The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Metabolomics for Investigating Physiological and Pathophysiological Processes
Open accessAbstract
Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids. The rapid growth in metabolomics is leading to a renewed interest in metabolism and the role that small molecule metabolites play in many biological processes. As a result, traditional views of metabolites as being simply the “bricks and mortar” of cells or just the fuel for cellular energetics are being upended. Indeed, metabolites appear to have much more varied and far more important roles as signaling molecules, immune modulators, endogenous toxins, and environmental sensors. This review explores how metabolomics is yielding important new insights into a number of important biological and physiological processes. In particular, a major focus is on illustrating how metabolomics and discoveries made through metabolomics are improving our understanding of both normal physiology and the pathophysiology of many diseases. These discoveries are yielding new insights into how metabolites influence organ function, immune function, nutrient sensing, and gut physiology. Collectively, this work is leading to a much more unified and system-wide perspective of biology wherein metabolites, proteins, and genes are understood to interact synergistically to modify the actions and functions of organelles, organs, and organisms.
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Cites
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Cited by
Pang, Z., Lu, Y., Zhou, G., Hui, F., Xu, L., Viau, C., Spigelman, A. F., MacDonald, P. E., Wishart, D. S., Li, S., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae253 · Cited by 2,291
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Multi-Omics Profiling for Health
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MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics
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Metadata
- Authors
- Wishart, D. S.
- Venue
- Physiological Reviews
- Publisher
- American Physiological Society
- Published
- 2019-10-01
- Volume
- 99
- Issue
- 4
- Pages
- 1819-1875
- ISSN
- 0031-9333 (ISSN-L)
- 1522-1210
- OpenAlex
- W2969664314
- Cited by
- 1,212
- References
- 73
- FWCI
- 5.94
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
