HMDB 4.0: the human metabolome database for 2018

By David S. Wishart, Y. D. Feunang, A. Marcu, Anchi Guo, Kevin Y. H. Liang, R. Vázquez-Fresno, Tanvir Sajed, Daniel Johnson, Carin Li, Naama Karu and 18 more. Nucleic Acids Res., 2017

3,045 citations recorded by the source corpus.

Abstract The Human Metabolome Database or HMDB (www.hmdb.ca) is a web-enabled metabolomic database containing comprehensive information about human metabolites along with their biological roles, physiological concentrations, disease associations, chemical reactions, metabolic pathways, and reference spectra. First described in 2007, the HMDB is now considered the standard metabolomic resource for human metabolic studies. Over the past decade the HMDB has continued to grow and evolve in response to emerging needs for metabolomics researchers and continuing changes in web standards. This year's update, HMDB 4.0, represents the most significant upgrade to the database in its history. For instance, the number of fully annotated metabolites has increased by nearly threefold, the number of experimental spectra has grown by almost fourfold and the number of illustrated metabolic pathways has grown by a factor of almost 60. Significant improvements have also been made to the HMDB’s chemical taxonomy, chemical ontology, spectral viewing, and spectral/text searching tools. A great deal of brand new data has also been added to HMDB 4.0. This includes large quantities of predicted MS/MS and GC–MS reference spectral data as well as predicted (physiologically feasible) metabolite structures to facilitate novel metabolite identification. Additional information on metabolite-SNP interactions and the influence of drugs on metabolite levels (pharmacometabolomics) has also been added. Many other important improvements in the content, the interface, and the performance of the HMDB website have been made and these should greatly enhance its ease of use and its potential applications in nutrition, biochemistry, clinical chemistry, clinical genetics, medicine, and metabolomics science.

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/80777d42513103bede188b2eebbdce7fb6f91390

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Citations in the corpus

HMDB 5.0: the Human Metabolome Database for 2022 (2021, methodology): “Furthermore, improvements in our spectral visualization program (JSV), also allowed us to undertake improvements in the graphical display of the spectral match output.”
BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification (2019, methodology): “While the command-line executable does not benefit from the database of computed metabolites, it also does provide some advantages, namely: [1] it allows users to submit large sets of compounds; [2] it does not rely on an Internet connection, and; [3] queries are executed immediately and not put in ”
Polyphenols: A concise overview on the chemistry, occurrence, and human health (2019, background): “ca/), a web metabolomic database on human metabolites (Wishart et al., 2018), and PhytoHub (Phytohub website http://phytohub.”
The Gut-Brain Axis: How Microbiota and Host Inflammasome Influence Brain Physiology and Pathology (2020, background): “SCFAs are, in fact, detectable in low amounts in the human brain under physiological conditions (102).”
Review on natural products databases: where to find data in 2020 (2020, background): “From the same institution, the Yeast Metabolome Database (YMDB) [59], was created with the same pattern as the HMDB, and therefore also contains very extensive metadata for baker’s yeast metabolites, enzymes that are involved in the molecular metabolism and reference spectra.”
One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome (2020, background): “This database contains diverse lipids, phospholipids, carbohydrates, glycosides, amino acid derivatives and more [38].”