Kun Wang

4.1k citations
165 papers · 3.1k · h-index 32

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Electrospun Nanofibers in Biomedical Applications

Papers in

    • Knee injuries and reconstruction techniques 11
    • Orthopaedic implants and arthroplasty 9
    • Extracellular vesicles in disease 9

Kun Wang

154 papers receiving 3.1k citations

Peers

Kun Wang
Comparison fields: 5 of 133
  • Cancer Research 664
  • Biomaterials 275
  • Rehabilitation 133
  • Molecular Biology 1.3k
  • Biomedical Engineering 606
Replace Francesca Diomede with:
Francesca Diomede Italy
Lei Guo China
An Qin China
Shanshan Ma China
Rosa Maria Borzı̀ Italy
Hongjun Wang United States
Sang‐Mo Kwon South Korea
Yijie Zhang China
Shunji Hattori Japan
Kun Wang relative to Francesca Diomede Italy Francesca Diomede's profile →
Citations per field
00.5×1.5×
Francesca Diomede · 1×
Citations per year

Countries citing papers authored by Kun Wang

Since Specialization
Citations

This map shows the geographic impact of Kun Wang'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 Kun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Wang more than expected).

Fields of papers citing papers by Kun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kun Wang. 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 Kun Wang. The network helps show where Kun Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Kun Wang, 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 Kun Wang Line = papers co-authored together Kun Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 165 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015226
2 2020176
3 2011112
4 2017101
5 201991
6 202071
7 200864
8 201357
9 202054
10 202252
11 202151
12 202151
13 202151
14 202148
15 201947
16 202147
17 201846
18 201745
19 201444
20 202040

About Kun Wang

Kun Wang is a scholar working on Surgery, Molecular Biology, Cancer Research, Biomedical Engineering and Cell Biology, having authored 165 papers that have together received 3.1k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (33 papers), Bone Tissue Engineering Materials (17 papers), Knee injuries and reconstruction techniques (11 papers), Osteoarthritis Treatment and Mechanisms (10 papers), Wound Healing and Treatments (9 papers), Extracellular vesicles in disease (9 papers), Orthopaedic implants and arthroplasty (9 papers) and Electrospun Nanofibers in Biomedical Applications (8 papers). The work is most often cited by research in Cancer Research (664 citations), Biomaterials (275 citations), Rehabilitation (133 citations), Molecular Biology (1.3k citations) and Biomedical Engineering (606 citations). Kun Wang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Ronghan He, Yu‐Jui Yvonne Wan, Jianhua Ren, Huading Lu, Lulu Lv, Huiqing Zhao, Tangzhao Liang, Lei Zhu, Yang Cao and Yu Song. Their work appears in journals such as Biomedicine & Pharmacotherapy, International Journal of Biological Macromolecules, Frontiers in Cellular and Infection Microbiology, Frontiers in Oncology 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.

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