Ming Shen
Impact in
- Biomaterials top 2%
- Nanoparticle-Based Drug Delivery
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
-
- RNA Interference and Gene Delivery 11
- Surgery 37
- Co-authors
- Yourong Duan (21 shared papers)Ying Sun (18 shared papers)Yourong Duan (11 shared papers)Xingjun Guo (14 shared papers)King H. Yang (14 shared papers)Chengjian Shi (13 shared papers)Feng Zhu (10 shared papers)Xin Jin (11 shared papers)
- Journals
- Oncotarget (10 papers)Clinical Neurology and Neurosurgery (5 papers)SAE technical papers on CD-ROM/SAE technical paper series (5 papers)Theranostics (4 papers)ACS Applied Materials & Interfaces (4 papers)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Ming Shen
169 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 147
- Biomaterials 606
- Cancer Research 575
- Endocrinology, Diabetes and Metabolism 395
- Oncology 642
- Genetics 206
Countries citing papers authored by Ming Shen
This map shows the geographic impact of Ming Shen'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 Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Shen more than expected).
Fields of papers citing papers by Ming Shen
This network shows the impact of papers produced by Ming Shen. 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 Shen. The network helps show where Ming Shen may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Shen, 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 175 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 166 | |
| 2 | 2019 | 107 | |
| 3 | 2014 | 106 | |
| 4 | 2019 | 98 | |
| 5 | 2014 | 91 | |
| 6 | 2013 | 88 | |
| 7 | 2012 | 86 | |
| 8 | 2016 | 85 | |
| 9 | 2012 | 78 | |
| 10 | 2016 | 77 | |
| 11 | 2017 | 71 | |
| 12 | 2010 | 69 | |
| 13 | 2019 | 63 | |
| 14 | 2019 | 62 | |
| 15 | 2017 | 58 | |
| 16 | 2017 | 57 | |
| 17 | 2018 | 57 | |
| 18 | 2016 | 55 | |
| 19 | 2017 | 55 | |
| 20 | 2015 | 55 |
About Ming Shen
Ming Shen is a scholar working on Molecular Biology, Surgery, Pulmonary and Respiratory Medicine, Endocrinology, Diabetes and Metabolism and Epidemiology, having authored 175 papers that have together received 3.7k indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (33 papers), Nanoparticle-Based Drug Delivery (20 papers), Growth Hormone and Insulin-like Growth Factors (19 papers), Automotive and Human Injury Biomechanics (17 papers), Pancreatic and Hepatic Oncology Research (12 papers), Nanoplatforms for cancer theranostics (12 papers), RNA Interference and Gene Delivery (11 papers) and MicroRNA in disease regulation (11 papers). The work is most often cited by research in Biomaterials (606 citations), Cancer Research (575 citations), Endocrinology, Diabetes and Metabolism (395 citations), Oncology (642 citations) and Genetics (206 citations). Ming Shen has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Yourong Duan, Ying Sun, Yourong Duan, Xingjun Guo, King H. Yang, Chengjian Shi, Feng Zhu, Xin Jin, Haojie Mao and Yao Zhao. Their work appears in journals such as Oncotarget, Clinical Neurology and Neurosurgery, SAE technical papers on CD-ROM/SAE technical paper series, Theranostics and ACS Applied Materials & Interfaces.
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.