The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Nuclear receptors: Decoding metabolic disease
Open accessAbstract
Nuclear receptors (NR) are a superfamily of ligand‐activated transcription factors that regulate development, reproduction, and metabolism of lipids, drugs and energy. The importance of this family of proteins in metabolic disease is exemplified by NR ligands used in the clinic or under exploratory development for the treatment of diabetes mellitus, dyslipidemia, hypercholesterolemia, or other metabolic abnormalities. Genetic studies in humans and rodents support the notion that NRs control a wide variety of metabolic processes by regulating the expression of genes encoding key enzymes, transporters and other proteins involved in metabolic homeostasis. Current knowledge of complex NR metabolic networks is summarized here.
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Cites
1 retracted
Orphan Receptor Small Heterodimer Partner Is an Important Mediator of Glucose Homeostasis
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BackgroundInfluentialSteroid Receptor Interactions with Heat Shock Protein and Immunophilin Chaperones*
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Cited by
Mechanisms of thyroid hormone action
Brent, G. A. (2012) · Journal of Clinical Investigation · doi:10.1172/jci60047 · Cited by 1,244
Pleiotropic Roles of Bile Acids in Metabolism
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Structure of the intact PPAR-γ–RXR-α nuclear receptor complex on DNA
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Structural Overview of the Nuclear Receptor Superfamily: Insights into Physiology and Therapeutics
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Circadian Clocks and Metabolism
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Metadata
- Authors
- Sonoda, J., Pei, L., & Evans, R. M.
- Venue
- FEBS Letters
- Publisher
- Wiley
- Published
- 2007-11-20
- Volume
- 582
- Issue
- 1
- Pages
- 2-9
- ISSN
- 0014-5793 (ISSN-L)
- 1873-3468
- OpenAlex
- W2076524169
- Cited by
- 313
- References
- 65
- FWCI
- 7.18
- 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.
