Jin-Kui Pi

20 papers receiving 368 citations

Jin-Kui Pi's Hit Papers

Hydrogel-exosome system in tissue engineering: A promising therapeutic strategy 2024 · 64 citations
640+1Years since publication204060

Peers

Jin-Kui Pi
Comparison fields: 5 of 71
  • Rehabilitation 52
  • Biomaterials 74
  • Genetics 59
  • Surgery 132
  • Molecular Medicine 14
Replace Yonglong Hong with:
Yonglong Hong China
Niloofar Sodeifi Iran
Aika Yamawaki-Ogata Japan
Janaki Iyer Canada
Tahereh Tayebi Iran
Wen-Fu T. Lai Taiwan
Ziheng Bu China
C. Muller France
Zhangfan Ding China
Matthew D. Treiser United States
Jin-Kui Pi relative to Yonglong Hong China Yonglong Hong's profile →
Citations per field
00.5×1.5×1.9×
Yonglong Hong · 1×
Citations per year

Countries citing papers authored by Jin-Kui Pi

Since Specialization
Citations

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

Fields of papers citing papers by Jin-Kui Pi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin-Kui Pi. 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 Jin-Kui Pi. The network helps show where Jin-Kui Pi may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1
Hydrogel-exosome system in tissue engineering: A promising therapeutic strategy
Hit paper breakdown →
202464
2 202048
3 201843
4 201942
5 202229
6 202426
7 202125
8 201315
9 202115
10 201815
11 202213
12 202310
13 20227
14 20187
15 20236
16 20243
17 20231
18 20251
19 20241
20 20241

About Jin-Kui Pi

Jin-Kui Pi is a scholar working on Surgery, Molecular Biology, Genetics, Pulmonary and Respiratory Medicine and Biomaterials, having authored 20 papers that have together received 372 indexed citations. Recurring topics across this work include Tissue Engineering and Regenerative Medicine (7 papers), Mesenchymal stem cell research (4 papers), Electrospun Nanofibers in Biomedical Applications (4 papers), Extracellular vesicles in disease (3 papers), Neuroscience and Neural Engineering (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Photoreceptor and optogenetics research (2 papers) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Rehabilitation (52 citations), Biomaterials (74 citations), Genetics (59 citations), Surgery (132 citations) and Molecular Medicine (14 citations). Jin-Kui Pi has collaborated with scholars based in China. Frequent co-authors include Huiqi Xie, Yanlin Jiang, Ming‐Hui Fan, Hong‐Wei Gao, Anjing Chen, Xiuzhen Zhang, Han Chen, Fei Xing, Qianjin Li and Jesse Li‐Ling. Their work appears in journals such as ACS Biomaterials Science & Engineering, Journal of Materials Chemistry B, Materials Science and Engineering C, International Journal of Biological Macromolecules and The Prostate.

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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