HMDB 5.0: the Human Metabolome Database for 2022

David S. Wishart(University of Alberta), AnChi Guo(University of Alberta), Eponine Oler(University of Alberta), Fei Wang(University of Alberta), Afia Anjum(University of Alberta), Harrison Peters(University of Alberta), Raynard Dizon(University of Alberta), Zinat Sayeeda(University of Alberta), Siyang Tian(University of Alberta), Brian L. Lee(University of Alberta), Mark Berjanskii(University of Alberta), Robert Mah(University of Alberta), Mai Yamamoto(University of Alberta), Juan Jovel(University of Alberta), Claudia Torres-Calzada(University of Alberta), Mickel Hiebert-Giesbrecht(University of Alberta), Vicki W Lui(University of Alberta), Dorna Varshavi(University of Alberta), Dorsa Varshavi(University of Alberta), Dana G. Allen(University of Alberta), David Arndt(University of Alberta), Nitya Khetarpal(University of Alberta), Aadhavya Sivakumaran(University of Alberta), Karxena Harford(University of Alberta), Selena Sanford(University of Alberta), Kristen S. Yee(University of Alberta), Xuan Cao(University of Alberta), Zachary Budinski(University of Alberta), Jaanus Liigand(University of Alberta), Lun Zhang(University of Alberta), Jiamin Zheng(University of Alberta), Rupasri Mandal(University of Alberta), Naama Karu(Leiden University), Maija Dambrova(Latvijas Organiskās Sintēzes Institūts), Helgi B. Schiöth(Uppsala University), Russell Greiner(University of Alberta), Vasuk Gautam(University of Alberta)
Nucleic Acids Research
October 21, 2021
10.1093/nar/gkab1062
Cited by 2,387Open Access
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Abstract

The Human Metabolome Database or HMDB (https://hmdb.ca) has been providing comprehensive reference information about human metabolites and their associated biological, physiological and chemical properties since 2007. Over the past 15 years, the HMDB has grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in internet and computing technology. This year's update, HMDB 5.0, brings a number of important improvements and upgrades to the database. These should make the HMDB more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the number of metabolite entries (from 114 100 to 217 920 compounds); (ii) enhancements to the quality and depth of metabolite descriptions; (iii) the addition of new structure, spectral and pathway visualization tools; (iv) the inclusion of many new and much more accurately predicted spectral data sets, including predicted NMR spectra, more accurately predicted MS spectra, predicted retention indices and predicted collision cross section data and (v) enhancements to the HMDB's search functions to facilitate better compound identification. Many other minor improvements and updates to the content, the interface, and general performance of the HMDB website have also been made. Overall, we believe these upgrades and updates should greatly enhance the HMDB's ease of use and its potential applications not only in human metabolomics but also in exposomics, lipidomics, nutritional science, biochemistry and clinical chemistry.

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