Insung Ahn
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
-
- Climate Change and Health Impacts
Papers in
- Epidemiology 17
- Influenza Virus Research Studies 14
- Data-Driven Disease Surveillance 6
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- RNA and protein synthesis mechanisms 10
- Genomics and Phylogenetic Studies 4
- Machine Learning in Bioinformatics 3
- Co-authors
- Soo Beom Choi (4 shared papers)Hyeon S. Son (16 shared papers)Woo‐Sik Son (1 shared paper)Yeonhee Ryu (1 shared paper)Okyu Kwon (1 shared paper)Ji‐Eun Park (1 shared paper)Jin Young Jung (1 shared paper)Sunghoon Jung (3 shared papers)
- Journals
- Experimental & Molecular Medicine (5 papers)PLoS ONE (4 papers)BMC Bioinformatics (2 papers)Scientific Reports (1 paper)Canadian Journal of Microbiology (1 paper)
- Partner nations
- South KoreaSudan
In The Last Decade
Insung Ahn
31 papers receiving 359 citations
Peers
Comparison fields: 5 of 88
- Modeling and Simulation 129
- Health, Toxicology and Mutagenesis 54
- Infectious Diseases 67
- Epidemiology 116
- Global and Planetary Change 50
Countries citing papers authored by Insung Ahn
This map shows the geographic impact of Insung Ahn'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 Insung Ahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Insung Ahn more than expected).
Fields of papers citing papers by Insung Ahn
This network shows the impact of papers produced by Insung Ahn. 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 Insung Ahn. The network helps show where Insung Ahn may publish in the future.
Co-authors
The 14 scholars most cited alongside Insung Ahn, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 155 | |
| 2 | 2021 | 33 | |
| 3 | 2006 | 31 | |
| 4 | 2020 | 18 | |
| 5 | 2019 | 16 | |
| 6 | 2011 | 13 | |
| 7 | 2019 | 13 | |
| 8 | 2015 | 8 | |
| 9 | 2007 | 8 | |
| 10 | 2009 | 6 | |
| 11 | 2023 | 6 | |
| 12 | 2013 | 6 | |
| 13 | 2016 | 6 | |
| 14 | 2014 | 5 | |
| 15 | 2006 | 5 | |
| 16 | 2017 | 5 | |
| 17 | 2007 | 4 | |
| 18 | 2020 | 4 | |
| 19 | 2011 | 4 | |
| 20 | 2011 | 3 |
About Insung Ahn
Insung Ahn is a scholar working on Epidemiology, Molecular Biology, Modeling and Simulation, Ecology and Public Health, Environmental and Occupational Health, having authored 37 papers that have together received 369 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (14 papers), RNA and protein synthesis mechanisms (10 papers), COVID-19 epidemiological studies (7 papers), Bacteriophages and microbial interactions (6 papers), Data-Driven Disease Surveillance (6 papers), Genomics and Phylogenetic Studies (4 papers), Mosquito-borne diseases and control (4 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Modeling and Simulation (129 citations), Health, Toxicology and Mutagenesis (54 citations), Infectious Diseases (67 citations), Epidemiology (116 citations) and Global and Planetary Change (50 citations). Insung Ahn has collaborated with scholars based in South Korea and Sudan. Frequent co-authors include Soo Beom Choi, Hyeon S. Son, Woo‐Sik Son, Yeonhee Ryu, Okyu Kwon, Ji‐Eun Park, Jin Young Jung, Sunghoon Jung, Ji‐Hae Lee and Jooyeon Park. Their work appears in journals such as Experimental & Molecular Medicine, PLoS ONE, BMC Bioinformatics, Scientific Reports and Canadian Journal of Microbiology.
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.