Dong‐Gi Mun
Impact in
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
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- Metabolomics and Mass Spectrometry Studies
- Glycosylation and Glycoproteins Research
Papers in
- Spectroscopy 22
- Advanced Proteomics Techniques and Applications 21
- Mass Spectrometry Techniques and Applications 16
- Analytical Chemistry and Chromatography 4
-
- Metabolomics and Mass Spectrometry Studies 6
- Glycosylation and Glycoproteins Research 4
- Genomics and Phylogenetic Studies 4
- Machine Learning in Bioinformatics 2
- Co-authors
- Sang‐Won Lee (17 shared papers)Akhilesh Pandey (25 shared papers)Hokeun Kim (12 shared papers)Mayank Saraswat (6 shared papers)Kishore Garapati (5 shared papers)Anil Kumar Madugundu (7 shared papers)Daehee Hwang (4 shared papers)Hangyeore Lee (5 shared papers)
- Journals
- Journal of Proteome Research (6 papers)Analytical Chemistry (5 papers)Molecular & Cellular Proteomics (3 papers)The Analyst (3 papers)PROTEOMICS (3 papers)
- Partner nations
- United StatesIndiaSouth Korea
In The Last Decade
Dong‐Gi Mun
37 papers receiving 570 citations
Peers
Comparison fields: 5 of 81
- Spectroscopy 194
- Molecular Biology 277
- Cell Biology 56
- Physiology 82
- Infectious Diseases 58
Countries citing papers authored by Dong‐Gi Mun
This map shows the geographic impact of Dong‐Gi Mun'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 Dong‐Gi Mun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dong‐Gi Mun more than expected).
Fields of papers citing papers by Dong‐Gi Mun
This network shows the impact of papers produced by Dong‐Gi Mun. 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 Dong‐Gi Mun. The network helps show where Dong‐Gi Mun may publish in the future.
Co-authors
The 25 scholars most cited alongside Dong‐Gi Mun, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 62 | |
| 2 | 2021 | 49 | |
| 3 | 2012 | 45 | |
| 4 | 2016 | 40 | |
| 5 | 2015 | 29 | |
| 6 | 2021 | 25 | |
| 7 | 2021 | 24 | |
| 8 | 2014 | 23 | |
| 9 | 2021 | 19 | |
| 10 | 2020 | 19 | |
| 11 | 2018 | 19 | |
| 12 | 2016 | 17 | |
| 13 | 2023 | 17 | |
| 14 | 2023 | 17 | |
| 15 | 2015 | 16 | |
| 16 | 2012 | 16 | |
| 17 | 2016 | 15 | |
| 18 | 2024 | 14 | |
| 19 | 2024 | 13 | |
| 20 | 2011 | 13 |
About Dong‐Gi Mun
Dong‐Gi Mun is a scholar working on Spectroscopy, Molecular Biology, Oncology, Infectious Diseases and Cellular and Molecular Neuroscience, having authored 40 papers that have together received 573 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (21 papers), Mass Spectrometry Techniques and Applications (16 papers), Metabolomics and Mass Spectrometry Studies (6 papers), Glycosylation and Glycoproteins Research (4 papers), Genomics and Phylogenetic Studies (4 papers), Analytical Chemistry and Chromatography (4 papers), Machine Learning in Bioinformatics (2 papers) and Axon Guidance and Neuronal Signaling (2 papers). The work is most often cited by research in Spectroscopy (194 citations), Molecular Biology (277 citations), Cell Biology (56 citations), Physiology (82 citations) and Infectious Diseases (58 citations). Dong‐Gi Mun has collaborated with scholars based in United States, India and South Korea. Frequent co-authors include Sang‐Won Lee, Akhilesh Pandey, Hokeun Kim, Mayank Saraswat, Kishore Garapati, Anil Kumar Madugundu, Daehee Hwang, Hangyeore Lee, Jingi Bae and Seunghoon Back. Their work appears in journals such as Journal of Proteome Research, Analytical Chemistry, Molecular & Cellular Proteomics, The Analyst 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.