Hyunsuk Shim
- Molecular Biology top 2%
- Cancer Research top 0.5%
- Oncology top 1%
- Immunology top 2%
- Radiology, Nuclear Medicine and Imaging top 1%
- Co-authors
- Zhongxing LiangChi V. DangYounghyoun YoonBrian C. LewisAizhi ZhuChristine DoldeRiccardo Dalla‐FaveraRichard A. Jungmann
- Topics
- Medical Imaging Techniques and Applications (36 papers)Glioma Diagnosis and Treatment (32 papers)Chemokine receptors and signaling (25 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of Clinical Oncology
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Hyunsuk Shim
124 papers receiving 6.9k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Molecular Biology 3.8k
- Cancer Research 2.2k
- Oncology 2.1k
- Immunology 1.2k
- Radiology, Nuclear Medicine and Imaging 1.0k
Countries citing papers authored by Hyunsuk Shim
This map shows the geographic impact of Hyunsuk Shim'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 Hyunsuk Shim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyunsuk Shim more than expected).
Fields of papers citing papers by Hyunsuk Shim
This network shows the impact of papers produced by Hyunsuk Shim. 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 Hyunsuk Shim. The network helps show where Hyunsuk Shim may publish in the future.
Co-authorship network of co-authors of Hyunsuk Shim
This figure shows the co-authorship network connecting the top 25 collaborators of Hyunsuk Shim. A scholar is included among the top collaborators of Hyunsuk Shim based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hyunsuk Shim. Hyunsuk Shim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 9 | |
| 7 | 8 | |
| 8 | 31 | |
| 9 | 26 | |
| 10 | High-resolution CT Image Retrieval Using Sparse Convolutional Neural Network | 1 |
| 11 | 40 | |
| 12 | 12 | |
| 13 | 20 | |
| 14 | 19 | |
| 15 | 13 | |
| 16 | 56 | |
| 17 | 98 | |
| 18 | MSX-122, an orally available small molecule targeting CXCR4, inhibits primary tumor growth in an orthotopic mouse model of lung cancer and improves the effect of paclitaxel | 3 |
| 19 | 17 | |
| 20 | 100 |
About Hyunsuk Shim
Hyunsuk Shim is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging and Oncology, having authored 126 papers that have together received 7.0k indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (36 papers), Glioma Diagnosis and Treatment (32 papers) and Chemokine receptors and signaling (25 papers). The work is most often cited by research in Cancer Research (2.2k citations), Oncology (2.1k citations) and Molecular Biology (3.8k citations). Hyunsuk Shim has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Zhongxing Liang, Chi V. Dang, Younghyoun Yoon, Brian C. Lewis, Aizhi Zhu, Christine Dolde, Riccardo Dalla‐Favera, Richard A. Jungmann, Daniel Lee and C. Chris Yun. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.
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.