Ming Han
Impact in
- Hepatology top 10%
- Liver physiology and pathology
Papers in
- Epidemiology 13
- Liver Disease Diagnosis and Treatment 7
- Hepatitis B Virus Studies 5
- Autophagy in Disease and Therapy 3
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- Epigenetics and DNA Methylation 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)Yanhua Ma (4 shared papers)Jing Zhao (5 shared papers)Tianhui Zhang (2 shared papers)
- Journals
- Virus Research (2 papers)Hepatology International (2 papers)Cancer Science (2 papers)Journal of Personalized Medicine (1 paper)Cellular and Molecular Neurobiology (1 paper)
- Partner nations
- ChinaPhilippinesBelgium
In The Last Decade
Ming Han
22 papers receiving 395 citations
Peers
Comparison fields: 5 of 75
- Hepatology 78
- Aging 12
- Cancer Research 99
- Epidemiology 141
- Molecular Biology 199
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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 65 | |
| 2 | 2022 | 56 | |
| 3 | 2017 | 32 | |
| 4 | 2014 | 31 | |
| 5 | 2020 | 29 | |
| 6 | 2016 | 27 | |
| 7 | 2017 | 27 | |
| 8 | 2019 | 20 | |
| 9 | 2019 | 20 | |
| 10 | 2017 | 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 | 3 | |
| 20 | 2016 | 3 |
About Ming Han
Ming Han is a scholar working on Epidemiology, Molecular Biology, Hepatology, Cancer Research and Surgery, having authored 25 papers that have together received 396 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (7 papers), Liver physiology and pathology (6 papers), Hepatitis B Virus Studies (5 papers), MicroRNA in disease regulation (3 papers), Autophagy in Disease and Therapy (3 papers), Liver Disease and Transplantation (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Hepatology (78 citations), Aging (12 citations), Cancer Research (99 citations), Epidemiology (141 citations) and Molecular Biology (199 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, Yanhua Ma, Jing Zhao, Tianhui Zhang, Na Duan and Yaru Li. Their work appears in journals such as Virus Research, Hepatology International, Cancer Science, Journal of Personalized Medicine and Cellular and Molecular Neurobiology.
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.