Chan Hyun Na
- Cell Biology top 5%
- Molecular Biology top 10%
- Ubiquitin and proteasome pathways 6
- Glycosylation and Glycoproteins Research 5
- Metabolomics and Mass Spectrometry Studies 5
- Neurology top 5%
- Parkinson's Disease Mechanisms and Treatments 8
- Neurological diseases and metabolism 5
- Neurology top 10%
- Parkinson's Disease Mechanisms and Treatments 8
- Neurological diseases and metabolism 5
- Aging top 10%
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- Alzheimer's disease research and treatments 14
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- Advanced Proteomics Techniques and Applications 9
- Mass Spectrometry Techniques and Applications 5
- Co-authors
- Akhilesh PandeyJunmin PengSantosh RenuseAnil K. MadugunduRaja Sekhar NirujogiYura JangRichard L. HuganirMin‐Sik Kim
- Journals
- Proceedings of the National Academy of Sciences (3 papers)Journal of Biological Chemistry (3 papers)Nature Communications (4 papers)
- Partner nations
- United StatesSouth KoreaIndia
In The Last Decade
Chan Hyun Na
65 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 100
- Cell Biology 251
- Molecular Biology 995
- Neurology 207
- Neurology 102
- Aging 19
Countries citing papers authored by Chan Hyun Na
This map shows the geographic impact of Chan Hyun Na'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 Chan Hyun Na with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chan Hyun Na more than expected).
Fields of papers citing papers by Chan Hyun Na
This network shows the impact of papers produced by Chan Hyun Na. 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 Chan Hyun Na. The network helps show where Chan Hyun Na may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chan Hyun Na, 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 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 4 | |
| 6 | 2025 | 0 | |
| 7 | 2025 | 0 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 2 | |
| 10 | 2024 | 3 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 29 | |
| 13 | 2023 | 18 | |
| 14 | 2023 | 35 | |
| 15 | 2022 | 31 | |
| 16 | 2021 | 15 | |
| 17 | 2020 | 12 | |
| 18 | 2018 | 58 | |
| 19 | 2018 | 4 | |
| 20 | 2015 | 34 |
About Chan Hyun Na
Chan Hyun Na is a scholar working on Neurology, Neurology and Molecular Biology, having authored 72 papers that have together received 1.6k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (14 papers), Advanced Proteomics Techniques and Applications (9 papers), Parkinson's Disease Mechanisms and Treatments (8 papers), Ubiquitin and proteasome pathways (6 papers), Glycosylation and Glycoproteins Research (5 papers), Neurological diseases and metabolism (5 papers), Metabolomics and Mass Spectrometry Studies (5 papers) and Mass Spectrometry Techniques and Applications (5 papers). The work is most often cited by research in Cell Biology (251 citations), Molecular Biology (995 citations) and Neurology (207 citations). Chan Hyun Na has collaborated with scholars based in United States, South Korea and India. Frequent co-authors include Akhilesh Pandey, Junmin Peng, Santosh Renuse, Anil K. Madugundu, Raja Sekhar Nirujogi, Yura Jang, Richard L. Huganir, Min‐Sik Kim, Sungtaek Oh and Abhay Moghekar. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.
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.