Pierre De Meyts
- Molecular Biology top 1%
- Endocrinology, Diabetes and Metabolism top 0.2%
- Surgery top 1%
- Physiology top 1%
- Genetics top 2%
- Co-authors
- Jesse RothDavid M. NevilleJames R. GavinJonathan WhittakerC. Ronald KahnDonald N. BuellRonald M. ShymkoMaxine A. Lesniak
- Topics
- Growth Hormone and Insulin-like Growth Factors (58 papers)Metabolism, Diabetes, and Cancer (58 papers)Pancreatic function and diabetes (38 papers)
- Partner nations
- United StatesDenmarkBelgium
In The Last Decade
Pierre De Meyts
142 papers receiving 8.5k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Molecular Biology 5.6k
- Endocrinology, Diabetes and Metabolism 3.1k
- Surgery 2.3k
- Physiology 1.6k
- Genetics 1.0k
Countries citing papers authored by Pierre De Meyts
This map shows the geographic impact of Pierre De Meyts'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 Pierre De Meyts with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre De Meyts more than expected).
Fields of papers citing papers by Pierre De Meyts
This network shows the impact of papers produced by Pierre De Meyts. 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 Pierre De Meyts. The network helps show where Pierre De Meyts may publish in the future.
Co-authorship network of co-authors of Pierre De Meyts
This figure shows the co-authorship network connecting the top 25 collaborators of Pierre De Meyts. A scholar is included among the top collaborators of Pierre De Meyts 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 Pierre De Meyts. Pierre De Meyts is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 59 | |
| 2 | 90 | |
| 3 | 13 | |
| 4 | 93 | |
| 5 | 51 | |
| 6 | 29 | |
| 7 | 55 | |
| 8 | 84 | |
| 9 | 22 | |
| 10 | 68 | |
| 11 | 34 | |
| 12 | 251 | |
| 13 | 464 | |
| 14 | 54 | |
| 15 | 5 | |
| 16 | 47 | |
| 17 | 30 | |
| 18 | Monoclonal antibodies and specific cell surface receptors do not discriminate between human growth hormone prepared by DNA recombinant techniques and the native hormone. | 3 |
| 19 | The Hypoglycemic Effect of a Sulfonylurea (gliclazide) in Moderate Type-ii Diabetes and Glucose-intolerance Is Not Accompanied By Changes in Insulin Action and Insulin Binding To Erythrocytes | 5 |
| 20 | 80 |
About Pierre De Meyts
Pierre De Meyts is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Aging, having authored 145 papers that have together received 9.1k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (58 papers), Metabolism, Diabetes, and Cancer (58 papers) and Pancreatic function and diabetes (38 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (3.1k citations), Molecular Biology (5.6k citations) and Aging (123 citations). Pierre De Meyts has collaborated with scholars based in United States, Denmark and Belgium. Frequent co-authors include Jesse Roth, David M. Neville, James R. Gavin, Jonathan Whittaker, C. Ronald Kahn, Donald N. Buell, Ronald M. Shymko, Maxine A. Lesniak, Claus T. Christoffersen and Phillip Görden. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.