Sungwon Han
Impact in
- Biochemistry top 2%
- Lipid metabolism and biosynthesis
- Cell Biology top 10%
- Endoplasmic Reticulum Stress and Disease
Papers in
-
- Sphingolipid Metabolism and Signaling 3
- Lipid Membrane Structure and Behavior 3
-
- Lipid metabolism and biosynthesis 4
- Amino Acid Enzymes and Metabolism 2
- Co-authors
- Joel Goodman (3 shared papers)Christopher Auger (7 shared papers)Vasu D. Appanna (7 shared papers)Derk D. Binns (2 shared papers)Qiang Gao (1 shared paper)Joseph Lemire (2 shared papers)Sean C. Thomas (2 shared papers)Gerardo Ulíbarri (1 shared paper)
- Journals
- Journal of Biological Chemistry (2 papers)Molecular Cell (1 paper)Cell Reports (1 paper)Molecular Biology of the Cell (1 paper)Biotechnology Advances (1 paper)
- Partner nations
- United StatesCanadaSouth Korea
In The Last Decade
Sungwon Han
23 papers receiving 646 citations
Peers
Comparison fields: 5 of 93
- Biochemistry 252
- Cell Biology 152
- Molecular Biology 401
- Pollution 34
- Health, Toxicology and Mutagenesis 38
Countries citing papers authored by Sungwon Han
This map shows the geographic impact of Sungwon 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 Sungwon Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungwon Han more than expected).
Fields of papers citing papers by Sungwon Han
This network shows the impact of papers produced by Sungwon 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 Sungwon Han. The network helps show where Sungwon Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Sungwon Han, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 139 | |
| 2 | 2011 | 86 | |
| 3 | 2013 | 67 | |
| 4 | 2015 | 59 | |
| 5 | 2012 | 58 | |
| 6 | 2013 | 47 | |
| 7 | 2016 | 37 | |
| 8 | 2019 | 20 | |
| 9 | 2009 | 18 | |
| 10 | 2012 | 15 | |
| 11 | 2013 | 14 | |
| 12 | 2002 | 13 | |
| 13 | 2012 | 13 | |
| 14 | 2012 | 12 | |
| 15 | 2019 | 11 | |
| 16 | 2011 | 11 | |
| 17 | 2021 | 10 | |
| 18 | 2004 | 9 | |
| 19 | 2016 | 4 | |
| 20 | 2023 | 3 |
About Sungwon Han
Sungwon Han is a scholar working on Molecular Biology, Biochemistry, Plant Science, Electrical and Electronic Engineering and Surgery, having authored 23 papers that have together received 653 indexed citations. Recurring topics across this work include Lipid metabolism and biosynthesis (4 papers), Aluminum toxicity and tolerance in plants and animals (3 papers), Sphingolipid Metabolism and Signaling (3 papers), Lipid Membrane Structure and Behavior (3 papers), Amino Acid Enzymes and Metabolism (2 papers), Conducting polymers and applications (2 papers), Advanced Sensor and Energy Harvesting Materials (2 papers) and Trace Elements in Health (2 papers). The work is most often cited by research in Biochemistry (252 citations), Cell Biology (152 citations), Molecular Biology (401 citations), Pollution (34 citations) and Health, Toxicology and Mutagenesis (38 citations). Sungwon Han has collaborated with scholars based in United States, Canada and South Korea. Frequent co-authors include Joel Goodman, Christopher Auger, Vasu D. Appanna, Derk D. Binns, Qiang Gao, Joseph Lemire, Sean C. Thomas, Gerardo Ulíbarri, Jin Ye and Sean C. Thomas. Their work appears in journals such as Journal of Biological Chemistry, Molecular Cell, Cell Reports, Molecular Biology of the Cell and Biotechnology Advances.
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.