Jun Won Park

714 citations
29 papers · 245 · h-index 11

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Cancer Cells and Metastasis

Papers in

Jun Won Park

29 papers receiving 244 citations

Peers

Jun Won Park
Comparison fields: 5 of 65
  • Cancer Research 34
  • Oncology 59
  • Immunology 40
  • Molecular Biology 129
  • Infectious Diseases 29
Replace Christina Kalderén with:
Christina Kalderén Sweden
Susann Herzog Germany
Robert J. Nichols United States
Kelsey E. Huntington United States
Da Chen China
Janet C. Reid Australia
Sahar Khorasani Iran
Susan Wittig Germany
Andrew Single New Zealand
Jing-Yuan Chooi Singapore
Jun Won Park relative to Christina Kalderén Sweden Christina Kalderén's profile →
Citations per field
00.5×1.5×1.8×
Christina Kalderén · 1×
Citations per year

Countries citing papers authored by Jun Won Park

Since Specialization
Citations

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

Fields of papers citing papers by Jun Won Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201432
2 201420
3 202118
4 201417
5 202315
6 201515
7 202215
8 201012
9 202211
10 202311
11 201110
12 202110
13 20239
14 20229
15 20236
16 20146
17 20225
18 20164
19 20213
20 20173

About Jun Won Park

Jun Won Park is a scholar working on Molecular Biology, Infectious Diseases, Oncology, Surgery and Pathology and Forensic Medicine, having authored 29 papers that have together received 245 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (8 papers), Cancer-related gene regulation (6 papers), Long-Term Effects of COVID-19 (3 papers), Cancer Research and Treatments (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), MicroRNA in disease regulation (3 papers), COVID-19 Clinical Research Studies (3 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Cancer Research (34 citations), Oncology (59 citations), Immunology (40 citations), Molecular Biology (129 citations) and Infectious Diseases (29 citations). Jun Won Park has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include Hark Kyun Kim, Je Kyung Seong, Dae-Yong Kim, Dae‐Yong Kim, Soo Young Cho, Sang‐Ho Woo, Hyo‐Jung Kwon, Beom K. Choi, Jeffrey E. Green and Byoung S. Kwon. Their work appears in journals such as Molecular Carcinogenesis, Scientific Reports, Pathology International, Journal of Clinical Oncology and PLoS ONE.

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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