Long Chen

7.6k citations
236 papers · 4.5k · h-index 39

Impact in

  • Genetics top 2%
    • Mesenchymal stem cell research
    • Electrospun Nanofibers in Biomedical Applications

Papers in

    • Tissue Engineering and Regenerative Medicine 10
    • Total Knee Arthroplasty Outcomes 7
    • Orthopaedic implants and arthroplasty 7

Long Chen

210 papers receiving 4.5k citations

Peers

Long Chen
Comparison fields: 5 of 165
  • Genetics 379
  • Biomaterials 488
  • Rehabilitation 178
  • Surgery 1.1k
  • Molecular Medicine 106
Replace Qin Shi with:
Qin Shi China
Shiqing Feng China
Dechun Geng China
Haibin Wang China
Jingping Liu China
Mei‐Ling Ho Taiwan
Ning Zhang China
Jiaxiang Bai China
Youshui Gao China
Hongjun Wang United States
Long Chen relative to Qin Shi China Qin Shi's profile →
Citations per field
00.5×1.5×
Qin Shi · 1×
Citations per year

Countries citing papers authored by Long Chen

Since Specialization
Citations

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

Fields of papers citing papers by Long Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 236 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019216
2 2010211
3 2011209
4 2009130
5 2020125
6 2016110
7 201890
8 202177
9 201171
10 202269
11 201968
12 201868
13 201967
14 202266
15 201766
16 201464
17 201763
18 202162
19 201455
20 202454

About Long Chen

Long Chen is a scholar working on Surgery, Molecular Biology, Biomedical Engineering, Genetics and Rheumatology, having authored 236 papers that have together received 4.5k indexed citations. Recurring topics across this work include Mesenchymal stem cell research (15 papers), Bone Tissue Engineering Materials (12 papers), Osteoarthritis Treatment and Mechanisms (10 papers), Electrospun Nanofibers in Biomedical Applications (10 papers), Tissue Engineering and Regenerative Medicine (10 papers), Total Knee Arthroplasty Outcomes (7 papers), Spine and Intervertebral Disc Pathology (7 papers) and Orthopaedic implants and arthroplasty (7 papers). The work is most often cited by research in Genetics (379 citations), Biomaterials (488 citations), Rehabilitation (178 citations), Surgery (1.1k citations) and Molecular Medicine (106 citations). Long Chen has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhou Xiang, Fei Xing, Heng Zhang, Kun Peng, Jun Huang, Hu Li, Hai‐Quan Mao, Song Yang, Jun Wu and Xiaowei Li. Their work appears in journals such as Journal of Biomedical Nanotechnology, Chinese Chemical Letters, Medicine, Scientific Reports and BMC Musculoskeletal Disorders.

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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