Jonghwan Choi
Impact in
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- Computational Drug Discovery Methods
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- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- Gene expression and cancer classification
- Machine Learning in Bioinformatics
- Receptor Mechanisms and Signaling
Papers in
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- Gene expression and cancer classification 3
- Bioinformatics and Genomic Networks 3
- Protein Structure and Dynamics 2
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- Computational Drug Discovery Methods 7
- Co-authors
- Jaegyoon Ahn (11 shared papers)Sanghyun Park (10 shared papers)Youngmi Yoon (1 shared paper)Chihyun Park (3 shared papers)Seung Kew Yoon (1 shared paper)Jinho Kim (1 shared paper)Sung Woo Cho (1 shared paper)Dong Jun Park (1 shared paper)
- Journals
- Scientific Reports (3 papers)BMC Bioinformatics (2 papers)IEEE Access (2 papers)Applied Intelligence (1 paper)Engineering Applications of Artificial Intelligence (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Jonghwan Choi
16 papers receiving 290 citations
Peers
Comparison fields: 5 of 66
- Computational Theory and Mathematics 121
- Molecular Biology 173
- Hepatology 15
- Biophysics 9
- Pharmacology 12
Countries citing papers authored by Jonghwan Choi
This map shows the geographic impact of Jonghwan Choi'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 Jonghwan Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonghwan Choi more than expected).
Fields of papers citing papers by Jonghwan Choi
This network shows the impact of papers produced by Jonghwan Choi. 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 Jonghwan Choi. The network helps show where Jonghwan Choi may publish in the future.
Co-authors
The 22 scholars most cited alongside Jonghwan Choi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 73 | |
| 2 | 2020 | 50 | |
| 3 | 2017 | 30 | |
| 4 | 2022 | 27 | |
| 5 | 2018 | 24 | |
| 6 | 2018 | 18 | |
| 7 | 2021 | 14 | |
| 8 | 2021 | 12 | |
| 9 | 2022 | 8 | |
| 10 | 2023 | 7 | |
| 11 | 2023 | 6 | |
| 12 | 2023 | 6 | |
| 13 | 2023 | 5 | |
| 14 | 2025 | 5 | |
| 15 | 2023 | 4 | |
| 16 | 2022 | 1 | |
| 17 | 2022 | 0 | |
| 18 | 2025 | 0 | |
| 19 | 2024 | 0 |
About Jonghwan Choi
Jonghwan Choi is a scholar working on Molecular Biology, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Networks and Communications, having authored 19 papers that have together received 290 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Gene expression and cancer classification (3 papers), Bioinformatics and Genomic Networks (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Cancer Genomics and Diagnostics (2 papers), Protein Structure and Dynamics (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Computational Theory and Mathematics (121 citations), Molecular Biology (173 citations), Hepatology (15 citations), Biophysics (9 citations) and Pharmacology (12 citations). Jonghwan Choi has collaborated with scholars based in South Korea and United States. Frequent co-authors include Jaegyoon Ahn, Sanghyun Park, Youngmi Yoon, Chihyun Park, Seung Kew Yoon, Jinho Kim, Sung Woo Cho, Dong Jun Park, Jong Young Choi and Jae Kwang Kim. Their work appears in journals such as Scientific Reports, BMC Bioinformatics, IEEE Access, Applied Intelligence and Engineering Applications of Artificial Intelligence.
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.