Peng Feng
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- Diabetes Treatment and Management 8
- Neurology top 10%
- Parkinson's Disease Mechanisms and Treatments 8
- Neurological Disease Mechanisms and Treatments 3
- Neuroinflammation and Neurodegeneration Mechanisms 2
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- Nuclear Receptors and Signaling 5
- Neurology top 10%
- Parkinson's Disease Mechanisms and Treatments 8
- Neurological Disease Mechanisms and Treatments 3
- Neuroinflammation and Neurodegeneration Mechanisms 2
- Physiology top 10%
- Reproductive biology and impacts on aquatic species 2
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- Metabolism, Diabetes, and Cancer 3
- Circular RNAs in diseases 2
Peng Feng
21 papers receiving 637 citations
Peers
Comparison fields: 5 of 68
- Endocrinology, Diabetes and Metabolism 316
- Neurology 179
- Cellular and Molecular Neuroscience 213
- Neurology 79
- Physiology 38
Countries citing papers authored by Peng Feng
This map shows the geographic impact of Peng Feng'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 Peng Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peng Feng more than expected).
Fields of papers citing papers by Peng Feng
This network shows the impact of papers produced by Peng Feng. 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 Peng Feng. The network helps show where Peng Feng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peng Feng, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 3 | |
| 4 | 2024 | 12 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 4 | |
| 7 | 2022 | 36 | |
| 8 | 2022 | 8 | |
| 9 | 2020 | 17 | |
| 10 | 2019 | 79 | |
| 11 | 2019 | 22 | |
| 12 | 2018 | 43 | |
| 13 | 2018 | 93 | |
| 14 | 2017 | 88 | |
| 15 | 2016 | 79 | |
| 16 | 2015 | 89 | |
| 17 | 2015 | 20 | |
| 18 | The correlation between blood pressure, heart rate circadian rhythm change and left ventricular hypertrophy in essential hypertensive patients | 2012 | 1 |
| 19 | 2010 | 1 | |
| 20 | [Protective effect of total paeony glycoside against cerebral ischemia-reperfusion injury in mice]. | 2000 | 5 |
About Peng Feng
Peng Feng is a scholar working on Physiology, Endocrinology, Diabetes and Metabolism and Neurology, having authored 23 papers that have together received 642 indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (8 papers), Diabetes Treatment and Management (8 papers), Nuclear Receptors and Signaling (5 papers), Neurological Disease Mechanisms and Treatments (3 papers), Metabolism, Diabetes, and Cancer (3 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Reproductive biology and impacts on aquatic species (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (316 citations), Neurology (179 citations) and Cellular and Molecular Neuroscience (213 citations). Peng Feng has collaborated with scholars based in China, United Kingdom and Spain. Frequent co-authors include Christian Hölscher, Dongfang Li, Guanglai Li, Guofang Xue, Chenhui Ji, Ziyue Yuan, Xiaoyan Yang, Xiangjian Zhang, Wenshi Wei and Jun‐Li Cao. Their work appears in journals such as Journal of Clinical Oncology, Brain Research and European Journal of Pharmacology.
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.