HMDB 5.0: the Human Metabolome Database for 2022. Issue Volume 50:Issue D1(2022) (19th November 2021)

• Record Type: Journal Article
• Authors: Wishart, David S; Guo, AnChi; Oler, Eponine; Wang, Fei; Anjum, Afia; Peters, Harrison; Dizon, Raynard; Sayeeda, Zinat; Tian, Siyang; Lee, Brian L; Berjanskii, Mark; Mah, Robert; Yamamoto, Mai; Jovel, Juan; Torres-Calzada, Claudia; Hiebert-Giesbrecht, Mickel; Lui, Vicki W; Varshavi, Dorna; Varshavi, Dorsa; Allen, Dana; Arndt, David; Khetarpal, Nitya; Sivakumaran, Aadhavya; Harford, Karxena; Sanford, Selena; Yee, Kristen; Cao, Xuan; Budinski, Zachary; Liigand, Jaanus; Zhang, Lun; Zheng, Jiamin; Mandal, Rupasri; Karu, Naama; Dambrova, Maija; Schiöth, Helgi B; Greiner, Russell; Gautam, Vasuk;
• Is Part Of: Nucleic acids research. Volume 50:Issue D1(2022)
• Page Start: D622
• Page End: D631
• Publication Date: 2021-11-19
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkab1062
• Languages: English
• ISSNs: 0305-1048

Abstract

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.