of GeorgiaIntegrating LC-MS and NMR for Compound ID using Computational Chemistry and a Genetics-focused Study DesignArt Edisonaedison@uga.edu
Closing RemarksRick Yost and Mike, mconlon@ufl.edu