Misu Lee
Impact in
- Cancer Research top 10%
- Cancer, Hypoxia, and Metabolism
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- Pituitary Gland Disorders and Treatments
Papers in
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- Protein purification and stability 5
- Glycosylation and Glycoproteins Research 5
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- Cancer, Hypoxia, and Metabolism 17
- Cancer, Lipids, and Metabolism 5
- Co-authors
- Natalia S. Pellegata (14 shared papers)Mijin Yun (15 shared papers)Jae‐Chul Pyun (28 shared papers)Federico Roncaroli (4 shared papers)In-San Kim (1 shared paper)Kwangmeyung Kim (1 shared paper)Baik Lin Seong (1 shared paper)Ick Chan Kwon (1 shared paper)
- Journals
- Bioconjugate Chemistry (3 papers)Cancers (3 papers)Biosensors and Bioelectronics (3 papers)Enzyme and Microbial Technology (3 papers)ACS Pharmacology & Translational Science (3 papers)
- Partner nations
- South KoreaGermanyItaly
In The Last Decade
Misu Lee
54 papers receiving 957 citations
Peers
Comparison fields: 5 of 86
- Cancer Research 194
- Endocrinology, Diabetes and Metabolism 164
- Oncology 177
- Genetics 65
- Molecular Biology 417
Countries citing papers authored by Misu Lee
This map shows the geographic impact of Misu Lee'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 Misu Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Misu Lee more than expected).
Fields of papers citing papers by Misu Lee
This network shows the impact of papers produced by Misu Lee. 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 Misu Lee. The network helps show where Misu Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Misu Lee, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 194 | |
| 2 | 2010 | 72 | |
| 3 | 2014 | 58 | |
| 4 | 2015 | 48 | |
| 5 | 2011 | 36 | |
| 6 | 2018 | 35 | |
| 7 | 2016 | 32 | |
| 8 | 2013 | 31 | |
| 9 | 2010 | 30 | |
| 10 | 2017 | 30 | |
| 11 | 2017 | 26 | |
| 12 | 2020 | 24 | |
| 13 | 2020 | 24 | |
| 14 | 2022 | 23 | |
| 15 | 2021 | 23 | |
| 16 | 2013 | 18 | |
| 17 | 2022 | 17 | |
| 18 | 2021 | 17 | |
| 19 | 2024 | 14 | |
| 20 | 2012 | 14 |
About Misu Lee
Misu Lee is a scholar working on Molecular Biology, Cancer Research, Radiology, Nuclear Medicine and Imaging, Oncology and Epidemiology, having authored 59 papers that have together received 961 indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (17 papers), Monoclonal and Polyclonal Antibodies Research (14 papers), Neuroendocrine Tumor Research Advances (9 papers), Pituitary Gland Disorders and Treatments (7 papers), SARS-CoV-2 and COVID-19 Research (7 papers), Cancer, Lipids, and Metabolism (5 papers), Protein purification and stability (5 papers) and Glycosylation and Glycoproteins Research (5 papers). The work is most often cited by research in Cancer Research (194 citations), Endocrinology, Diabetes and Metabolism (164 citations), Oncology (177 citations), Genetics (65 citations) and Molecular Biology (417 citations). Misu Lee has collaborated with scholars based in South Korea, Germany and Italy. Frequent co-authors include Natalia S. Pellegata, Mijin Yun, Jae‐Chul Pyun, Federico Roncaroli, In-San Kim, Kwangmeyung Kim, Baik Lin Seong, Ick Chan Kwon, Hesson Chung and Hyungkyu Park. Their work appears in journals such as Bioconjugate Chemistry, Cancers, Biosensors and Bioelectronics, Enzyme and Microbial Technology and ACS Pharmacology & Translational Science.
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.