Edward G. Rennels
- Endocrinology, Diabetes and Metabolism top 5%
- Molecular Biology
- Reproductive Medicine top 5%
- Physiology
- Cell Biology top 10%
- Co-authors
- Masataka ShiinoDamon C. HerbertAkira ArimuraAndrew V. SchallyHiroshi IshikawaR. H. RigdonAlbert E. SandersJohn C. Finerty
- Topics
- Growth Hormone and Insulin-like Growth Factors (38 papers)Birth, Development, and Health (11 papers)Reproductive Biology and Fertility (10 papers)
- Partner nations
- United StatesJapan
In The Last Decade
Edward G. Rennels
71 papers receiving 952 citations
Peers
Comparison fields: 5 of 96
- Endocrinology, Diabetes and Metabolism 423
- Molecular Biology 226
- Reproductive Medicine 191
- Physiology 144
- Cell Biology 114
Countries citing papers authored by Edward G. Rennels
This map shows the geographic impact of Edward G. Rennels'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 Edward G. Rennels with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward G. Rennels more than expected).
Fields of papers citing papers by Edward G. Rennels
This network shows the impact of papers produced by Edward G. Rennels. 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 Edward G. Rennels. The network helps show where Edward G. Rennels may publish in the future.
Co-authorship network of co-authors of Edward G. Rennels
This figure shows the co-authorship network connecting the top 25 collaborators of Edward G. Rennels. A scholar is included among the top collaborators of Edward G. Rennels 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 Edward G. Rennels. Edward G. Rennels is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | Functional correlates of anterior pituitary cytology. | 11 |
| 3 | 14 | |
| 4 | 11 | |
| 5 | Electron Microscopic Observations on Depression of Pituitary Prolactin Secretion by Vinblastine in the Rat | 3 |
| 6 | 3 | |
| 7 | 11 | |
| 8 | 15 | |
| 9 | 18 | |
| 10 | 18 | |
| 11 | 27 | |
| 12 | Effects of neonatal inoculation of thymus antiserum on growth of sarcoma 180 in mice. | 3 |
| 13 | 1 | |
| 14 | 3 | |
| 15 | 0 | |
| 16 | 33 | |
| 17 | 2 | |
| 18 | 8 | |
| 19 | A comparison of pituitary content of oxytocic hormone and the amount of Gomori-positive neurosecretion under normal and experimental conditions | 1 |
| 20 | 66 |
About Edward G. Rennels
Edward G. Rennels is a scholar working on Endocrinology, Diabetes and Metabolism, Behavioral Neuroscience and Reproductive Medicine, having authored 75 papers that have together received 1.1k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (38 papers), Birth, Development, and Health (11 papers) and Reproductive Biology and Fertility (10 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (423 citations), Reproductive Medicine (191 citations) and Behavioral Neuroscience (55 citations). Edward G. Rennels has collaborated with scholars based in United States and Japan. Frequent co-authors include Masataka Shiino, Damon C. Herbert, Akira Arimura, Andrew V. Schally, Hiroshi Ishikawa, Hiroshi Ishikawa, R. H. Rigdon, Albert E. Sanders, John C. Finerty and Arthur Ruskin. Their work appears in journals such as Science, Circulation Research and Biochemical and Biophysical Research Communications.
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.