National Metabolomics Data Repository

As of 03/01/21 a total of 1638 studies have been processed by the the National Metabolomics Data Repository (NMDR). There are 1367 publicly available studies and the remainder (271) will be made available subject to their embargo dates.

Recently released studies on NMDR

ST001218 - Wild type versus TRACK Mice on regular chow and Vitamin A deprived diet; Mus musculus; Weill Cornell Medicine

ST001394 - Metabolomic study of Escherichia coli K-12 MG1655 and mutants; Escherichia coli; IIT Bombay

ST001400 - Identification of distinct metabolic perturbations and associated immunomodulatory events during intra-erythrocytic development stage of pediatric Plasmodium falciparum malaria; Homo sapiens; New York University Abu Dhabi

ST001421 - Metabolomic study of Escherichia coli K-12 MG1655 WT and its transcriptional regulator mutants under anaerobic fermentation conditions; Escherichia coli; IIT Bombay

Highlights

Mobile phone apps for metabolomics (January 4, 2021)

• NMDR metabolite summary app. Search over 1,250 studies in NMDR by anlytical technique, sample source, species and metabolite class. Retrieve a summary table sorted by frequency of detection of metabolite species, linked to structures and individual NMDR study information.
• RefMet search app. Search RefMet by (partial) name and/or neutral mass.
• RefMet name conversion app. Convert a metabolite name to RefMet nomenclature. Display structure. Calculate m/z.
• RefMet MS search app. Search RefMet with m/z value.
• Lipid mass/formula app. Calculate lipid neutral mass and m/z for over 160 lipid species.
• View Screenshot
  
• Reference: RefMet: a reference nomenclature for metabolomics (Nature Methods, 2020)
  

Higlights/News archive

Lipid Notation in RefMet and lipid m/z calculation tools

Convert your metabolite name to standardized nomenclature via RefMet

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.