NIH Common Fund Metabolomics Consortium Annual Meeting Agenda 2022

Agenda and Recordings:

PI Institution Lightning Talk # Title Presenting Author Presenting Author Email Recording
Tuesday, May 31st
Welcome and Program Overview James Anderson and Art Castle andersonjm@od.nih.gov, arthur.castle@nih.gov https://youtu.be/toHzdKwBpis
University of Florida Coordinating, Engaging and Promoting the Consortium Rick Yost and Mike Conlon ryost@ufl.edu, mconlon@ufl.edu https://youtu.be/mxRHHFIGGh4
Jackson Laboratory Mummichog 3, aligning mass spectrometry data to biological networks Shuzhao Li Shuzhao.Li@jax.org https://youtu.be/H4l1pwAIt-Q
Lightning Talks A  – 12:30-12:45        
University of Georgia/Georgia Tech (CIDC) 1 Strengths and Current Limitations of Ion Mobility for Unknown Metabolite Identification Carter Asef casef3@gatech.edu https://youtu.be/WKz23gANfHk
University of Michigan (DTC) 2 Integrative transcriptome-metabolome analysis of sexual dimorphism in aerobic capacity rat model Gayatri Iyer griyer@umich.edu https://youtu.be/G2ORK1vEglk
Pacific Northwest National Lab/University of Alberta (CIDC) 3 BioTransformer 3.0—A Web Server for Accurately Predicting Metabolic Transformation Products Siyang Tian stian2@ualberta.ca https://youtu.be/2dugPG1yi3Y
University of California, Davis Integrating MassBank.us, MS, MS/MS and retention time modeling in confident annotation of metabolites in the LC-BinBase database Oliver Fiehn ofiehn@ucdavis.edu https://youtu.be/dz7wCeW4U7k
Lightning Talks B  – 1:45 – 2:00        
UC Davis (CIDC) 4 Quantum chemistry and electron ionization mass spectra prediction Shunyang Wang sywang@ucdavis.edu https://youtu.be/TFamAdhCY7w
UC San Diego (NMDR) 5 MetEnp Mano Maurya mano@sdsc.edu https://youtu.be/lkKNstiesE4
Vanderbilt University (DTC) 6 Elucidating active networks using stable-isotope labeling and untargeted metabolomics Javier Gomez javier.d.gomez@vanderbilt.edu https://youtu.be/WR3rQ60bQHM
Working Group Reports QM Modeling and Terminology in Metabolomics Art Edison and Gary Patti aedison@uga.edu, gjpattij@wustl.edu https://youtu.be/5T7bOHalApw
Lightning Talks C  – 2:30 to 2:45        
University of Colorado (DTC) 7 DisCo P-ad: Distance Correlation-Based Adjusted P-value Boosts Multiple-Testing Corrections in Metabolomics Analyses Debmalya Nandy debmalya.nandy@cuanschutz.edu https://youtu.be/u2nRPzZP59E
University of Michigan (CIDC) 8 LC-MS Strategies for Additional Metabolite Identification Brady Anderson anderbra@umich.edu https://youtu.be/BvarseXc63I
Jackson Laboratory/Scripps (DTC) 9 5 minutes • 5 years • 5 METLIN downloads Gary Siuzdak siuzdak@scripps.edu https://youtu.be/lAzvNBKFmDE
University of North Carolina, Charlotte ADAP-BIG: A cross-platform and graphical software tool for preprocessing metabolomics big data Xiuxia Du xiuxia.du@uncc.edu https://youtu.be/Qqt06aaoOnw
Lightning Talks D  – 3:30 to 3:50        
Pacific Northwest National Lab/University of Alberta (CIDC) 10 CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification Fei Wang fw4@ualberta.ca https://youtu.be/iMXb8OovF8I
Washington University (DTC) 11       https://youtu.be/NglLtkwKXK0
UC San Diego (NMDR) 12 MetGene Sumana Srinivasan susrinivasan@eng.ucsd.edu https://youtu.be/0gWji05a7RI
University of Florida (M3C) 13 Open, Published, RDF Metadata for Datasets, Studies, Publications, and Investigators of the Metabolomics Workbench and Related Work Mike Conlon mconlon@ufl.edu https://youtu.be/0B96nDuuTbc
Working Group Reports Unknown Lipids and Unknown Polars Charles Evans chevans@umich.edu https://youtu.be/Ql7m2Z_O_kc
Wednesday June 1st
Washington University Database-Assisted MS/MS Deconvolution for Metabolite Identification Gary Patti gjpattij@wustl.edu https://youtu.be/Cf_bdTNvQfE
Lightning Talks E  – 1:00 to 1:15        
Jackson Laboratory/McGill University (DTC) 14 Comprehensive investigation of pathway enrichment methods for LC-MS-based untargeted metabolomics data Yao Lu yao.lu5@mail.mcgill.ca https://youtu.be/j2NX2EJST3w
University of Michigan (CIDC) 15 Disparate LC-MS Alignment of Common Fund Metabolomics Consortium Inter-laboratory Unknown Lipids Datasets Hani Habra hhani@umich.edu https://youtu.be/fz6HRLSzz4c
University of Colorado (DTC) 16 MSCAT v2.0: Updates and new features on the Metabolomics Software Database Wladimir Labeikovsky Wladimir.Labeikovsky@cuanschutz.edu https://youtu.be/hpwEtFa5ql0
Emory University Development of biological criteria to enhance mass spectrometry-based metabolite identification Dean Jones dpjones@emory.edu https://youtu.be/nxjZT6E7sDg
Collaborative Projects Reports The National Metabolomics Data Repository and integrated resources on the Metabolomics Workbench and Common Datasets for Benchmarking Shankar Subramaniam and Corey Broeckling shankar@sdsc.edu, Corey.Broeckling@colostate.edu https://youtu.be/z4ZaA2Ckptc
MD Anderson MetaBatch Omic Browser update: a web resource for dynamic visualization, analysis, and correction of batch effects in MWB data John Weinstein jweinste@mdanderson.org https://youtu.be/mmFhe1wUV-8
Lightning Talks F  – 3:30 to 3:45        
Jackson Laboratory (DTC) 17 Trackable and scalable LC-MS metabolomics data processing using asari Amnah Siddiqa Amnah.Siddiqa@jax.org https://youtu.be/50eRFsHiGBg
University of Georgia (CIDC) 18 Addressing Batch Effects in Large-Scale Metabolomics Amanda Shaver amanda.shaver@uga.edu https://youtu.be/P4j-1m-i0wo
University of Michigan (DTC) 19 Bayesian methodology for estimating differential networks with applications to metabolomics George Michailidis gmichail@ufl.edu https://youtu.be/x89OLdBOJCI
Collaborative Project Report ADAP-KDB: Tracking known and unknown mass spectral features in NMDR Xiuxia Du xiuxia.du@uncc.edu https://youtu.be/3PvPhiTe2cc
Pacific Northwest National Lab Exploiting the ‘curse of dimensionality’ for metabolite identification Tom Metz thomas.metz@pnnl.gov https://youtu.be/NNkl-kiJJ_E
Thursday June 2nd
University of California, San Diego Metabolomics Tools and Resources for the Research Community Shankar Subramaniam shankar@sdsc.edu https://youtu.be/rMxnHIcQQw8
Lightning Talks G  – 11:30 to 11:45  
Washington University (DTC) 20       https://youtu.be/dq7-ZrRYT70
University of North Carolina Charlotte (DTC) 21 Approaches to optimize speed and memory Aleksandr Smirnov asmirno1@uncc.edu https://youtu.be/9eWbB5Pm1Oo
Pacific Northwest National Lab (CIDC) 22 MS2 Drift Time Offset in IMS-QTOF Data Processing Jessica Bade jessica.bade@pnnl.gov https://youtu.be/nHTofW84yOk
University of Michigan Applications of data-driven network analysis for metabolomics and gene expression Alla Karnovsky akarnovs@umich.edu https://youtu.be/6FqM6rL0SJI
Lightning Talks H  – 12:15 to 12:30        
Vanderbilt University/Danforth Center (DTC) 23 Insights into plant lipid metabolism using stable isotopes and high-resolution mass spectrometry Shrikaar Kambhampati SKambhampati@danforthcenter.org https://youtu.be/ScOz85kC_68
Jackson Laboratory (DTC) 24 Simultaneous metabolomics and lipidomics profiling reveals intracellular pathways in trophectoderm differentiation altered by metabolic environments Maheshwor Thapa Maheshwor.Thapa@jax.org https://youtu.be/V6mX6RKUHNY
Emory University (CIDC) 25 Xenobiotic biotransformation networking for identification of undocumented xenobiotic exposures Grant Singer grant.matthew.singer@emory.edu https://youtu.be/WNFcKFluZ-c
Vanderbilt University Tools for Leveraging High-Resolution MS Detection of Stable Isotopes for Metabolomics Applications Jamey Young j.d.young@vanderbilt.edu https://youtu.be/OmiBwWHW8Yw
University of Michigan Chromatographic strategies to enhance compound identification, and software tools to line up IDs, assess confidence, and keep track of it all Charles Evans chevans@umich.edu https://youtu.be/x7S1a5BAUZc
Lightning Talks I  – 2:00 to 2:15        
Pacific Northwest National Lab (CIDC) 26 An Automated Process for Expanding Experimental CCS Reference Libraries Christine Chang christine.chang@pnnl.gov https://youtu.be/PLna1y8W100
Jackson Laboratory/McGill University (DTC) 27 COVID Metabolomics Explorer: collaborative exploration of public COVID-19 metabolomics data within MetaboAnalyst Zhiqiang Pang zhiqiang.pang@mail.mcgill.ca https://youtu.be/Z7ntKTxikp4
University of North Carolina Charlotte (DTC) 28 Towards prediction of unknown lipids Ciara Conway cconwa10@uncc.edu https://youtu.be/-ENuRTiP4JY
University of Colorado, Denver Addressing Sparsity in Metabolomics Data Analysis Katerina Kechris katerina.kechris@cuanschutz.edu https://youtu.be/LWCpaenqYHI
Lightning Talks J  – 3:00 to 3:15        
Jackson Laboratory (DTC) 29 JSON’s Metabolite Services to bridge genome-scale metabolic models and metabolomics Minghao Gong Minghao.Gong@jax.org https://youtu.be/XCSPII5-Djk
UC Davis (CIDC) 30 Creation of tandem mass spectra (MS/MS) with density functional theory (DFT) Tobias Kind tkind@ucdavis.edu https://youtu.be/9I_oecU5N5s
MD Anderson (DTC) 31 MetaBatch Omic Browser: a web resource for visualization and analysis of batch effects in MWB John Weinstein jweinste@mdanderson.org https://youtu.be/4WWZz4y_7TU
University of Georgia Integrating LC-MS and NMR for Compound ID using Computational Chemistry and a Genetics-focused Study Design Art Edison aedison@uga.edu https://youtu.be/z2d3hDZ2ouA
Closing Remarks Rick Yost and Mike Conlon ryost@ufl.edu, mconlon@ufl.edu https://youtu.be/80im3h7VUos