Seong Won
Impact in
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
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- Genomics and Phylogenetic Studies
- Metabolomics and Mass Spectrometry Studies
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- RNA modifications and cancer
- Molecular Biology Techniques and Applications
Papers in
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- Genomics and Phylogenetic Studies 2
- RNA and protein synthesis mechanisms 2
- Viral Infectious Diseases and Gene Expression in Insects 1
- Metabolomics and Mass Spectrometry Studies 1
- Glycosylation and Glycoproteins Research 1
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- Advanced Proteomics Techniques and Applications 3
- Mass Spectrometry Techniques and Applications 2
- Co-authors
- Vineet Bafna (5 shared papers)Nuno Bandeira (1 shared paper)Mingxun Wang (1 shared paper)Jian Wang (1 shared paper)Jeremy Carver (1 shared paper)Benjamin Pullman (1 shared paper)Sunghee Woo (3 shared papers)Clark C. Guest (2 shared papers)
- Journals
- Journal of Proteome Research (3 papers)Molecular & Cellular Proteomics (1 paper)Cell Systems (1 paper)PROTEOMICS (1 paper)
- Partner nations
- United StatesIreland
In The Last Decade
Seong Won
6 papers receiving 309 citations
Peers
Comparison fields: 5 of 58
- Spectroscopy 184
- Molecular Biology 247
- Cancer Research 13
- Biophysics 5
- Health Informatics 1
Countries citing papers authored by Seong Won
This map shows the geographic impact of Seong 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 Seong Won with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seong Won more than expected).
Fields of papers citing papers by Seong Won
This network shows the impact of papers produced by Seong 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 Seong Won. The network helps show where Seong Won may publish in the future.
Co-authors
The 25 scholars most cited alongside Seong 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 | 2018 | 126 | |
| 2 | 2013 | 86 | |
| 3 | 2014 | 55 | |
| 4 | 2015 | 28 | |
| 5 | 2019 | 12 | |
| 6 | 2017 | 5 |
About Seong Won
Seong Won is a scholar working on Molecular Biology, Spectroscopy, Oncology, Radiology, Nuclear Medicine and Imaging and Immunology, having authored 6 papers that have together received 312 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (3 papers), Genomics and Phylogenetic Studies (2 papers), Mass Spectrometry Techniques and Applications (2 papers), RNA and protein synthesis mechanisms (2 papers), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper), Glycosylation and Glycoproteins Research (1 paper) and Immunotherapy and Immune Responses (1 paper). The work is most often cited by research in Spectroscopy (184 citations), Molecular Biology (247 citations), Cancer Research (13 citations), Biophysics (5 citations) and Health Informatics (1 citation). Seong Won has collaborated with scholars based in United States and Ireland. Frequent co-authors include Vineet Bafna, Nuno Bandeira, Mingxun Wang, Jian Wang, Jeremy Carver, Benjamin Pullman, Sunghee Woo, Clark C. Guest, Seungjin Na and Gennifer E. Merrihew. Their work appears in journals such as Journal of Proteome Research, Molecular & Cellular Proteomics, Cell Systems and PROTEOMICS.
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.