Keesiang Lim
Impact in
- Structural Biology top 10%
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- SARS-CoV-2 and COVID-19 Research
Papers in
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- Nuclear Structure and Function 9
- RNA Research and Splicing 6
- Lipid Membrane Structure and Behavior 5
- Extracellular vesicles in disease 3
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- SARS-CoV-2 and COVID-19 Research 6
- Co-authors
- Richard W. Wong (25 shared papers)Masaharu Hazawa (21 shared papers)Akiko Kobayashi (9 shared papers)Toshio Ando (10 shared papers)Carlos Marcuello (2 shared papers)John Kit Chung Tam (1 shared paper)Arkadiusz Ptak (1 shared paper)María Carmen Pallarés (1 shared paper)
In The Last Decade
Keesiang Lim
30 papers receiving 609 citations
Peers
Comparison fields: 5 of 86
- Structural Biology 26
- Infectious Diseases 109
- Molecular Biology 285
- Immunology 81
- Atomic and Molecular Physics, and Optics 126
Countries citing papers authored by Keesiang Lim
This map shows the geographic impact of Keesiang Lim'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 Keesiang Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keesiang Lim more than expected).
Fields of papers citing papers by Keesiang Lim
This network shows the impact of papers produced by Keesiang Lim. 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 Keesiang Lim. The network helps show where Keesiang Lim may publish in the future.
Co-authors
The 25 scholars most cited alongside Keesiang Lim, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 68 | |
| 2 | 2020 | 59 | |
| 3 | 2016 | 46 | |
| 4 | 2021 | 42 | |
| 5 | 2020 | 31 | |
| 6 | 2013 | 30 | |
| 7 | 2021 | 28 | |
| 8 | 2021 | 26 | |
| 9 | 2021 | 26 | |
| 10 | 2019 | 24 | |
| 11 | 2020 | 24 | |
| 12 | 2022 | 23 | |
| 13 | 2018 | 20 | |
| 14 | 2025 | 18 | |
| 15 | 2018 | 16 | |
| 16 | 2023 | 16 | |
| 17 | 2022 | 15 | |
| 18 | 2025 | 14 | |
| 19 | 2023 | 14 | |
| 20 | 2023 | 14 |
About Keesiang Lim
Keesiang Lim is a scholar working on Molecular Biology, Infectious Diseases, Atomic and Molecular Physics, and Optics, Structural Biology and Genetics, having authored 31 papers that have together received 614 indexed citations. Recurring topics across this work include Nuclear Structure and Function (9 papers), Force Microscopy Techniques and Applications (8 papers), SARS-CoV-2 and COVID-19 Research (6 papers), RNA Research and Splicing (6 papers), Lipid Membrane Structure and Behavior (5 papers), Virus-based gene therapy research (3 papers), Extracellular vesicles in disease (3 papers) and IL-33, ST2, and ILC Pathways (2 papers). The work is most often cited by research in Structural Biology (26 citations), Infectious Diseases (109 citations), Molecular Biology (285 citations), Immunology (81 citations) and Atomic and Molecular Physics, and Optics (126 citations). Keesiang Lim has collaborated with scholars based in Japan, Singapore and Spain. Frequent co-authors include Richard W. Wong, Masaharu Hazawa, Akiko Kobayashi, Toshio Ando, Carlos Marcuello, John Kit Chung Tam, Arkadiusz Ptak, María Carmen Pallarés, Anabel Lostao and Takeshi Yoshida. Their work appears in journals such as Cells, Journal of Extracellular Vesicles, ACS Nano, Nano Letters and Biochemical and Biophysical Research Communications.
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.