Ming Han
Impact in
- Hepatology top 10%
- Liver physiology and pathology
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
- Epidemiology 11
- Hepatitis B Virus Studies 5
- Liver Disease Diagnosis and Treatment 5
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- Gut microbiota and health 2
- Extracellular vesicles in disease 2
- Peroxisome Proliferator-Activated Receptors 2
- Co-authors
- Jun Cheng (13 shared papers)Shunai Liu (15 shared papers)Xiaoxue Yuan (11 shared papers)Li Zhou (7 shared papers)Kai Han (7 shared papers)Jing Zhao (5 shared papers)Yanhua Ma (4 shared papers)Tianhui Zhang (2 shared papers)
- Journals
- Hepatology International (2 papers)Virus Research (2 papers)Cancer Science (2 papers)Journal of Personalized Medicine (1 paper)Human Reproduction (1 paper)
- Partner nations
- ChinaPhilippinesBelgium
In The Last Decade
Ming Han
25 papers receiving 412 citations
Peers
Comparison fields: 5 of 73
- Hepatology 77
- Cancer Research 86
- Aging 10
- Epidemiology 129
- Molecular Biology 173
Countries citing papers authored by Ming Han
This map shows the geographic impact of Ming Han'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 Ming Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Han more than expected).
Fields of papers citing papers by Ming Han
This network shows the impact of papers produced by Ming Han. 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 Ming Han. The network helps show where Ming Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Han, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 65 | |
| 2 | 2022 | 63 | |
| 3 | 2017 | 33 | |
| 4 | 2014 | 31 | |
| 5 | 2020 | 30 | |
| 6 | 2017 | 27 | |
| 7 | 2016 | 27 | |
| 8 | 2019 | 23 | |
| 9 | 2017 | 21 | |
| 10 | 2019 | 20 | |
| 11 | 2020 | 14 | |
| 12 | 2020 | 12 | |
| 13 | 2022 | 8 | |
| 14 | 2016 | 7 | |
| 15 | 2023 | 5 | |
| 16 | 2019 | 5 | |
| 17 | 2017 | 5 | |
| 18 | 2024 | 4 | |
| 19 | 2018 | 4 | |
| 20 | 2016 | 4 |
About Ming Han
Ming Han is a scholar working on Epidemiology, Molecular Biology, Hepatology, Cancer Research and Cell Biology, having authored 26 papers that have together received 414 indexed citations. Recurring topics across this work include Liver physiology and pathology (6 papers), Hepatitis B Virus Studies (5 papers), Liver Disease Diagnosis and Treatment (5 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Gut microbiota and health (2 papers), Cholesterol and Lipid Metabolism (2 papers), Extracellular vesicles in disease (2 papers) and Peroxisome Proliferator-Activated Receptors (2 papers). The work is most often cited by research in Hepatology (77 citations), Cancer Research (86 citations), Aging (10 citations), Epidemiology (129 citations) and Molecular Biology (173 citations). Ming Han has collaborated with scholars based in China, Philippines and Belgium. Frequent co-authors include Jun Cheng, Shunai Liu, Xiaoxue Yuan, Li Zhou, Kai Han, Jing Zhao, Yanhua Ma, Tianhui Zhang, Na Duan and Zitong Wang. Their work appears in journals such as Hepatology International, Virus Research, Cancer Science, Journal of Personalized Medicine and Human Reproduction.
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.