Stephen D. Ayers
Impact in
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- Peroxisome Proliferator-Activated Receptors
- Epigenetics and DNA Methylation
- Biochemistry top 10%
Papers in ⓘ
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- Thyroid Disorders and Treatments 2
- Hormonal Regulation and Hypertension 2
- Growth Hormone and Insulin-like Growth Factors 2
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- Peroxisome Proliferator-Activated Receptors 6
- Epigenetics and DNA Methylation 3
- Genomics and Chromatin Dynamics 2
- RNA and protein synthesis mechanisms 2
- Co-authors
- Noa Noy (2 shared papers)Richard E. Gillilan (2 shared papers)Paul Webb (8 shared papers)Anusha Angajala (2 shared papers)Qingyuan Zhu (1 shared paper)Amanda Bernardes (2 shared papers)Igor Polikarpov (2 shared papers)Munir S. Skaf (2 shared papers)
- Journals
- Journal of Molecular Biology (2 papers)Methods (1 paper)The Journal of Steroid Biochemistry and Molecular Biology (1 paper)Thyroid (1 paper)Molecular Endocrinology (1 paper)
- Partner nations
- United StatesMexicoCanada
In The Last Decade
Stephen D. Ayers
15 papers receiving 886 citations
Peers
Comparison fields: 5 of 90
- Molecular Biology 557
- Biochemistry 55
- Endocrinology, Diabetes and Metabolism 123
- Cancer Research 89
- Physiology 112
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 | 136 | |
| 2 | 2013 | 119 | |
| 3 | 2007 | 116 | |
| 4 | 2013 | 86 | |
| 5 | 2011 | 84 | |
| 6 | 2012 | 81 | |
| 7 | 2014 | 48 | |
| 8 | 2014 | 42 | |
| 9 | 2012 | 41 | |
| 10 | 2007 | 38 | |
| 11 | 2012 | 36 | |
| 12 | 2014 | 24 | |
| 13 | 2015 | 24 | |
| 14 | 2013 | 22 | |
| 15 | 2011 | 5 |
About Stephen D. Ayers
Stephen D. Ayers is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology, Biochemistry, Cancer Research and Pharmacology, having authored 15 papers that have together received 902 indexed citations. Recurring topics across this work include Peroxisome Proliferator-Activated Receptors (6 papers), Epigenetics and DNA Methylation (3 papers), Thyroid Disorders and Treatments (2 papers), Genomics and Chromatin Dynamics (2 papers), Hormonal Regulation and Hypertension (2 papers), Cholesterol and Lipid Metabolism (2 papers), RNA and protein synthesis mechanisms (2 papers) and Growth Hormone and Insulin-like Growth Factors (2 papers). The work is most often cited by research in Molecular Biology (557 citations), Biochemistry (55 citations), Endocrinology, Diabetes and Metabolism (123 citations), Cancer Research (89 citations) and Physiology (112 citations). Stephen D. Ayers has collaborated with scholars based in United States, Mexico and Canada. Frequent co-authors include Noa Noy, Richard E. Gillilan, Paul Webb, Anusha Angajala, Qingyuan Zhu, Amanda Bernardes, Igor Polikarpov, Munir S. Skaf, Peter S. Reinach and Helen Y. Wang. Their work appears in journals such as Journal of Molecular Biology, Methods, The Journal of Steroid Biochemistry and Molecular Biology, Thyroid and Molecular Endocrinology.
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.