Sunyoung Kwon

26 papers receiving 525 citations

Peers

Sunyoung Kwon
Comparison fields: 5 of 120
  • Computational Theory and Mathematics 155
  • Immunology and Allergy 35
  • Dermatology 51
  • Cancer Research 71
  • Molecular Biology 245
Replace Yonghong Tang with:
Yonghong Tang China
Ngan Nguyen Taiwan
Petr Hájek Czechia
Xuejiao Wang China
Nitish K. Mishra United States
Cláudia Barbosa Ladeira de Campos Brazil
Emmett Sprecher United States
Enrico Giampieri Italy
Jens Eckstein Switzerland
Jeffrey A. Cramer United States
Sunyoung Kwon relative to Yonghong Tang China Yonghong Tang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sunyoung Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Sunyoung Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019156
2 201874
3 201855
4 201449
5 202146
6 201735
7 201322
8 202315
9 202213
10 201812
11 202410
12 20139
13 20208
14
Clinical and Prognostic Value of Human Mammary Tumor Virus in Korean Patients with Breast Carcinoma.
20196
15 20145
16 20185
17
METTL3 regulates alternative splicing of cell cycle-related genes via crosstalk between mRNA m6A modifications and splicing factors.
20234
18 20194
19 20144
20 20203

About Sunyoung Kwon

Sunyoung Kwon is a scholar working on Molecular Biology, Artificial Intelligence, Cancer Research, Oncology and Computational Theory and Mathematics, having authored 30 papers that have together received 544 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Machine Learning in Materials Science (4 papers), Genomics and Phylogenetic Studies (3 papers), Breast Cancer Treatment Studies (3 papers), Advanced Graph Neural Networks (3 papers), Analytical Chemistry and Chromatography (2 papers), HER2/EGFR in Cancer Research (2 papers) and Diverse Approaches in Healthcare and Education Studies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (155 citations), Immunology and Allergy (35 citations), Dermatology (51 citations), Cancer Research (71 citations) and Molecular Biology (245 citations). Sunyoung Kwon has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Sungroh Yoon, Byunghan Lee, Ho Bae, Jaekoo Lee, Jung Won Shin, Kyungho Park, Chang‐Hun Huh, Jaehyuk Choi, Minquan Du and Jihyoung Cho. Their work appears in journals such as IEEE Access, BMC Bioinformatics, Bioinformatics, Clinical Cancer Research and International Journal of Medical Sciences.

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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