Sun‐Mi Park

2.1k citations
90 papers · 1.4k · h-index 23

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Oncology top 10%
    • Cancer-related Molecular Pathways
    • Cancer Cells and Metastasis

Papers in

Sun‐Mi Park

83 papers receiving 1.4k citations

Peers

Sun‐Mi Park
Comparison fields: 5 of 119
  • Cancer Research 281
  • Oncology 290
  • Endocrinology, Diabetes and Metabolism 166
  • Molecular Biology 712
  • Hematology 83
Replace Huan Deng with:
Huan Deng China
Armel Hervé Nwabo Kamdje Cameroon
Li‐Shun Wang China
Zhiqiang Ning China
Karol L. Thompson United States
Ekaterina Nevedomskaya Netherlands
Raj K. Tiwari United States
Guowei Zuo China
Xiaodong Xie China
Sun‐Mi Park relative to Huan Deng China Huan Deng's profile →
Citations per field
00.5×2.8×
Huan Deng · 1×
Citations per year

Countries citing papers authored by Sun‐Mi Park

Since Specialization
Citations

This map shows the geographic impact of Sun‐Mi 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 Sun‐Mi Park 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 Park more than expected).

Fields of papers citing papers by Sun‐Mi Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sun‐Mi 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 Sun‐Mi Park. The network helps show where Sun‐Mi Park may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011138
2 2014112
3 201867
4 201654
5 202053
6 201850
7 201442
8 201441
9 202038
10 201138
11 201937
12 201734
13 201234
14 200832
15 201431
16 202129
17 200829
18 201226
19 202325
20 201824

About Sun‐Mi Park

Sun‐Mi Park is a scholar working on Molecular Biology, Artificial Intelligence, Information Systems, Oncology and Endocrinology, Diabetes and Metabolism, having authored 90 papers that have together received 1.4k indexed citations. Recurring topics across this work include Coding theory and cryptography (15 papers), Cryptography and Residue Arithmetic (12 papers), Finite Group Theory Research (6 papers), RNA Research and Splicing (6 papers), Protein Degradation and Inhibitors (6 papers), Thyroid Cancer Diagnosis and Treatment (6 papers), Ubiquitin and proteasome pathways (5 papers) and Cancer Cells and Metastasis (5 papers). The work is most often cited by research in Cancer Research (281 citations), Oncology (290 citations), Endocrinology, Diabetes and Metabolism (166 citations), Molecular Biology (712 citations) and Hematology (83 citations). Sun‐Mi Park has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Sheue-yann Cheng, Michael G. Kharas, Xuguang Zhu, Marcus E. Peter, Ernst Lengyel, Mark C. Willingham, Benjamin Boyerinas, Christina S. Leslie, Youjia Hua and Andrea E. Murmann. Their work appears in journals such as IEEE Transactions on Computers, Endocrine Related Cancer, Oncotarget, Cancers and American Journal of Infection Control.

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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