Jaejoon Won
Impact in
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- Neuroscience and Neuropharmacology Research
- Cognitive Neuroscience top 5%
- Memory and Neural Mechanisms
- Neural dynamics and brain function
Papers in
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- Cancer-related gene regulation 3
- Wnt/β-catenin signaling in development and cancer 3
- Ubiquitin and proteasome pathways 2
- DNA and Nucleic Acid Chemistry 2
- RNA Interference and Gene Delivery 2
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- Telomeres, Telomerase, and Senescence 4
- Nitric Oxide and Endothelin Effects 3
- Co-authors
- Tae Kook Kim (6 shared papers)Jeongbin Yim (5 shared papers)Alcino J. Silva (2 shared papers)Mikael C. Guzman-Karlsson (1 shared paper)Miou Zhou (1 shared paper)Panayiota Poirazi (1 shared paper)Rachael L. Neve (1 shared paper)Thomas Rogerson (1 shared paper)
- Journals
- Molecules and Cells (2 papers)Gene (1 paper)Neurobiology of Learning and Memory (1 paper)Molecular Pharmacology (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Jaejoon Won
12 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 82
- Cellular and Molecular Neuroscience 366
- Cognitive Neuroscience 302
- Behavioral Neuroscience 37
- Aging 18
- Neurology 75
Countries citing papers authored by Jaejoon Won
This map shows the geographic impact of Jaejoon Won'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 Jaejoon Won with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaejoon Won more than expected).
Fields of papers citing papers by Jaejoon Won
This network shows the impact of papers produced by Jaejoon Won. 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 Jaejoon Won. The network helps show where Jaejoon Won may publish in the future.
Co-authors
The 21 scholars most cited alongside Jaejoon Won, 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 | 2009 | 413 | |
| 2 | 2002 | 167 | |
| 3 | 2006 | 98 | |
| 4 | 2006 | 96 | |
| 5 | 2007 | 70 | |
| 6 | 2002 | 57 | |
| 7 | 2005 | 57 | |
| 8 | 2004 | 40 | |
| 9 | 2000 | 16 | |
| 10 | 1998 | 13 | |
| 11 | 2006 | 4 | |
| 12 | 2000 | 1 |
About Jaejoon Won
Jaejoon Won is a scholar working on Molecular Biology, Physiology, Cellular and Molecular Neuroscience, Social Psychology and Behavioral Neuroscience, having authored 12 papers that have together received 1.0k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (4 papers), Nitric Oxide and Endothelin Effects (3 papers), Cancer-related gene regulation (3 papers), Wnt/β-catenin signaling in development and cancer (3 papers), Ubiquitin and proteasome pathways (2 papers), DNA and Nucleic Acid Chemistry (2 papers), Neuroscience and Neuropharmacology Research (2 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (366 citations), Cognitive Neuroscience (302 citations), Behavioral Neuroscience (37 citations), Aging (18 citations) and Neurology (75 citations). Jaejoon Won has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Tae Kook Kim, Jeongbin Yim, Alcino J. Silva, Mikael C. Guzman-Karlsson, Miou Zhou, Panayiota Poirazi, Rachael L. Neve, Thomas Rogerson, Yu Zhou and Sangtaek Oh. Their work appears in journals such as Molecules and Cells, Gene, Neurobiology of Learning and Memory, Molecular Pharmacology and Proceedings of the National Academy of Sciences.
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.