Kyungsook Han
- Molecular Biology top 5%
- Computational Theory and Mathematics top 5%
- Cancer Research
- Artificial Intelligence top 10%
- Ecology
- Co-authors
- De-Shuang HuangByungkyu ParkWook LeeSeong‐Wook LeeJunfeng XiaGuangyu CuiAsoke K. NandiEuna Jeong
- Topics
- RNA and protein synthesis mechanisms (36 papers)Bioinformatics and Genomic Networks (28 papers)Machine Learning in Bioinformatics (21 papers)
- Partner nations
- South KoreaChinaUnited Kingdom
In The Last Decade
Kyungsook Han
95 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 138
- Molecular Biology 1.5k
- Computational Theory and Mathematics 177
- Cancer Research 144
- Artificial Intelligence 130
- Ecology 97
Countries citing papers authored by Kyungsook Han
This map shows the geographic impact of Kyungsook Han'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 Kyungsook Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyungsook Han more than expected).
Fields of papers citing papers by Kyungsook Han
This network shows the impact of papers produced by Kyungsook Han. 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 Kyungsook Han. The network helps show where Kyungsook Han may publish in the future.
Co-authorship network of co-authors of Kyungsook Han
This figure shows the co-authorship network connecting the top 25 collaborators of Kyungsook Han. A scholar is included among the top collaborators of Kyungsook Han 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 Kyungsook Han. Kyungsook Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 11 | |
| 5 | 9 | |
| 6 | 9 | |
| 7 | Intelligent Computing in Bioinformatics: 10th International Conference, ICIC 2014, Taiyuan, China, August 3-6, 2014, Proceedings | 3 |
| 8 | 0 | |
| 9 | 82 | |
| 10 | 20 | |
| 11 | 40 | |
| 12 | Bio-Inspired Computing and Applications: 7th International Conference on Intelligent Computing | 1 |
| 13 | Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications | 1 |
| 14 | 10 | |
| 15 | 6 | |
| 16 | 26 | |
| 17 | 25 | |
| 18 | 2 | |
| 19 | 1 | |
| 20 | 30 |
About Kyungsook Han
Kyungsook Han is a scholar working on Molecular Biology, Cancer Research and Hepatology, having authored 100 papers that have together received 1.8k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (36 papers), Bioinformatics and Genomic Networks (28 papers) and Machine Learning in Bioinformatics (21 papers). The work is most often cited by research in Molecular Biology (1.5k citations), Computational Theory and Mathematics (177 citations) and Cancer Research (144 citations). Kyungsook Han has collaborated with scholars based in South Korea, China and United Kingdom. Frequent co-authors include De-Shuang Huang, Byungkyu Park, Wook Lee, Seong‐Wook Lee, Junfeng Xia, Guangyu Cui, Asoke K. Nandi, Euna Jeong, Chao Fang and Youhua Zhang. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and FEBS Letters.
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.