The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
HMDB 5.0: the Human Metabolome Database for 2022
Open accessAbstract
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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The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.18 · Cited by 18,423
DrugBank 5.0: a major update to the DrugBank database for 2018
Wishart, D. S., Feunang, Y. D., Guo, A. C., Lo, E. J., Marcu, A., Grant, J. R., Sajed, T., Johnson, D., Li, C., Sayeeda, Z., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1037 · Cited by 8,404
Self-citationGlobal chemical effects of the microbiome include new bile-acid conjugations
Quinn, R. A., Melnik, A. V., Vrbanac, A., Fu, T., Patras, K. A., Christy, M. P., Bodai, Z., Belda-Ferre, P., Tripathi, A., Chung, L. K., et al. (2020) · Nature · doi:10.1038/s41586-020-2047-9 · Cited by 579
Cited by
Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkae1059 · Cited by 1,625
Applications of multi‐omics analysis in human diseases
Chen, C., Wang, J., Pan, D., Wang, X., Xu, Y., Yan, J., Wang, L., Yang, X., Yang, M., & Liu, G. (2023) · MedComm · doi:10.1002/mco2.315 · Cited by 545
Inhibition of inflammatory microglia by dietary fiber and short-chain fatty acids
Caetano-Silva, M. E., Rund, L., Hutchinson, N. T., Woods, J. A., Steelman, A. J., & Johnson, R. W. (2023) · Scientific Reports · doi:10.1038/s41598-022-27086-x · Cited by 225
Holden, D. T., Morato, N. M., & Cooks, R. G. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2212642119 · Cited by 147
Annotating metabolite mass spectra with domain-inspired chemical formula transformers
Goldman, S., Wohlwend, J., Stražar, M., Haroush, G., Xavier, R. J., & Coley, C. W. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00708-3 · Cited by 87
Metadata
- Authors
- Wishart, D. S., Guo, A., Oler, E., Wang, F., Anjum, A., Peters, H., Dizon, R., Sayeeda, Z., Tian, S., Lee, B. L., Berjanskii, M., Mah, R., Yamamoto, M., Jovel, J., Torres-Calzada, C., Hiebert-Giesbrecht, M., Lui, V. W., Varshavi, D., Varshavi, D., Allen, D., Arndt, D., Khetarpal, N., Sivakumaran, A., Harford, K., Sanford, S., Yee, K., Cao, X., Budinski, Z., Liigand, J., Zhang, L., Zheng, J., Mandal, R., Karu, N., Dambrova, M., Schiöth, H. B., Greiner, R., & Gautam, V.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-11-19
- Volume
- 50
- Issue
- D1
- Pages
- D622-D631
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W4206447491
- Cited by
- 2,519
- References
- 3
- FWCI
- 86.47
- Type
- journal article
- Language
- en
- Open access
- gold
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- The paper
- Wishart, D. S., Guo, A., Oler, E., Wang, F., Anjum, A., Peters, H., Dizon, R., Sayeeda, Z., Tian, S., Lee, B. L., Berjanskii, M., Mah, R., Yamamoto, M., Jovel, J., Torres-Calzada, C., Hiebert-Giesbrecht, M., Lui, V. W., Varshavi, D., Varshavi, D., . . . Gautam, V. (2022). HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Research. https://doi.org/10.1093/nar/gkab1062
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.