C P Python
Impact in
- Cell Biology top 5%
- Cellular transport and secretion
- Molecular Biology top 10%
- Fungal and yeast genetics research
- Ion channel regulation and function
- Receptor Mechanisms and Signaling
- Protein Kinase Regulation and GTPase Signaling
Papers in
-
- Hormonal Regulation and Hypertension 6
- Hormonal and reproductive studies 2
-
- Ion channel regulation and function 4
- Receptor Mechanisms and Signaling 4
- Fungal and yeast genetics research 2
- Co-authors
- Hiroshi Qadota (2 shared papers)Yasuhiro Anraku (2 shared papers)David E. Levin (2 shared papers)Yoshikazu Ohya (2 shared papers)Michel B. Vallotton (8 shared papers)Michel Florian Rossier (8 shared papers)A M Capponi (5 shared papers)Shunsuke Ben Inoue (1 shared paper)
- Journals
- Endocrinology (6 papers)Journal of Biological Chemistry (2 papers)Biochemical Journal (2 papers)Science (1 paper)
- Partner nations
- SwitzerlandUnited StatesJapan
In The Last Decade
C P Python
11 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 72
- Cell Biology 246
- Molecular Biology 847
- Endocrinology, Diabetes and Metabolism 166
- Plant Science 255
- Cellular and Molecular Neuroscience 108
Countries citing papers authored by C P Python
This map shows the geographic impact of C P Python'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 C P Python with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C P Python more than expected).
Fields of papers citing papers by C P Python
This network shows the impact of papers produced by C P Python. 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 C P Python. The network helps show where C P Python may publish in the future.
Co-authors
The 20 scholars most cited alongside C P Python, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 407 | |
| 2 | 1996 | 264 | |
| 3 | 1994 | 76 | |
| 4 | 1993 | 75 | |
| 5 | 1993 | 57 | |
| 6 | 1996 | 46 | |
| 7 | 1995 | 45 | |
| 8 | 1995 | 45 | |
| 9 | 1993 | 43 | |
| 10 | 1993 | 16 | |
| 11 | 1993 | 9 |
About C P Python
C P Python is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology, Cellular and Molecular Neuroscience, Behavioral Neuroscience and Cardiology and Cardiovascular Medicine, having authored 11 papers that have together received 1.1k indexed citations. Recurring topics across this work include Hormonal Regulation and Hypertension (6 papers), Ion channel regulation and function (4 papers), Receptor Mechanisms and Signaling (4 papers), Fungal and yeast genetics research (2 papers), Hormonal and reproductive studies (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Renin-Angiotensin System Studies (1 paper) and Pharmacological Effects of Natural Compounds (1 paper). The work is most often cited by research in Cell Biology (246 citations), Molecular Biology (847 citations), Endocrinology, Diabetes and Metabolism (166 citations), Plant Science (255 citations) and Cellular and Molecular Neuroscience (108 citations). C P Python has collaborated with scholars based in Switzerland, United States and Japan. Frequent co-authors include Hiroshi Qadota, Yasuhiro Anraku, David E. Levin, Yoshikazu Ohya, Michel B. Vallotton, Michel Florian Rossier, A M Capponi, Shunsuke Ben Inoue, Takahide Watanabe and Mikio Arisawa. Their work appears in journals such as Endocrinology, Journal of Biological Chemistry, Biochemical Journal and Science.
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.