Jun Jin

2.4k citations
51 papers · 1.5k indexed · h-index 19

Impact in

  • Genetics top 5%
    • Mesenchymal stem cell research
    • Silk-based biomaterials and applications
    • Electrospun Nanofibers in Biomedical Applications

Papers in

Jun Jin

48 papers receiving 1.4k citations

Peers

Jun Jin
Comparison fields: 5 of 126
  • Genetics 324
  • Biomaterials 234
  • Urology 76
  • Critical Care and Intensive Care Medicine 59
  • Infectious Diseases 207
Replace Nora G. Singer with:
Nora G. Singer United States
Takashi Yokoyama Japan
Stefano de Franciscis Italy
Edward L. Snyder United States
Hakan Göker Türkiye
Jeffery J. Auletta United States
Bruno Amato Italy
Li Zhong China
Jun Jin relative to Nora G. Singer United States Nora G. Singer's profile →
Citations per field
00.5×1.5×2.5×
Nora G. Singer · 1×
Citations per year

Countries citing papers authored by Jun Jin

Since Specialization
Citations

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

Fields of papers citing papers by Jun Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006355
2 2020183
3 2005122
4 200859
5 200852
6 202048
7 200948
8 202041
9 202041
10 200638
11 201935
12 202032
13 201431
14 201227
15 202127
16 202126
17 202225
18 200519
19 201719
20 201118

About Jun Jin

Jun Jin is a scholar working on Critical Care and Intensive Care Medicine, Nephrology, Reproductive Medicine, Urology and Family Practice, having authored 51 papers that have together received 1.5k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (6 papers), Silk-based biomaterials and applications (5 papers), Bone Tissue Engineering Materials (4 papers), MRI in cancer diagnosis (4 papers), Ovarian cancer diagnosis and treatment (4 papers), COVID-19 Clinical Research Studies (4 papers), Periodontal Regeneration and Treatments (3 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Genetics (324 citations), Biomaterials (234 citations), Urology (76 citations), Critical Care and Intensive Care Medicine (59 citations) and Infectious Diseases (207 citations). Jun Jin has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zongning Miao, Jianzhong Zhu, Jidong Zhao, Xueguang Zhang, Lei Chen, Wei Huang, Jianhong Fu, Chenyan Zhao, Wei Wang and Xin Yu. Their work appears in journals such as Journal of Ovarian Research, Annals of Translational Medicine, Critical Care, Biochemical and Biophysical Research Communications and Cellular Reprogramming.

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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