Jinping Pang
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Protein Degradation and Inhibitors
Papers in
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- Receptor Mechanisms and Signaling 4
- Protein Degradation and Inhibitors 3
- Genetics 13
- Estrogen and related hormone effects 13
- Co-authors
- Tingjun Hou (19 shared papers)Dan Li (15 shared papers)Xin Chai (13 shared papers)Lei Xu (12 shared papers)Chao Shen (6 shared papers)Dongsheng Cao (4 shared papers)Wenfang Zhou (5 shared papers)Qin Tang (3 shared papers)
In The Last Decade
Jinping Pang
20 papers receiving 455 citations
Peers
Comparison fields: 5 of 67
- Computational Theory and Mathematics 192
- Molecular Biology 275
- Genetics 108
- Endocrinology, Diabetes and Metabolism 49
- Pulmonary and Respiratory Medicine 85
Countries citing papers authored by Jinping Pang
This map shows the geographic impact of Jinping Pang'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 Jinping Pang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinping Pang more than expected).
Fields of papers citing papers by Jinping Pang
This network shows the impact of papers produced by Jinping Pang. 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 Jinping Pang. The network helps show where Jinping Pang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jinping Pang, 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 | 2018 | 59 | |
| 2 | 2020 | 57 | |
| 3 | 2020 | 53 | |
| 4 | 2018 | 39 | |
| 5 | 2021 | 35 | |
| 6 | 2021 | 33 | |
| 7 | 2020 | 21 | |
| 8 | 2022 | 20 | |
| 9 | 2022 | 19 | |
| 10 | 2022 | 19 | |
| 11 | 2020 | 18 | |
| 12 | 2021 | 16 | |
| 13 | 2021 | 15 | |
| 14 | 2021 | 13 | |
| 15 | 2021 | 12 | |
| 16 | 2023 | 8 | |
| 17 | 2022 | 8 | |
| 18 | 2021 | 7 | |
| 19 | 2022 | 7 | |
| 20 | 2025 | 1 |
About Jinping Pang
Jinping Pang is a scholar working on Molecular Biology, Genetics, Pulmonary and Respiratory Medicine, Computational Theory and Mathematics and Oncology, having authored 20 papers that have together received 460 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (13 papers), Prostate Cancer Treatment and Research (7 papers), Computational Drug Discovery Methods (6 papers), Receptor Mechanisms and Signaling (4 papers), Cytokine Signaling Pathways and Interactions (3 papers), Protein Degradation and Inhibitors (3 papers), Machine Learning in Materials Science (2 papers) and Hormonal and reproductive studies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (192 citations), Molecular Biology (275 citations), Genetics (108 citations), Endocrinology, Diabetes and Metabolism (49 citations) and Pulmonary and Respiratory Medicine (85 citations). Jinping Pang has collaborated with scholars based in China and Macao. Frequent co-authors include Tingjun Hou, Dan Li, Xin Chai, Lei Xu, Chao Shen, Dongsheng Cao, Wenfang Zhou, Qin Tang, Xueping Hu and Weitao Fu. Their work appears in journals such as European Journal of Medicinal Chemistry, Journal of Medicinal Chemistry, Briefings in Bioinformatics, Acta Pharmacologica Sinica and Drug Discovery Today.
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.