Sun‐Mi Yun
Impact in
- Pharmacology top 5%
- Medicinal Plant Pharmacodynamics Research
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- Traditional Chinese Medicine Analysis
Papers in
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- PI3K/AKT/mTOR signaling in cancer 5
- Genomics, phytochemicals, and oxidative stress 5
- Natural product bioactivities and synthesis 3
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- Insect Utilization and Effects 7
- Silkworms and Sericulture Research 4
- Co-authors
- Eun‐Hee Kim (13 shared papers)Sung‐Hoon Kim (8 shared papers)Soo‐Jin Jeong (8 shared papers)Seok‐Ho Kim (4 shared papers)Bonglee Kim (2 shared papers)Ji Hoon Jung (5 shared papers)Da-Young Lee (9 shared papers)Ji‐Hyun Kim (5 shared papers)
- Journals
- Cancer Letters (4 papers)Oncotarget (2 papers)Journal of Functional Foods (2 papers)Journal of Pineal Research (1 paper)Scientific Reports (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Sun‐Mi Yun
34 papers receiving 845 citations
Peers
Comparison fields: 5 of 96
- Pharmacology 104
- Complementary and alternative medicine 77
- Endocrine and Autonomic Systems 62
- Molecular Biology 484
- Cancer Research 97
Countries citing papers authored by Sun‐Mi Yun
This map shows the geographic impact of Sun‐Mi Yun'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 Sun‐Mi Yun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sun‐Mi Yun more than expected).
Fields of papers citing papers by Sun‐Mi Yun
This network shows the impact of papers produced by Sun‐Mi Yun. 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 Sun‐Mi Yun. The network helps show where Sun‐Mi Yun may publish in the future.
Co-authors
The 25 scholars most cited alongside Sun‐Mi Yun, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 86 | |
| 2 | 2011 | 84 | |
| 3 | 2013 | 76 | |
| 4 | 2021 | 64 | |
| 5 | 2010 | 58 | |
| 6 | 2017 | 54 | |
| 7 | 2020 | 46 | |
| 8 | 2011 | 43 | |
| 9 | 2013 | 32 | |
| 10 | 2013 | 28 | |
| 11 | 2017 | 28 | |
| 12 | 2010 | 27 | |
| 13 | 2013 | 27 | |
| 14 | 2018 | 24 | |
| 15 | 2022 | 23 | |
| 16 | 2007 | 20 | |
| 17 | 2019 | 19 | |
| 18 | 2014 | 15 | |
| 19 | 2009 | 11 | |
| 20 | 2020 | 11 |
About Sun‐Mi Yun
Sun‐Mi Yun is a scholar working on Molecular Biology, Insect Science, Oncology, Pathology and Forensic Medicine and Immunology, having authored 35 papers that have together received 855 indexed citations. Recurring topics across this work include Insect Utilization and Effects (7 papers), PI3K/AKT/mTOR signaling in cancer (5 papers), Genomics, phytochemicals, and oxidative stress (5 papers), Silkworms and Sericulture Research (4 papers), Cancer Mechanisms and Therapy (4 papers), Silk-based biomaterials and applications (4 papers), Natural product bioactivities and synthesis (3 papers) and Traditional Chinese Medicine Analysis (3 papers). The work is most often cited by research in Pharmacology (104 citations), Complementary and alternative medicine (77 citations), Endocrine and Autonomic Systems (62 citations), Molecular Biology (484 citations) and Cancer Research (97 citations). Sun‐Mi Yun has collaborated with scholars based in South Korea and United States. Frequent co-authors include Eun‐Hee Kim, Sung‐Hoon Kim, Soo‐Jin Jeong, Seok‐Ho Kim, Bonglee Kim, Ji Hoon Jung, Da-Young Lee, Ji‐Hyun Kim, Moon-Young Song and Eun Jung Sohn. Their work appears in journals such as Cancer Letters, Oncotarget, Journal of Functional Foods, Journal of Pineal Research and Scientific 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.