Hangyeore Lee
Impact in
- Spectroscopy top 10%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
- Analytical Chemistry and Chromatography
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- Alzheimer's disease research and treatments
- Pain Mechanisms and Treatments
Papers in
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- Advanced Proteomics Techniques and Applications 6
- Mass Spectrometry Techniques and Applications 5
- Analytical Chemistry and Chromatography 4
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- Metabolomics and Mass Spectrometry Studies 2
- Glycosylation and Glycoproteins Research 2
- Machine Learning in Bioinformatics 1
- Co-authors
- Sang‐Won Lee (10 shared papers)Hokeun Kim (9 shared papers)Jingi Bae (8 shared papers)Dong‐Gi Mun (5 shared papers)Daehee Hwang (3 shared papers)Su‐Jin Kim (3 shared papers)Hark Kyun Kim (2 shared papers)Jung Hwa Lee (2 shared papers)
- Journals
- Journal of Proteome Research (2 papers)Scientific Reports (1 paper)Progress in Neurobiology (1 paper)Neurotherapeutics (1 paper)Analytical Chemistry (1 paper)
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Hangyeore Lee
10 papers receiving 175 citations
Peers
Comparison fields: 5 of 58
- Spectroscopy 77
- Physiology 37
- Molecular Biology 93
- Hematology 15
- Psychiatry and Mental health 16
Countries citing papers authored by Hangyeore Lee
This map shows the geographic impact of Hangyeore Lee'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 Hangyeore Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hangyeore Lee more than expected).
Fields of papers citing papers by Hangyeore Lee
This network shows the impact of papers produced by Hangyeore Lee. 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 Hangyeore Lee. The network helps show where Hangyeore Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Hangyeore Lee, 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 | 2015 | 28 | |
| 2 | 2019 | 23 | |
| 3 | 2014 | 20 | |
| 4 | 2016 | 20 | |
| 5 | 2020 | 18 | |
| 6 | 2015 | 16 | |
| 7 | 2016 | 15 | |
| 8 | 2012 | 15 | |
| 9 | 2014 | 13 | |
| 10 | 2021 | 7 | |
| 11 | 2024 | 0 |
About Hangyeore Lee
Hangyeore Lee is a scholar working on Spectroscopy, Molecular Biology, Cellular and Molecular Neuroscience, Physiology and Cardiology and Cardiovascular Medicine, having authored 11 papers that have together received 175 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (6 papers), Mass Spectrometry Techniques and Applications (5 papers), Analytical Chemistry and Chromatography (4 papers), Nerve injury and regeneration (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Glycosylation and Glycoproteins Research (2 papers), Machine Learning in Bioinformatics (1 paper) and Cancer Treatment and Pharmacology (1 paper). The work is most often cited by research in Spectroscopy (77 citations), Physiology (37 citations), Molecular Biology (93 citations), Hematology (15 citations) and Psychiatry and Mental health (16 citations). Hangyeore Lee has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Sang‐Won Lee, Hokeun Kim, Jingi Bae, Dong‐Gi Mun, Daehee Hwang, Su‐Jin Kim, Hark Kyun Kim, Jung Hwa Lee, Seunghoon Back and Ji-Hwan Park. Their work appears in journals such as Journal of Proteome Research, Scientific Reports, Progress in Neurobiology, Neurotherapeutics and Analytical Chemistry.
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.