Ming Jin
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Oncology top 10%
- Colorectal Cancer Surgical Treatments
- Pancreatic and Hepatic Oncology Research
Papers in
-
- 14-3-3 protein interactions 6
- Epigenetics and DNA Methylation 6
- RNA modifications and cancer 6
- Oncology 18
- Lung Cancer Research Studies 5
- Peptidase Inhibition and Analysis 5
- Co-authors
- Wendy L. Frankel (6 shared papers)Kwang Won Jeong (5 shared papers)Haifeng Wu (4 shared papers)Paul E. Wakely (7 shared papers)Jin‐Shui Zhu (2 shared papers)Xiaoyu Chen (2 shared papers)Joel Saltz (1 shared paper)Lidan Hou (1 shared paper)
- Journals
- Journal of Clinical Laboratory Analysis (5 papers)Aging (3 papers)Frontiers in Oncology (2 papers)Scientific Reports (2 papers)BMC Cancer (2 papers)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Ming Jin
76 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 101
- Cancer Research 278
- Oncology 375
- Nephrology 72
- Immunology 186
- Molecular Biology 563
Countries citing papers authored by Ming Jin
This map shows the geographic impact of Ming Jin'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 Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Jin more than expected).
Fields of papers citing papers by Ming Jin
This network shows the impact of papers produced by Ming Jin. 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 Jin. The network helps show where Ming Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Jin, 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 80 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 127 | |
| 2 | 2008 | 124 | |
| 3 | 2017 | 98 | |
| 4 | 2005 | 87 | |
| 5 | 2009 | 66 | |
| 6 | 2017 | 66 | |
| 7 | 2010 | 65 | |
| 8 | 2014 | 63 | |
| 9 | 2019 | 47 | |
| 10 | 2020 | 43 | |
| 11 | 2018 | 42 | |
| 12 | 2015 | 42 | |
| 13 | 2016 | 41 | |
| 14 | 2023 | 39 | |
| 15 | 2013 | 38 | |
| 16 | 2018 | 37 | |
| 17 | 2013 | 28 | |
| 18 | 2018 | 25 | |
| 19 | 2019 | 22 | |
| 20 | 2021 | 21 |
About Ming Jin
Ming Jin is a scholar working on Molecular Biology, Oncology, Pulmonary and Respiratory Medicine, Epidemiology and Surgery, having authored 80 papers that have together received 1.5k indexed citations. Recurring topics across this work include Neuroendocrine Tumor Research Advances (7 papers), 14-3-3 protein interactions (6 papers), Epigenetics and DNA Methylation (6 papers), Ferroptosis and cancer prognosis (6 papers), RNA modifications and cancer (6 papers), Lung Cancer Research Studies (5 papers), Peptidase Inhibition and Analysis (5 papers) and Cancer-related molecular mechanisms research (5 papers). The work is most often cited by research in Cancer Research (278 citations), Oncology (375 citations), Nephrology (72 citations), Immunology (186 citations) and Molecular Biology (563 citations). Ming Jin has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Wendy L. Frankel, Kwang Won Jeong, Haifeng Wu, Paul E. Wakely, Jin‐Shui Zhu, Xiaoyu Chen, Joel Saltz, Lidan Hou, Jing Zhang and Hongjian Wang. Their work appears in journals such as Journal of Clinical Laboratory Analysis, Aging, Frontiers in Oncology, Scientific Reports and BMC Cancer.
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.