Hee Gu Lee
- Immunology top 5%
- Immune Cell Function and Interaction 12
- Immunotherapy and Immune Responses 11
- Cancer Research top 5%
- Molecular Biology top 5%
- Mechanisms of cancer metastasis 8
- Wnt/β-catenin signaling in development and cancer 7
- Protein Kinase Regulation and GTPase Signaling 7
- Cell death mechanisms and regulation 7
- Oncology top 5%
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- Autophagy in Disease and Therapy 11
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- Endoplasmic Reticulum Stress and Disease 7
Hee Gu Lee
138 papers receiving 3.7k citations
Peers
Comparison fields: 5 of 122
- Immunology 854
- Cancer Research 522
- Molecular Biology 2.0k
- Oncology 729
- Pathology and Forensic Medicine 349
Countries citing papers authored by Hee Gu Lee
This map shows the geographic impact of Hee Gu 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 Hee Gu Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hee Gu Lee more than expected).
Fields of papers citing papers by Hee Gu Lee
This network shows the impact of papers produced by Hee Gu 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 Hee Gu Lee. The network helps show where Hee Gu Lee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hee Gu 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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 7 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 13 | |
| 6 | 2022 | 10 | |
| 7 | 2021 | 33 | |
| 8 | 2020 | 14 | |
| 9 | 2020 | 11 | |
| 10 | 2020 | 52 | |
| 11 | 2019 | 16 | |
| 12 | 2019 | 30 | |
| 13 | 2019 | 51 | |
| 14 | 2016 | 59 | |
| 15 | 2008 | 109 | |
| 16 | Cancer biomarkers in 'omics age | 2008 | 3 |
| 17 | Effects of 3,5-di-O-Caffeoylquinic acid from Artemisia scoparia waldstein et kitamura on the function of HPV 16 oncoproteins | 2004 | 1 |
| 18 | Analysis of the stability of HLA-A2 molecules expressed on the cell surface | 1996 | 2 |
| 19 | Production of viruslike particles from human papillomavirus type 16 capsid protein L1 expressed in insect cells | 1995 | 2 |
| 20 | Purification and characterization of human complement component C3 | 1990 | 1 |
About Hee Gu Lee
Hee Gu Lee is a scholar working on Immunology, Cell Biology, Molecular Biology, Aging and Cancer Research, having authored 140 papers that have together received 3.8k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (12 papers), Immunotherapy and Immune Responses (11 papers), Autophagy in Disease and Therapy (11 papers), Mechanisms of cancer metastasis (8 papers), Endoplasmic Reticulum Stress and Disease (7 papers), Wnt/β-catenin signaling in development and cancer (7 papers), Protein Kinase Regulation and GTPase Signaling (7 papers) and Cell death mechanisms and regulation (7 papers). The work is most often cited by research in Immunology (854 citations), Cancer Research (522 citations), Molecular Biology (2.0k citations), Oncology (729 citations) and Pathology and Forensic Medicine (349 citations). Hee Gu Lee has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include Jong‐Seok Lim, Suk Ran Yoon, Eun Young Song, Jae Wha Kim, Hee Jun Cho, Inpyo Choi, Haiyoung Jung, Jong‐Tae Kim, Young‐Jun Park and Seon‐Jin Lee. Their work appears in journals such as Oncotarget, International Journal of Molecular Sciences, Clinica Chimica Acta, Cancers and Cancer 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.