Young V. Kwon
Impact in
- Aging top 5%
- Sensory Systems top 2%
- Ion Channels and Receptors
Papers in
-
- Bioinformatics and Genomic Networks 4
- Muscle Physiology and Disorders 4
- Protein Structure and Dynamics 2
-
- Neurobiology and Insect Physiology Research 11
- Co-authors
- Craig Montell (7 shared papers)Norbert Perrimon (8 shared papers)Thomas Hofmann (1 shared paper)Wei L. Shen (2 shared papers)Yanhui Hu (2 shared papers)Arunachalam Vinayagam (3 shared papers)Xiaoyue Wang (1 shared paper)John M. Asara (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)Current Biology (2 papers)Journal of Ethnopharmacology (2 papers)Science (2 papers)eLife (2 papers)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Young V. Kwon
30 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 115
- Aging 89
- Sensory Systems 244
- Cellular and Molecular Neuroscience 639
- Endocrine and Autonomic Systems 174
- Insect Science 205
Countries citing papers authored by Young V. Kwon
This map shows the geographic impact of Young V. 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 Young V. Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young V. Kwon more than expected).
Fields of papers citing papers by Young V. Kwon
This network shows the impact of papers produced by Young V. 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 Young V. Kwon. The network helps show where Young V. Kwon may publish in the future.
Co-authors
The 25 scholars most cited alongside Young V. 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
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 191 | |
| 2 | 2011 | 184 | |
| 3 | 2016 | 178 | |
| 4 | 2007 | 176 | |
| 5 | 2010 | 158 | |
| 6 | 2013 | 150 | |
| 7 | 2008 | 143 | |
| 8 | 1998 | 91 | |
| 9 | 2010 | 88 | |
| 10 | 2011 | 73 | |
| 11 | 2011 | 40 | |
| 12 | 2016 | 28 | |
| 13 | 2006 | 28 | |
| 14 | 2020 | 23 | |
| 15 | 2021 | 23 | |
| 16 | 2021 | 22 | |
| 17 | 2000 | 14 | |
| 18 | 2019 | 11 | |
| 19 | 2023 | 7 | |
| 20 | 2013 | 7 |
About Young V. Kwon
Young V. Kwon is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Immunology, Cell Biology and Sensory Systems, having authored 33 papers that have together received 1.7k indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (11 papers), Hippo pathway signaling and YAP/TAZ (5 papers), Invertebrate Immune Response Mechanisms (4 papers), Bioinformatics and Genomic Networks (4 papers), Ion Channels and Receptors (4 papers), Muscle Physiology and Disorders (4 papers), Plant and animal studies (3 papers) and Protein Structure and Dynamics (2 papers). The work is most often cited by research in Aging (89 citations), Sensory Systems (244 citations), Cellular and Molecular Neuroscience (639 citations), Endocrine and Autonomic Systems (174 citations) and Insect Science (205 citations). Young V. Kwon has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Craig Montell, Norbert Perrimon, Thomas Hofmann, Wei L. Shen, Yanhui Hu, Arunachalam Vinayagam, Xiaoyue Wang, John M. Asara, Ilia A. Droujinine and Wei Song. Their work appears in journals such as Proceedings of the National Academy of Sciences, Current Biology, Journal of Ethnopharmacology, Science and eLife.
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.