Tetsuya Kita
- Endocrinology, Diabetes and Metabolism top 5%
- Organic Chemistry top 10%
- Molecular Biology
- Cellular and Molecular Neuroscience top 10%
- Endocrine and Autonomic Systems top 5%
- Co-authors
- Takuo FujitaKazuo ChiharaHidesuke KajiYOICHI KASHIOYuichi HashimotoYasuhiko OkimuraKazuo NagasawaAngelina Georgieva
- Topics
- Growth Hormone and Insulin-like Growth Factors (16 papers)Neuropeptides and Animal Physiology (8 papers)Pituitary Gland Disorders and Treatments (7 papers)
- Cited by
- Endocrinology, Diabetes and MetabolismBehavioral NeuroscienceEndocrine and Autonomic Systems
- Journals
- Angewandte Chemie International EditionThe Journal of Clinical Endocrinology & MetabolismBrain Research
- Partner nations
- JapanUnited StatesSweden
In The Last Decade
Tetsuya Kita
35 papers receiving 867 citations
Peers
Comparison fields: 5 of 75
- Endocrinology, Diabetes and Metabolism 380
- Organic Chemistry 297
- Molecular Biology 240
- Cellular and Molecular Neuroscience 172
- Endocrine and Autonomic Systems 134
Countries citing papers authored by Tetsuya Kita
This map shows the geographic impact of Tetsuya Kita'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 Tetsuya Kita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tetsuya Kita more than expected).
Fields of papers citing papers by Tetsuya Kita
This network shows the impact of papers produced by Tetsuya Kita. 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 Tetsuya Kita. The network helps show where Tetsuya Kita may publish in the future.
Co-authorship network of co-authors of Tetsuya Kita
This figure shows the co-authorship network connecting the top 25 collaborators of Tetsuya Kita. A scholar is included among the top collaborators of Tetsuya Kita 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 Tetsuya Kita. Tetsuya Kita is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 10 | |
| 5 | 31 | |
| 6 | 51 | |
| 7 | 145 | |
| 8 | 42 | |
| 9 | 27 | |
| 10 | 42 | |
| 11 | 2 | |
| 12 | 82 | |
| 13 | 4 | |
| 14 | 23 | |
| 15 | 38 | |
| 16 | 5 | |
| 17 | 6 | |
| 18 | 37 | |
| 19 | 21 | |
| 20 | 25 |
About Tetsuya Kita
Tetsuya Kita is a scholar working on Endocrinology, Diabetes and Metabolism, Endocrine and Autonomic Systems and Behavioral Neuroscience, having authored 35 papers that have together received 896 indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (16 papers), Neuropeptides and Animal Physiology (8 papers) and Pituitary Gland Disorders and Treatments (7 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (380 citations), Behavioral Neuroscience (71 citations) and Endocrine and Autonomic Systems (134 citations). Tetsuya Kita has collaborated with scholars based in Japan, United States and Sweden. Frequent co-authors include Takuo Fujita, Kazuo Chihara, Hidesuke Kaji, YOICHI KASHIO, Yuichi Hashimoto, Yasuhiko Okimura, Kazuo Nagasawa, Angelina Georgieva, Tadashi Nakata and Hiromi Abe. Their work appears in journals such as Angewandte Chemie International Edition, The Journal of Clinical Endocrinology & Metabolism and Brain Research.
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.