Sohee Kwon

414 citations
12 papers · 176 · h-index 8

Impact in

Papers in

    • Protein Structure and Dynamics 8
    • Machine Learning in Bioinformatics 4
    • RNA and protein synthesis mechanisms 3
    • Receptor Mechanisms and Signaling 2
    • Bacterial biofilms and quorum sensing 1
    • Computational Drug Discovery Methods 6

Sohee Kwon

12 papers receiving 174 citations

Peers

Sohee Kwon
Comparison fields: 5 of 62
  • Structural Biology 4
  • Computational Theory and Mathematics 43
  • Molecular Biology 122
  • Cellular and Molecular Neuroscience 16
  • Materials Chemistry 39
Replace Ida de Vries with:
Ida de Vries Netherlands
Anastasiia Gusach United States
N. Hung United States
Monica Sekharan United States
Batuhan Kav Germany
Emma K. Livingstone Australia
Tia A. Tummino United States
Kazuyoshi Ikeda Japan
Saketh Chemuru United States
Shuichi Hirose Japan
Sohee Kwon relative to Ida de Vries Netherlands Ida de Vries's profile →
Citations per field
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Ida de Vries · 1×
Citations per year

Countries citing papers authored by Sohee Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Sohee Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 202138
2 202036
3 202226
4 202117
5 202213
6 202212
7 202211
8 20228
9 20216
10 20234
11 20243
12 20232

About Sohee Kwon

Sohee Kwon is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pharmacology, Materials Chemistry and Organic Chemistry, having authored 12 papers that have together received 176 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Computational Drug Discovery Methods (6 papers), Machine Learning in Bioinformatics (4 papers), RNA and protein synthesis mechanisms (3 papers), Microbial Natural Products and Biosynthesis (2 papers), Enzyme Structure and Function (2 papers), Receptor Mechanisms and Signaling (2 papers) and Bacterial biofilms and quorum sensing (1 paper). The work is most often cited by research in Structural Biology (4 citations), Computational Theory and Mathematics (43 citations), Molecular Biology (122 citations), Cellular and Molecular Neuroscience (16 citations) and Materials Chemistry (39 citations). Sohee Kwon has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include Chaok Seok, Jonghun Won, Andriy Kryshtafovych, Hyeonuk Woo, Ji‐Hyun Lee, Gyu Rie Lee, Hahnbeom Park, Seeun Kim, Kliment Olechnovič and Dennis Della Corte. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Computational and Structural Biotechnology Journal, Journal of Computational Chemistry, Journal of Biological Chemistry and Journal of Molecular Biology.

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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