Daniel Kelly
- Endocrinology, Diabetes and Metabolism top 2%
- Pharmacology top 5%
- Molecular Biology
- Reproductive Medicine top 5%
- Physiology
- Co-authors
- T. Hugh JonesDonna SellersKevin S. ChannerJoanne E. NettleshipSamia AkhtarVakkat MuraleedharanAksam YassinMustafa Alwani
- Topics
- Hormonal and reproductive studies (14 papers)Pharmacology and Obesity Treatment (7 papers)Pharmacological Effects and Assays (3 papers)
- Partner nations
- United KingdomQatarJordan
In The Last Decade
Daniel Kelly
15 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Endocrinology, Diabetes and Metabolism 658
- Pharmacology 225
- Molecular Biology 192
- Reproductive Medicine 160
- Physiology 155
Countries citing papers authored by Daniel Kelly
This map shows the geographic impact of Daniel Kelly'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 Daniel Kelly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kelly more than expected).
Fields of papers citing papers by Daniel Kelly
This network shows the impact of papers produced by Daniel Kelly. 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 Daniel Kelly. The network helps show where Daniel Kelly may publish in the future.
Co-authorship network of co-authors of Daniel Kelly
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Kelly. A scholar is included among the top collaborators of Daniel Kelly based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Kelly. Daniel Kelly is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 11 | |
| 5 | 83 | |
| 6 | 11 | |
| 7 | 24 | |
| 8 | How do “heroes” speak up? NHS staff raising concerns during covid-19 | 3 |
| 9 | 0 | |
| 10 | 67 | |
| 11 | Testosterone and obesitybreakdown → | 334 |
| 12 | 77 | |
| 13 | 209 | |
| 14 | 219 | |
| 15 | 30 | |
| 16 | Investigating the atheroprotective effect of testosterone: Role in modulation of inflammatory markers in the development of early atherogenesis in the testicular feminised mouse model | 1 |
About Daniel Kelly
Daniel Kelly is a scholar working on Endocrinology, Diabetes and Metabolism, Pharmacology and Reproductive Medicine, having authored 16 papers that have together received 1.1k indexed citations. Recurring topics across this work include Hormonal and reproductive studies (14 papers), Pharmacology and Obesity Treatment (7 papers) and Pharmacological Effects and Assays (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (658 citations), Reproductive Medicine (160 citations) and Pharmacology (225 citations). Daniel Kelly has collaborated with scholars based in United Kingdom, Qatar and Jordan. Frequent co-authors include T. Hugh Jones, Donna Sellers, Kevin S. Channer, Joanne E. Nettleship, Samia Akhtar, Vakkat Muraleedharan, T. Hugh Jones, Aksam Yassin, Mustafa Alwani and Omar M. Aboumarzouk. Their work appears in journals such as Life Sciences, Obesity Reviews and Nature Reviews 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.