Kyuri Jo
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 9
- Gene expression and cancer classification 4
- Machine Learning in Bioinformatics 2
- Gene Regulatory Network Analysis 2
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- Computational Drug Discovery Methods 7
- Co-authors
- Sun Kim (14 shared papers)Hawk-Bin Kwon (1 shared paper)Sung Sik Choe (3 shared papers)Inuk Jung (4 shared papers)Jae Bum Kim (4 shared papers)Yong Geun Jeon (4 shared papers)Kyung Cheul Shin (3 shared papers)Hongryul Ahn (3 shared papers)
- Journals
- Bioinformatics (3 papers)Nature Communications (2 papers)Scientific Reports (2 papers)Methods (2 papers)IEEE Access (2 papers)
- Partner nations
- South KoreaPuerto RicoUnited States
In The Last Decade
Kyuri Jo
22 papers receiving 304 citations
Peers
Comparison fields: 5 of 78
- Computational Theory and Mathematics 59
- Biological Psychiatry 8
- Physiology 54
- Molecular Biology 139
- Cancer Research 26
Countries citing papers authored by Kyuri Jo
This map shows the geographic impact of Kyuri Jo'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 Kyuri Jo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyuri Jo more than expected).
Fields of papers citing papers by Kyuri Jo
This network shows the impact of papers produced by Kyuri Jo. 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 Kyuri Jo. The network helps show where Kyuri Jo may publish in the future.
Co-authors
The 25 scholars most cited alongside Kyuri Jo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 65 | |
| 2 | 2019 | 36 | |
| 3 | 2022 | 33 | |
| 4 | 2021 | 29 | |
| 5 | 2016 | 26 | |
| 6 | 2014 | 24 | |
| 7 | 2022 | 14 | |
| 8 | 2020 | 14 | |
| 9 | 2017 | 12 | |
| 10 | 2019 | 7 | |
| 11 | 2016 | 7 | |
| 12 | 2016 | 6 | |
| 13 | 2021 | 6 | |
| 14 | 2019 | 5 | |
| 15 | 2019 | 4 | |
| 16 | 2020 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2023 | 4 | |
| 19 | 2025 | 3 | |
| 20 | 2024 | 3 |
About Kyuri Jo
Kyuri Jo is a scholar working on Molecular Biology, Computational Theory and Mathematics, Epidemiology, Physiology and Genetics, having authored 25 papers that have together received 309 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (9 papers), Computational Drug Discovery Methods (7 papers), Gene expression and cancer classification (4 papers), Adipose Tissue and Metabolism (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers), Cell Image Analysis Techniques (2 papers), Machine Learning in Bioinformatics (2 papers) and Gene Regulatory Network Analysis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (59 citations), Biological Psychiatry (8 citations), Physiology (54 citations), Molecular Biology (139 citations) and Cancer Research (26 citations). Kyuri Jo has collaborated with scholars based in South Korea, Puerto Rico and United States. Frequent co-authors include Sun Kim, Hawk-Bin Kwon, Sung Sik Choe, Inuk Jung, Jae Bum Kim, Yong Geun Jeon, Kyung Cheul Shin, Hongryul Ahn, Hyejin Kang and Jong In Kim. Their work appears in journals such as Bioinformatics, Nature Communications, Scientific Reports, Methods and IEEE Access.
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.