Stephen D. Ayers
Impact in
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- Thyroid Disorders and Treatments
- Growth Hormone and Insulin-like Growth Factors
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- Peroxisome Proliferator-Activated Receptors
- Epigenetics and DNA Methylation
Papers in
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- Peroxisome Proliferator-Activated Receptors 5
- Epigenetics and DNA Methylation 3
- RNA and protein synthesis mechanisms 2
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- Thyroid Disorders and Treatments 2
- Hormonal Regulation and Hypertension 2
- Co-authors
- Richard E. Gillilan (2 shared papers)Noa Noy (2 shared papers)Paul Webb (8 shared papers)Anusha Angajala (2 shared papers)Helen Y. Wang (1 shared paper)Wei Zhao (1 shared paper)Igor Polikarpov (2 shared papers)Amanda Bernardes (2 shared papers)
- Journals
- Journal of Molecular Biology (2 papers)Molecular and Cellular Endocrinology (1 paper)Methods (1 paper)The Journal of Steroid Biochemistry and Molecular Biology (1 paper)Thyroid (1 paper)
- Partner nations
- United StatesChinaBrazil
In The Last Decade
Stephen D. Ayers
15 papers receiving 923 citations
Peers
Comparison fields: 5 of 87
- Endocrinology, Diabetes and Metabolism 131
- Molecular Biology 555
- Biochemistry 50
- Cancer Research 82
- Physiology 108
Countries citing papers authored by Stephen D. Ayers
This map shows the geographic impact of Stephen D. Ayers's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stephen D. Ayers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen D. Ayers more than expected).
Fields of papers citing papers by Stephen D. Ayers
This network shows the impact of papers produced by Stephen D. Ayers. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stephen D. Ayers. The network helps show where Stephen D. Ayers may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen D. Ayers, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 140 | |
| 2 | 2013 | 122 | |
| 3 | 2007 | 121 | |
| 4 | 2013 | 89 | |
| 5 | 2011 | 88 | |
| 6 | 2012 | 85 | |
| 7 | 2014 | 50 | |
| 8 | 2014 | 44 | |
| 9 | 2007 | 44 | |
| 10 | 2012 | 43 | |
| 11 | 2012 | 37 | |
| 12 | 2015 | 28 | |
| 13 | 2014 | 24 | |
| 14 | 2013 | 24 | |
| 15 | 2011 | 5 |
About Stephen D. Ayers
Stephen D. Ayers is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Surgery, Genetics and Cancer Research, having authored 15 papers that have together received 944 indexed citations. Recurring topics across this work include Peroxisome Proliferator-Activated Receptors (5 papers), Epigenetics and DNA Methylation (3 papers), Cholesterol and Lipid Metabolism (2 papers), Thyroid Disorders and Treatments (2 papers), Hormonal Regulation and Hypertension (2 papers), Estrogen and related hormone effects (2 papers), NF-κB Signaling Pathways (2 papers) and RNA and protein synthesis mechanisms (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (131 citations), Molecular Biology (555 citations), Biochemistry (50 citations), Cancer Research (82 citations) and Physiology (108 citations). Stephen D. Ayers has collaborated with scholars based in United States, China and Brazil. Frequent co-authors include Richard E. Gillilan, Noa Noy, Paul Webb, Anusha Angajala, Helen Y. Wang, Wei Zhao, Igor Polikarpov, Amanda Bernardes, Peter S. Reinach and Munir S. Skaf. Their work appears in journals such as Journal of Molecular Biology, Molecular and Cellular Endocrinology, Methods, The Journal of Steroid Biochemistry and Molecular Biology and Thyroid.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.