Se‐Ran Jun
Impact in
- Molecular Medicine top 5%
- Endocrinology top 5%
Papers in
-
- Genomics and Phylogenetic Studies 14
- Gut microbiota and health 6
- Machine Learning in Bioinformatics 3
-
- Plant-Microbe Interactions and Immunity 3
- Co-authors
- Sung‐Hou Kim (5 shared papers)Guohong Wu (4 shared papers)Gregory E. Sims (4 shared papers)David W. Ussery (16 shared papers)Intawat Nookaew (16 shared papers)Loren Hauser (5 shared papers)Trudy M. Wassenaar (9 shared papers)Miriam Land (4 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (5 papers)Applied and Environmental Microbiology (2 papers)BMC Bioinformatics (2 papers)Metabolomics (1 paper)Food Control (1 paper)
- Partner nations
- United StatesDenmarkSouth Korea
In The Last Decade
Se‐Ran Jun
42 papers receiving 1.9k citations
Se‐Ran Jun's Hit Papers
Peers
Comparison fields: 5 of 132
- Molecular Medicine 119
- Endocrinology 110
- Molecular Biology 1.2k
- Ecology 335
- Food Science 175
Countries citing papers authored by Se‐Ran Jun
This map shows the geographic impact of Se‐Ran Jun'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 Se‐Ran Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Se‐Ran Jun more than expected).
Fields of papers citing papers by Se‐Ran Jun
This network shows the impact of papers produced by Se‐Ran Jun. 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 Se‐Ran Jun. The network helps show where Se‐Ran Jun may publish in the future.
Co-authors
The 25 scholars most cited alongside Se‐Ran Jun, 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Insights from 20 years of bacterial genome sequencing Hit paper breakdown → | 2015 | 508 |
| 2 | 2009 | 302 | |
| 3 | 2009 | 126 | |
| 4 | 2018 | 106 | |
| 5 | 2016 | 98 | |
| 6 | 2020 | 95 | |
| 7 | 2005 | 85 | |
| 8 | 2015 | 68 | |
| 9 | 2009 | 60 | |
| 10 | 2009 | 54 | |
| 11 | 2015 | 52 | |
| 12 | 2015 | 45 | |
| 13 | 2015 | 41 | |
| 14 | 2017 | 38 | |
| 15 | 2014 | 33 | |
| 16 | 2018 | 32 | |
| 17 | 2021 | 20 | |
| 18 | 2017 | 19 | |
| 19 | 2020 | 19 | |
| 20 | 2020 | 15 |
About Se‐Ran Jun
Se‐Ran Jun is a scholar working on Molecular Biology, Plant Science, Infectious Diseases, Epidemiology and Clinical Biochemistry, having authored 44 papers that have together received 1.9k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (14 papers), Gut microbiota and health (6 papers), Antibiotic Resistance in Bacteria (6 papers), Bacterial Identification and Susceptibility Testing (6 papers), Antimicrobial Resistance in Staphylococcus (5 papers), Bacteriophages and microbial interactions (4 papers), Plant-Microbe Interactions and Immunity (3 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Molecular Medicine (119 citations), Endocrinology (110 citations), Molecular Biology (1.2k citations), Ecology (335 citations) and Food Science (175 citations). Se‐Ran Jun has collaborated with scholars based in United States, Denmark and South Korea. Frequent co-authors include Sung‐Hou Kim, Guohong Wu, Gregory E. Sims, David W. Ussery, Intawat Nookaew, Loren Hauser, Trudy M. Wassenaar, Miriam Land, Ole Lund and Michael R. Leuze. Their work appears in journals such as Proceedings of the National Academy of Sciences, Applied and Environmental Microbiology, BMC Bioinformatics, Metabolomics and Food Control.
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.