Jun Jin
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Immunology top 10%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
Papers in
-
- Inflammasome and immune disorders 5
- Gene Regulatory Network Analysis 4
- Immunology 16
- Immune Cell Function and Interaction 12
- T-cell and B-cell Immunology 8
- Co-authors
- Cornelia M. Weyand (11 shared papers)Jörg J. Goronzy (12 shared papers)Chulwoo Kim (6 shared papers)Huimin Zhang (7 shared papers)Jianwei Shuai (12 shared papers)Fei Xu (10 shared papers)Rohit R. Jadhav (5 shared papers)Kai Wang (3 shared papers)
- Journals
- Chemistry & Biodiversity (4 papers)Chaos Solitons & Fractals (3 papers)Physical review. E (2 papers)Science Advances (2 papers)Cell Reports (2 papers)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Jun Jin
55 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 102
- Cancer Research 247
- Immunology 300
- Molecular Medicine 54
- Virology 41
- Molecular Biology 583
Countries citing papers authored by Jun Jin
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
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.
All Works
Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 137 | |
| 2 | 2018 | 91 | |
| 3 | 2022 | 84 | |
| 4 | 2014 | 59 | |
| 5 | 2022 | 53 | |
| 6 | 2020 | 50 | |
| 7 | 2017 | 44 | |
| 8 | 2018 | 42 | |
| 9 | 2020 | 42 | |
| 10 | 2019 | 37 | |
| 11 | 2023 | 37 | |
| 12 | 2018 | 37 | |
| 13 | 2017 | 36 | |
| 14 | 2021 | 36 | |
| 15 | 2019 | 35 | |
| 16 | 2016 | 35 | |
| 17 | 2021 | 32 | |
| 18 | 2009 | 32 | |
| 19 | 2023 | 30 | |
| 20 | 2023 | 27 |
About Jun Jin
Jun Jin is a scholar working on Molecular Biology, Immunology, Plant Science, Epidemiology and Pharmacology, having authored 60 papers that have together received 1.3k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (12 papers), T-cell and B-cell Immunology (8 papers), Inflammasome and immune disorders (5 papers), Phytochemistry and Bioactive Compounds (5 papers), Dermatologic Treatments and Research (4 papers), Gene Regulatory Network Analysis (4 papers), stochastic dynamics and bifurcation (4 papers) and Synthesis of Organic Compounds (3 papers). The work is most often cited by research in Cancer Research (247 citations), Immunology (300 citations), Molecular Medicine (54 citations), Virology (41 citations) and Molecular Biology (583 citations). Jun Jin has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Cornelia M. Weyand, Jörg J. Goronzy, Chulwoo Kim, Huimin Zhang, Jianwei Shuai, Fei Xu, Rohit R. Jadhav, Kai Wang, Bin Hu and Zhenhua Jia. Their work appears in journals such as Chemistry & Biodiversity, Chaos Solitons & Fractals, Physical review. E, Science Advances and Cell Reports.
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.