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
-
- Ion channel regulation and function 4
- Receptor Mechanisms and Signaling 4
- Fungal and yeast genetics research 2
-
- Hormonal Regulation and Hypertension 6
- Hormonal and reproductive studies 2
- Co-authors
- David E. Levin (2 shared papers)Yasuhiro Anraku (2 shared papers)Yoshikazu Ohya (2 shared papers)Hiroshi Qadota (2 shared papers)Michel B. Vallotton (8 shared papers)Michel F. Rossier (8 shared papers)A M Capponi (5 shared papers)Mikio Arisawa (1 shared paper)
- Journals
- Endocrinology (6 papers)Biochemical Journal (2 papers)Journal of Biological Chemistry (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 243
- Molecular Biology 844
- Endocrinology, Diabetes and Metabolism 170
- Plant Science 254
- 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 | 404 | |
| 2 | 1996 | 263 | |
| 3 | 1994 | 76 | |
| 4 | 1993 | 75 | |
| 5 | 1993 | 56 | |
| 6 | 1996 | 47 | |
| 7 | 1995 | 46 | |
| 8 | 1995 | 46 | |
| 9 | 1993 | 43 | |
| 10 | 1993 | 16 | |
| 11 | 1993 | 9 |
About C P Python
C P Python is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine and Pharmacology, 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), Hormonal and reproductive studies (2 papers), Fungal and yeast genetics research (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Cardiac electrophysiology and arrhythmias (1 paper) and Pharmacological Effects of Natural Compounds (1 paper). The work is most often cited by research in Cell Biology (243 citations), Molecular Biology (844 citations), Endocrinology, Diabetes and Metabolism (170 citations), Plant Science (254 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 David E. Levin, Yasuhiro Anraku, Yoshikazu Ohya, Hiroshi Qadota, Michel B. Vallotton, Michel F. Rossier, A M Capponi, Mikio Arisawa, Takahide Watanabe and Yi Zheng. Their work appears in journals such as Endocrinology, Biochemical Journal, Journal of Biological Chemistry 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.