Chenyang Gu
Impact in
- Statistics and Probability top 10%
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
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- Breast Cancer Treatment Studies
- Cancer Genomics and Diagnostics
Papers in
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- Statistical Methods and Inference 4
- Advanced Causal Inference Techniques 4
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- Genomics and Chromatin Dynamics 4
- RNA Research and Splicing 2
- Co-authors
- Liangyuan Hu (3 shared papers)Michael J. Lopez (2 shared papers)Jiayi Ji (2 shared papers)Juan P. Wisnivesky (1 shared paper)Andrew Briggs (2 shared papers)Jing Zhao (2 shared papers)John S. Cook (2 shared papers)Cynthia Z. Qi (2 shared papers)
- Journals
- Biometrics (2 papers)Lung (1 paper)Changing English (1 paper)Health Services and Outcomes Research Methodology (1 paper)Solid State Ionics (1 paper)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Chenyang Gu
20 papers receiving 244 citations
Peers
Comparison fields: 5 of 72
- Statistics and Probability 43
- Cancer Research 74
- Oncology 93
- Pathology and Forensic Medicine 30
- Dermatology 14
Countries citing papers authored by Chenyang Gu
This map shows the geographic impact of Chenyang Gu'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 Chenyang Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenyang Gu more than expected).
Fields of papers citing papers by Chenyang Gu
This network shows the impact of papers produced by Chenyang Gu. 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 Chenyang Gu. The network helps show where Chenyang Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Chenyang Gu, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 89 | |
| 2 | 2020 | 43 | |
| 3 | 2020 | 32 | |
| 4 | 2021 | 10 | |
| 5 | 2021 | 9 | |
| 6 | 2020 | 9 | |
| 7 | 2022 | 8 | |
| 8 | 2024 | 7 | |
| 9 | 2023 | 6 | |
| 10 | 2022 | 6 | |
| 11 | 2020 | 5 | |
| 12 | 2016 | 4 | |
| 13 | 2022 | 4 | |
| 14 | 2024 | 3 | |
| 15 | 2020 | 3 | |
| 16 | 2013 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2021 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 1 |
About Chenyang Gu
Chenyang Gu is a scholar working on Statistics and Probability, Molecular Biology, Biomedical Engineering, Civil and Structural Engineering and Dermatology, having authored 22 papers that have together received 247 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (4 papers), Statistical Methods and Inference (4 papers), Advanced Causal Inference Techniques (4 papers), Nanowire Synthesis and Applications (3 papers), Ga2O3 and related materials (2 papers), Breast Cancer Treatment Studies (2 papers), Botulinum Toxin and Related Neurological Disorders (2 papers) and RNA Research and Splicing (2 papers). The work is most often cited by research in Statistics and Probability (43 citations), Cancer Research (74 citations), Oncology (93 citations), Pathology and Forensic Medicine (30 citations) and Dermatology (14 citations). Chenyang Gu has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Liangyuan Hu, Michael J. Lopez, Jiayi Ji, Juan P. Wisnivesky, Andrew Briggs, Jing Zhao, John S. Cook, Cynthia Z. Qi, Peter A. Fasching and Vassiliki Karantza. Their work appears in journals such as Biometrics, Lung, Changing English, Health Services and Outcomes Research Methodology and Solid State Ionics.
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.