Tadao Kakegawa
- Pharmacology top 0.5%
- Surgery top 5%
- Cellular and Molecular Neuroscience top 2%
- Endocrinology, Diabetes and Metabolism top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Co-authors
- Masahiko FujinoKazuhiko TatemotoYuji KawamataMasaki HosoyaRyo FujiiShuji HinumaChieko KitadaTsutomu Kurokawa
- Topics
- Growth Hormone and Insulin-like Growth Factors (8 papers)Regulation of Appetite and Obesity (7 papers)Stress Responses and Cortisol (4 papers)
In The Last Decade
Tadao Kakegawa
16 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Pharmacology 1.2k
- Surgery 962
- Cellular and Molecular Neuroscience 662
- Endocrinology, Diabetes and Metabolism 327
- Cardiology and Cardiovascular Medicine 288
Countries citing papers authored by Tadao Kakegawa
This map shows the geographic impact of Tadao Kakegawa'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 Tadao Kakegawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tadao Kakegawa more than expected).
Fields of papers citing papers by Tadao Kakegawa
This network shows the impact of papers produced by Tadao Kakegawa. 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 Tadao Kakegawa. The network helps show where Tadao Kakegawa may publish in the future.
Co-authorship network of co-authors of Tadao Kakegawa
This figure shows the co-authorship network connecting the top 25 collaborators of Tadao Kakegawa. A scholar is included among the top collaborators of Tadao Kakegawa 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 Tadao Kakegawa. Tadao Kakegawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Isolation and Characterization of a Novel Endogenous Peptide Ligand for the Human APJ Receptorbreakdown → | 1405 |
| 2 | 11 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 3 | |
| 9 | 8 | |
| 10 | 10 | |
| 11 | 14 | |
| 12 | 50 | |
| 13 | 11 | |
| 14 | 15 | |
| 15 | 13 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | Ouabain-insensitive active transport of amino acid into rat pituitary gland | 1 |
About Tadao Kakegawa
Tadao Kakegawa is a scholar working on Endocrine and Autonomic Systems, Behavioral Neuroscience and Endocrinology, Diabetes and Metabolism, having authored 18 papers that have together received 1.6k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (8 papers), Regulation of Appetite and Obesity (7 papers) and Stress Responses and Cortisol (4 papers). The work is most often cited by research in Pharmacology (1.2k citations), Cellular and Molecular Neuroscience (662 citations) and Surgery (962 citations). Tadao Kakegawa has collaborated with scholars based in Japan and Czechia. Frequent co-authors include Masahiko Fujino, Kazuhiko Tatemoto, Yuji Kawamata, Masaki Hosoya, Ryo Fujii, Shuji Hinuma, Chieko Kitada, Tsutomu Kurokawa, Yugo Habata and Min‐Xu Zou. Their work appears in journals such as Brain Research, Biochemical and Biophysical Research Communications and 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.