Sen Shi
Impact in
- Nephrology top 5%
- Chronic Kidney Disease and Diabetes
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- Diabetes Treatment and Management
Papers in
-
- Fibroblast Growth Factor Research 2
- Oncology 7
- Peptidase Inhibition and Analysis 7
- Co-authors
- Daisuke Koya (13 shared papers)Keizo Kanasaki (13 shared papers)Munehiro Kitada (9 shared papers)Swayam Prakash Srivastava (7 shared papers)Takako Nagai (6 shared papers)Megumi Kanasaki (5 shared papers)Jianhua He (4 shared papers)Yuka Nakamura (3 shared papers)
In The Last Decade
Sen Shi
21 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 86
- Nephrology 169
- Endocrinology, Diabetes and Metabolism 294
- Cancer Research 168
- Oncology 244
- Geriatrics and Gerontology 24
Countries citing papers authored by Sen Shi
This map shows the geographic impact of Sen Shi'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 Sen Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sen Shi more than expected).
Fields of papers citing papers by Sen Shi
This network shows the impact of papers produced by Sen Shi. 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 Sen Shi. The network helps show where Sen Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Sen Shi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 301 | |
| 2 | 2015 | 132 | |
| 3 | 2018 | 105 | |
| 4 | 2016 | 81 | |
| 5 | 2014 | 75 | |
| 6 | 2014 | 63 | |
| 7 | 2016 | 57 | |
| 8 | 2017 | 54 | |
| 9 | 2016 | 53 | |
| 10 | 2020 | 51 | |
| 11 | 2016 | 38 | |
| 12 | 2016 | 37 | |
| 13 | 2019 | 26 | |
| 14 | 2022 | 14 | |
| 15 | Protective role of propofol on the kidney during early unilateral ureteral obstruction through inhibition of epithelial-mesenchymal transition. | 2016 | 10 |
| 16 | 2016 | 10 | |
| 17 | 2022 | 9 | |
| 18 | 2023 | 6 | |
| 19 | 2023 | 2 | |
| 20 | 2020 | 2 |
About Sen Shi
Sen Shi is a scholar working on Molecular Biology, Oncology, Endocrinology, Diabetes and Metabolism, Surgery and Nephrology, having authored 23 papers that have together received 1.1k indexed citations. Recurring topics across this work include Diabetes Treatment and Management (7 papers), Peptidase Inhibition and Analysis (7 papers), Chronic Kidney Disease and Diabetes (4 papers), Pregnancy and preeclampsia studies (2 papers), Advanced Sensor and Energy Harvesting Materials (2 papers), Dielectric materials and actuators (2 papers), Fibroblast Growth Factor Research (2 papers) and Cancer, Stress, Anesthesia, and Immune Response (2 papers). The work is most often cited by research in Nephrology (169 citations), Endocrinology, Diabetes and Metabolism (294 citations), Cancer Research (168 citations), Oncology (244 citations) and Geriatrics and Gerontology (24 citations). Sen Shi has collaborated with scholars based in Japan, China and Germany. Frequent co-authors include Daisuke Koya, Keizo Kanasaki, Munehiro Kitada, Swayam Prakash Srivastava, Takako Nagai, Megumi Kanasaki, Jianhua He, Yuka Nakamura, Yasuhito Ishigaki and Kyoko Nitta. Their work appears in journals such as BioMed Research International, Scientific Reports, Biochemical and Biophysical Research Communications, Dose-Response and Diabetologia.
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.