Sung Eun Kwon
Impact in
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- Neuroscience and Neuropharmacology Research
- Photoreceptor and optogenetics research
- Neuroscience and Neural Engineering
- Neurobiology and Insect Physiology Research
- Cell Biology top 5%
- Cellular transport and secretion
Papers in
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- Neuroscience and Neural Engineering 4
- Neuroscience and Neuropharmacology Research 4
- Photoreceptor and optogenetics research 3
- Neurobiology and Insect Physiology Research 2
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- Neural dynamics and brain function 7
- Co-authors
- Edwin R. Chapman (5 shared papers)Daniel H. O’Connor (6 shared papers)Hongdian Yang (2 shared papers)Jon D. Gaffaney (2 shared papers)Jun Yao (2 shared papers)Genki Minamisawa (2 shared papers)Kyle S. Severson (1 shared paper)F. Mark Dunning (1 shared paper)
- Journals
- Nature Neuroscience (3 papers)Neuroscience (2 papers)Neuron (1 paper)eLife (1 paper)Cell (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Sung Eun Kwon
17 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 102
- Cellular and Molecular Neuroscience 629
- Cell Biology 390
- Cognitive Neuroscience 356
- Developmental Neuroscience 53
- Physiology 48
Countries citing papers authored by Sung Eun Kwon
This map shows the geographic impact of Sung Eun Kwon'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 Sung Eun Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sung Eun Kwon more than expected).
Fields of papers citing papers by Sung Eun Kwon
This network shows the impact of papers produced by Sung Eun Kwon. 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 Sung Eun Kwon. The network helps show where Sung Eun Kwon may publish in the future.
Co-authors
The 25 scholars most cited alongside Sung Eun Kwon, 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 | 2011 | 387 | |
| 2 | 2011 | 168 | |
| 3 | 2016 | 142 | |
| 4 | 2015 | 133 | |
| 5 | 2011 | 110 | |
| 6 | 2014 | 93 | |
| 7 | 2012 | 43 | |
| 8 | 2018 | 40 | |
| 9 | 2015 | 31 | |
| 10 | 2017 | 17 | |
| 11 | 2020 | 16 | |
| 12 | 2021 | 9 | |
| 13 | 2015 | 8 | |
| 14 | 2023 | 5 | |
| 15 | 2022 | 4 | |
| 16 | 2018 | 3 | |
| 17 | 2015 | 2 | |
| 18 | 2025 | 0 |
About Sung Eun Kwon
Sung Eun Kwon is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Cell Biology, Physiology and Molecular Biology, having authored 18 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (7 papers), Cellular transport and secretion (6 papers), Lipid Membrane Structure and Behavior (4 papers), Neuroscience and Neural Engineering (4 papers), Neuroscience and Neuropharmacology Research (4 papers), Photoreceptor and optogenetics research (3 papers), Neurobiology and Insect Physiology Research (2 papers) and Calcium signaling and nucleotide metabolism (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (629 citations), Cell Biology (390 citations), Cognitive Neuroscience (356 citations), Developmental Neuroscience (53 citations) and Physiology (48 citations). Sung Eun Kwon has collaborated with scholars based in United States and South Korea. Frequent co-authors include Edwin R. Chapman, Daniel H. O’Connor, Hongdian Yang, Jon D. Gaffaney, Jun Yao, Genki Minamisawa, Kyle S. Severson, F. Mark Dunning, Huisheng Liu and Hua Juan Bai. Their work appears in journals such as Nature Neuroscience, Neuroscience, Neuron, eLife and Cell.
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.