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National Metabolomics Data Repository
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StudiesAs of 06/22/21 a total of 1756 studies have been processed by the National Metabolomics Data Repository (NMDR). There are 1486 publicly available studies and the remainder (270) will be made available subject to their embargo dates.
Recently released studies on NMDR
ST001406 - Environmental chemical burden in metabolic tissues and systemic biological pathways in adolescent bariatric surgery patients: A pilot untargeted metabolomic approach (part-II); Homo sapiens; Icahn School of Medicine at Mount Sinai
ST001407 - Environmental chemical burden in metabolic tissues and systemic biological pathways in adolescent bariatric surgery patients: A pilot untargeted metabolomic approach; Homo sapiens; Icahn School of Medicine at Mount Sinai
ST001733 - Understanding systemic and local inflammation induced by nasal polyposis: role of the allergic phenotype (part-I); Homo sapiens; CEMBIO
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Summary reports on metabolites in NMDR
Typical metabolite concentration ranges via MetStat in NMDR (April 22, 2021)
View typical concentration ranges for a metabolite depending on species, tissue/organ, analysis method, etc. using MetStat. For example, what are typical concentrations of metabolites detected in human blood samples by MS or NMR? MetStat provides summary information across over 1,400 studies in NMDR. Here is a quick tutorial.
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NMDR studies and Jupyter Notebooks
Analyze Workbench studies via Python-based Jupyter Notebooks. Launch notebooks on Binder or download notebooks from GitHub and run them locally.
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Lipid Notation in RefMet and lipid m/z calculation tools
View table of over 170 revised lipid abbreviations covered by RefMet, including structure examples and m/z calculation tools for a variety of adducts.
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Convert your metabolite name to standardized nomenclature via RefMet
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Exemplary Studies
A list of exemplary studies are listed here which adhere to the submission guidelines of Metabolomics Workbench. Specifically, publically available studies having all or most of the features below were identified as exemplary studies.
- Well-written study summary
- Detailed metadata for collection/treatment/chromatography/MS/NMR, etc.
- Post-processing details
- Presence of control samples
- Raw data availability for samples and controls
- One-to-one mapping of sample names to raw data file name
- Internal standards (with measurements)
- Clear and organized metabolite annotations
These include different analysis (GC-MS, LC-MS, NMR) and species type. We recommend looking at these studies as a model example before submitting to Metabolomics Workbench.
