Ken I. Mitchelhill
- Molecular Biology top 2%
- Physiology top 2%
- Surgery top 5%
- Endocrinology, Diabetes and Metabolism top 2%
- Cardiology and Cardiovascular Medicine top 5%
- Co-authors
- Bruce E. KempBelinda J. MichellDavid StapletonLee A. WittersColin M. HouseIgnacio Rodríguez‐CrespoDavid A. PowerGuang Gao
- Topics
- Metabolism, Diabetes, and Cancer (7 papers)Calcium signaling and nucleotide metabolism (5 papers)Pancreatic function and diabetes (4 papers)
- Cited by
- PhysiologyMolecular Biology
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryCurrent Biology
- Partner nations
- AustraliaUnited StatesCzechia
In The Last Decade
Ken I. Mitchelhill
25 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Molecular Biology 2.6k
- Physiology 1.0k
- Surgery 1.0k
- Endocrinology, Diabetes and Metabolism 466
- Cardiology and Cardiovascular Medicine 369
Countries citing papers authored by Ken I. Mitchelhill
This map shows the geographic impact of Ken I. Mitchelhill'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 Ken I. Mitchelhill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken I. Mitchelhill more than expected).
Fields of papers citing papers by Ken I. Mitchelhill
This network shows the impact of papers produced by Ken I. Mitchelhill. 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 Ken I. Mitchelhill. The network helps show where Ken I. Mitchelhill may publish in the future.
Co-authorship network of co-authors of Ken I. Mitchelhill
This figure shows the co-authorship network connecting the top 25 collaborators of Ken I. Mitchelhill. A scholar is included among the top collaborators of Ken I. Mitchelhill 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 Ken I. Mitchelhill. Ken I. Mitchelhill is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 20 | |
| 2 | 57 | |
| 3 | 442 | |
| 4 | AMP‐activated protein kinase phosphorylation of endothelial NO synthasebreakdown → | 711 |
| 5 | 70 | |
| 6 | 420 | |
| 7 | 115 | |
| 8 | 133 | |
| 9 | 105 | |
| 10 | Mammalian AMP-activated Protein Kinase Subfamilybreakdown → | 556 |
| 11 | 87 | |
| 12 | 114 | |
| 13 | 2 | |
| 14 | 4 | |
| 15 | 282 | |
| 16 | 111 | |
| 17 | 6 | |
| 18 | 122 | |
| 19 | 36 | |
| 20 | 17 |
About Ken I. Mitchelhill
Ken I. Mitchelhill is a scholar working on Physiology, Molecular Biology and Geriatrics and Gerontology, having authored 25 papers that have together received 3.5k indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (7 papers), Calcium signaling and nucleotide metabolism (5 papers) and Pancreatic function and diabetes (4 papers). The work is most often cited by research in Physiology (194 citations), Physiology (1.0k citations) and Molecular Biology (2.6k citations). Ken I. Mitchelhill has collaborated with scholars based in Australia, United States and Czechia. Frequent co-authors include Bruce E. Kemp, Belinda J. Michell, David Stapleton, Lee A. Witters, Colin M. House, Ignacio Rodríguez‐Crespo, David A. Power, Guang Gao, Paul R. Ortiz de Montellano and Zhiping Chen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Current Biology.
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.