Ming Shen

5.5k citations
177 papers · 3.8k · h-index 35

Impact in

    • Nanoparticle-Based Drug Delivery
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research

Papers in

Ming Shen

171 papers receiving 3.8k citations

Peers

Ming Shen
Comparison fields: 5 of 148
  • Biomaterials 627
  • Cancer Research 523
  • Endocrinology, Diabetes and Metabolism 385
  • Oncology 581
  • Pharmaceutical Science 112
Replace Lang Chen with:
Lang Chen China
Hongjun Wang United States
Bobin Mi China
Adriana C. Panayi United States
George R. Beck United States
Hai Huang China
Hang Xue China
Jun Huang China
Sofia Avnet Italy
Junnan Tang China
Ming Shen relative to Lang Chen China Lang Chen's profile →
Citations per field
00.5×6.7×
Lang Chen · 1×
Citations per year

Countries citing papers authored by Ming Shen

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Ming Shen Line = papers co-authored together Ming Shen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 177 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013180
2 2019110
3 2014108
4 2019102
5 201498
6 201289
7 201388
8 201687
9 201287
10 201677
11 201774
12 201972
13 201070
14 201964
15 201764
16 201759
17 201557
18 201657
19 201857
20 201657

About Ming Shen

Ming Shen is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Pulmonary and Respiratory Medicine, Surgery and Oncology, having authored 177 papers that have together received 3.8k indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (31 papers), Nanoparticle-Based Drug Delivery (19 papers), Automotive and Human Injury Biomechanics (18 papers), Pancreatic and Hepatic Oncology Research (11 papers), RNA Interference and Gene Delivery (10 papers), MicroRNA in disease regulation (10 papers), Nanoplatforms for cancer theranostics (10 papers) and Traffic and Road Safety (9 papers). The work is most often cited by research in Biomaterials (627 citations), Cancer Research (523 citations), Endocrinology, Diabetes and Metabolism (385 citations), Oncology (581 citations) and Pharmaceutical Science (112 citations). Ming Shen has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Yourong Duan, Ying Sun, Yourong Duan, Xingjun Guo, King H. Yang, Chengjian Shi, Xin Jin, Feng Zhu, Haojie Mao and Xuefei Shou. Their work appears in journals such as Oncotarget, SAE technical papers on CD-ROM/SAE technical paper series, Clinical Neurology and Neurosurgery, ACS Applied Materials & Interfaces and Theranostics.

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.

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