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Grant Details

Grant Number: 5U01CA235493-02 Interpret this number
Primary Investigator: Li, Shuzhao
Organization: Emory University
Project Title: Mummichog 3, Aligning Mass Spectrometry Data to Biological Networks
Fiscal Year: 2019
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Abstract

Abstract The mummichog software was initially published in 2013, as a computational approach to match patterns in metabolomics data to known biochemical networks, without the requirement of upfront metabolite identification. This approach enables rapid generation of biological hypotheses from untargeted data, and has gained considerable popularity, which also creates urgent needs to upgrade the software itself. This proposal aims to add a rich user interface, and better support of LC-MS, LC- MS/MS, IMS/MS and GC-MS. Furthermore, this work will make a conceptual leap to establish a framework of network alignment as a vehicle to interpret metabolomics data by integrating multiple layers of information. The new development will be integrated into XCMS Online and MetaboAnalyst, and will be made freely available as modular software tools.

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Publications

MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics.
Authors: Pang Z. , Chong J. , Li S. , Xia J. .
Source: Metabolites, 2020-05-07; 10(5), .
EPub date: 2020-05-07.
PMID: 32392884
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Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's.
Authors: Li S. , Cirillo P. , Hu X. , Tran V. , Krigbaum N. , Yu S. , Jones D.P. , Cohn B. .
Source: Reproductive toxicology (Elmsford, N.Y.), 2020 Mar; 92, p. 57-65.
EPub date: 2019-07-09.
PMID: 31299210
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Network-Based Approaches for Multi-omics Integration.
Authors: Zhou G. , Li S. , Xia J. .
Source: Methods in molecular biology (Clifton, N.J.), 2020; 2104, p. 469-487.
PMID: 31953831
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Pathway Analysis for Targeted and Untargeted Metabolomics.
Authors: Karnovsky A. , Li S. .
Source: Methods in molecular biology (Clifton, N.J.), 2020; 2104, p. 387-400.
PMID: 31953827
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Using MetaboAnalyst 4.0 for Metabolomics Data Analysis, Interpretation, and Integration with Other Omics Data.
Authors: Chong J. , Xia J. .
Source: Methods in molecular biology (Clifton, N.J.), 2020; 2104, p. 337-360.
PMID: 31953825
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The Essential Toolbox of Data Science: Python, R, Git, and Docker.
Authors: Pittard W.S. , Li S. .
Source: Methods in molecular biology (Clifton, N.J.), 2020; 2104, p. 265-311.
PMID: 31953823
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A Bioinformatics Primer to Data Science, with Examples for Metabolomics.
Authors: Pittard W.S. , Villaveces C.K. , Li S. .
Source: Methods in molecular biology (Clifton, N.J.), 2020; 2104, p. 245-263.
PMID: 31953822
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METLIN: A Tandem Mass Spectral Library of Standards.
Authors: Montenegro-Burke J.R. , Guijas C. , Siuzdak G. .
Source: Methods in molecular biology (Clifton, N.J.), 2020; 2104, p. 149-163.
PMID: 31953817
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Metabolomics Data Processing Using XCMS.
Authors: Domingo-Almenara X. , Siuzdak G. .
Source: Methods in molecular biology (Clifton, N.J.), 2020; 2104, p. 11-24.
PMID: 31953810
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Metabolic rewiring of the hypertensive kidney.
Authors: Rinschen M.M. , Palygin O. , Guijas C. , Palermo A. , Palacio-Escat N. , Domingo-Almenara X. , Montenegro-Burke R. , Saez-Rodriguez J. , Staruschenko A. , Siuzdak G. .
Source: Science signaling, 2019-12-10; 12(611), .
EPub date: 2019-12-10.
PMID: 31822592
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Identification of bioactive metabolites using activity metabolomics.
Authors: Rinschen M.M. , Ivanisevic J. , Giera M. , Siuzdak G. .
Source: Nature reviews. Molecular cell biology, 2019 06; 20(6), p. 353-367.
PMID: 30814649
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