Skip to main content

COVID-19 is an emerging, rapidly evolving situation.

What people with cancer should know:

Guidance for cancer researchers:

Get the latest public health information from CDC:

Get the latest research information from NIH:

Grant Details

Grant Number: 7U01CA235493-03 Interpret this number
Primary Investigator: Li, Shuzhao
Organization: Jackson Laboratory
Project Title: Mummichog 3, Aligning Mass Spectrometry Data to Biological Networks
Fiscal Year: 2020


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.


Comprehensive Meta-Analysis of COVID-19 Global Metabolomics Datasets.
Authors: Pang Z. , Zhou G. , Chong J. , Xia J. .
Source: Metabolites, 2021-01-09; 11(1), .
EPub date: 2021-01-09.
PMID: 33435351
Related Citations

METLIN MS2 molecular standards database: a broad chemical and biological resource.
Authors: Xue J. , Guijas C. , Benton H.P. , Warth B. , Siuzdak G. .
Source: Nature methods, 2020 10; 17(10), p. 953-954.
PMID: 32839599
Related Citations

Metabolic adaptation to calorie restriction.
Authors: Guijas C. , Montenegro-Burke J.R. , Cintron-Colon R. , Domingo-Almenara X. , Sanchez-Alavez M. , Aguirre C.A. , Shankar K. , Majumder E.L. , Billings E. , Conti B. , et al. .
Source: Science signaling, 2020-09-08; 13(648), .
EPub date: 2020-09-08.
PMID: 32900879
Related Citations

Addressing the batch effect issue for LC/MS metabolomics data in data preprocessing.
Authors: Liu Q. , Walker D. , Uppal K. , Liu Z. , Ma C. , Tran V. , Li S. , Jones D.P. , Yu T. .
Source: Scientific reports, 2020-08-17; 10(1), p. 13856.
EPub date: 2020-08-17.
PMID: 32807888
Related Citations

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
Related Citations

Enhanced in-Source Fragmentation Annotation Enables Novel Data Independent Acquisition and Autonomous METLIN Molecular Identification.
Authors: Xue J. , Domingo-Almenara X. , Guijas C. , Palermo A. , Rinschen M.M. , Isbell J. , Benton H.P. , Siuzdak G. .
Source: Analytical chemistry, 2020-04-21; 92(8), p. 6051-6059.
EPub date: 2020-04-10.
PMID: 32242660
Related Citations

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 03; 92, p. 57-65.
EPub date: 2019-07-09.
PMID: 31299210
Related Citations

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
Related Citations

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
Related Citations

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
Related Citations

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
Related Citations

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
Related Citations

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
Related Citations

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
Related Citations

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
Related Citations

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
Related Citations

Back to Top