HMDB: the Human Metabolome Database

By David S. Wishart, D. Tzur, Craig Knox, Roman Eisner, Anchi Guo, Nelson Young, D. Cheng, K. Jewell, David Arndt, S. Sawhney and 30 more. Nucleic Acids Res., 2007

3,058 citations recorded by the source corpus.

The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at:

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/4c987ffb492e44acc010cbeb2347b92e257d7b59

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Citations in the corpus

Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum (2008, background): “Metabolomics, which is the rapidly evolving field of measuring all endogenous metabolites in a cell or body fluid [8–16], may contribute to solving this problem.”
DrugBank: a knowledgebase for drugs, drug actions and drug targets (2007, methodology): “…format and spelling checks) and later (once a week), through the use of ‘sanity checker’ (Supplementary Table 1) that checks the consistency of chemical structure ﬁles, chemical formulae and chemical properties using a variety of custom-built prediction and ﬁle-formatting programs (8, 14, 24).”
SMPDB: The Small Molecule Pathway Database (2009, methodology): “…artists and annotators were also required to consult a variety of sources including biochemistry textbooks, the Boerhinger–Manheim wall chart (2), OMIM (17), Wikipedia, KEGG (5), HumanCyc (7), Reactome (8), the Medical Biochemistry Page, UniProt (16), the HMDB (15), DrugBank (14) and PharmGKB (11).”
High-fat diet alters gut microbiota physiology in mice (2013, methodology): “Masses were searched against the KEGG (Kyoto Encyclopedia of Genes and Genomes) (Kanehisa and Goto, 2000), HMDB (Human Metabolome Database) (Wishart et al., 2007) and Lipid Maps (www.lipidmaps.org) databases usingMus musculus as reference organism.”
Reconstruction of Genome-Scale Active Metabolic Networks for 69 Human Cell Types and 16 Cancer Types Using INIT (2012, methodology): “The reactions are linked to metabolites that themselves are linked to their tissue specific information collected from the HMDB [22].”
Rewiring of the Fruit Metabolome in Tomato Breeding. (2018, background): “Metabolomics is defined, by analogy to transcriptomics and proteomics, as the analysis of the metabolic complement of an organism (Wishart et al., 2007).”
Ambiguity of non-systematic chemical identifiers within and between small-molecule databases (2015, methodology): “Databases We selected eight well-known chemical databases covering a wide range of bioactive compounds: Chemical Entities of Biological Interest (ChEBI) [18], ChEMBL [19], ChemSpider [20], DrugBank [21], the Human Metabolome Database (HMDB) [9, 22], the NCGC Pharmaceutical Collection (NPC) [23], Pub”
Gut Microbiota-Derived Tryptophan Metabolites Modulate Inflammatory Response in Hepatocytes and Macrophages (2018, positive): “Each feature was searched against spectral libraries in METLIN (Smith et al., 2005) and HMDB (Wishart et al., 2007) and analyzed using in silico fragmentation tools MetFrag (Wolf et al., 2010) and CFM-ID (Allen et al., 2014).”
RIKEN tandem mass spectral database (ReSpect) for phytochemicals: a plant-specific MS/MS-based data resource and database. (2012, methodology): “MS/MS data have recently been made available via web databases such as METLIN (Smith et al., 2005), BinBase (Fiehn et al., 2005, 2008), HMDB (Wishart et al., 2009, 2007), MMCD (Cui et al., 2008), and MassBank (Horai et al., 2010).”
Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles (2009, methodology): “3.2 Comparison of the obtained metabolites with previous studies Of the metabolite profiles obtained, the annotated metabolites included carnitines (betaine, choline, carnitine, glycerophosphocholine), polyamines (cadaverine and putrescine), a purine (hypoxanthine), amino alcohols (ethanolamine), al”
1001 Ways to run AutoDock Vina for virtual screening (2016, background): “The same result was obtained for similar experiments we conducted with exhaustiveness 40 on HMDB and with exhaustiveness 10 on FDA.”