Anthony J. Mason
- Molecular Biology top 1%
- Endocrinology, Diabetes and Metabolism top 0.5%
- Reproductive Medicine top 0.5%
- Genetics top 1%
- Public Health, Environmental and Occupational Health top 1%
- Co-authors
- Peter H. SeeburgRalph SchwallKároly NikolicsJoel S. HayflickJ. RamachandranHugh D. NiallJeffrey R. BellThomas J. Dull
- Topics
- TGF-β signaling in diseases (27 papers)Growth Hormone and Insulin-like Growth Factors (11 papers)Kruppel-like factors research (8 papers)
- Partner nations
- United StatesGermanyAustralia
In The Last Decade
Anthony J. Mason
53 papers receiving 7.3k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Molecular Biology 4.8k
- Endocrinology, Diabetes and Metabolism 1.6k
- Reproductive Medicine 1.5k
- Genetics 1.2k
- Public Health, Environmental and Occupational Health 1.0k
Countries citing papers authored by Anthony J. Mason
This map shows the geographic impact of Anthony J. Mason'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 Anthony J. Mason with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anthony J. Mason more than expected).
Fields of papers citing papers by Anthony J. Mason
This network shows the impact of papers produced by Anthony J. Mason. 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 Anthony J. Mason. The network helps show where Anthony J. Mason may publish in the future.
Co-authorship network of co-authors of Anthony J. Mason
This figure shows the co-authorship network connecting the top 25 collaborators of Anthony J. Mason. A scholar is included among the top collaborators of Anthony J. Mason 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 Anthony J. Mason. Anthony J. Mason 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 | 164 | |
| 3 | 1 | |
| 4 | 45 | |
| 5 | 92 | |
| 6 | 70 | |
| 7 | 121 | |
| 8 | 144 | |
| 9 | 29 | |
| 10 | 18 | |
| 11 | 136 | |
| 12 | 3 | |
| 13 | 225 | |
| 14 | 5 | |
| 15 | 77 | |
| 16 | 103 | |
| 17 | 70 | |
| 18 | 178 | |
| 19 | 29 | |
| 20 | 6 |
About Anthony J. Mason
Anthony J. Mason is a scholar working on Reproductive Medicine, Endocrinology, Diabetes and Metabolism and Molecular Biology, having authored 53 papers that have together received 7.6k indexed citations. Recurring topics across this work include TGF-β signaling in diseases (27 papers), Growth Hormone and Insulin-like Growth Factors (11 papers) and Kruppel-like factors research (8 papers). The work is most often cited by research in Reproductive Medicine (1.5k citations), Endocrinology, Diabetes and Metabolism (1.6k citations) and Molecular Biology (4.8k citations). Anthony J. Mason has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Peter H. Seeburg, Ralph Schwall, Károly Nikolics, Joel S. Hayflick, J. Ramachandran, Hugh D. Niall, Jeffrey R. Bell, Thomas J. Dull, Román Herrera and A Ullrich. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.