Haining Gan
Impact in
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- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- Molecular Medicine top 10%
- Curcumin's Biomedical Applications
Papers in
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- Metabolomics and Mass Spectrometry Studies 2
- Peroxisome Proliferator-Activated Receptors 2
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- Cancer, Lipids, and Metabolism 3
- MicroRNA in disease regulation 2
- Co-authors
- Dake Cai (11 shared papers)Yaoshu Teng (1 shared paper)Xuehu Xu (1 shared paper)Hanzhen Xiong (1 shared paper)Weixiang Liang (1 shared paper)Xuejuan Liu (1 shared paper)Dongzhi Cen (1 shared paper)Kun Wang (1 shared paper)
- Journals
- Molecular Therapy (1 paper)Phytotherapy Research (1 paper)Pharmaceutical Biology (1 paper)Biopharmaceutics & Drug Disposition (1 paper)Phytomedicine (1 paper)
- Partner nations
- China
In The Last Decade
Haining Gan
15 papers receiving 471 citations
Peers
Comparison fields: 5 of 77
- Immunology 199
- Molecular Medicine 40
- Oncology 219
- Complementary and alternative medicine 36
- Pharmacology 37
Countries citing papers authored by Haining Gan
This map shows the geographic impact of Haining Gan'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 Haining Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haining Gan more than expected).
Fields of papers citing papers by Haining Gan
This network shows the impact of papers produced by Haining Gan. 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 Haining Gan. The network helps show where Haining Gan may publish in the future.
Co-authors
The 25 scholars most cited alongside Haining Gan, 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 | 2019 | 234 | |
| 2 | 2018 | 49 | |
| 3 | 2016 | 44 | |
| 4 | 2018 | 35 | |
| 5 | 2019 | 27 | |
| 6 | 2021 | 24 | |
| 7 | 2022 | 14 | |
| 8 | 2018 | 14 | |
| 9 | 2020 | 11 | |
| 10 | 2023 | 8 | |
| 11 | 2016 | 6 | |
| 12 | 2024 | 5 | |
| 13 | 2022 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2024 | 1 |
About Haining Gan
Haining Gan is a scholar working on Molecular Biology, Cancer Research, Complementary and alternative medicine, Epidemiology and Surgery, having authored 15 papers that have together received 477 indexed citations. Recurring topics across this work include Cancer, Lipids, and Metabolism (3 papers), Traditional Chinese Medicine Analysis (3 papers), MicroRNA in disease regulation (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Curcumin's Biomedical Applications (2 papers), Peroxisome Proliferator-Activated Receptors (2 papers) and Pancreatic function and diabetes (1 paper). The work is most often cited by research in Immunology (199 citations), Molecular Medicine (40 citations), Oncology (219 citations), Complementary and alternative medicine (36 citations) and Pharmacology (37 citations). Haining Gan has collaborated with scholars based in China. Frequent co-authors include Dake Cai, Yaoshu Teng, Xuehu Xu, Hanzhen Xiong, Weixiang Liang, Xuejuan Liu, Dongzhi Cen, Kun Wang, Can Chen and Lin Xiao. Their work appears in journals such as Molecular Therapy, Phytotherapy Research, Pharmaceutical Biology, Biopharmaceutics & Drug Disposition and Phytomedicine.
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.