Pan‐Jun Kim
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
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- Bioinformatics and Genomic Networks 6
- Gene Regulatory Network Analysis 6
- Microbial Metabolic Engineering and Bioproduction 5
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- Technology and Data Analysis 4
- Co-authors
- Hawoong Jeong (12 shared papers)Sang Hoon Lee (4 shared papers)Yong‐Su Jin (6 shared papers)Jaeyun Sung (6 shared papers)Nathan D. Price (6 shared papers)Nicholas Chia (2 shared papers)Dong‐Yup Lee (2 shared papers)Seunghyeon Kim (1 shared paper)
- Journals
- PLoS Computational Biology (4 papers)PLoS ONE (4 papers)BMC Systems Biology (2 papers)Physical Review Letters (1 paper)Scientific Data (1 paper)
- Partner nations
- South KoreaUnited StatesItaly
In The Last Decade
Pan‐Jun Kim
45 papers receiving 1.2k citations
Pan‐Jun Kim's Hit Papers
Peers
Comparison fields: 5 of 143
- Statistical and Nonlinear Physics 341
- Aging 18
- Molecular Biology 572
- Biological Psychiatry 16
- General Social Sciences 21
Countries citing papers authored by Pan‐Jun Kim
This map shows the geographic impact of Pan‐Jun Kim'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 Pan‐Jun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pan‐Jun Kim more than expected).
Fields of papers citing papers by Pan‐Jun Kim
This network shows the impact of papers produced by Pan‐Jun Kim. 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 Pan‐Jun Kim. The network helps show where Pan‐Jun Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Pan‐Jun Kim, 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 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Statistical properties of sampled networks Hit paper breakdown → | 2006 | 327 |
| 2 | 2017 | 194 | |
| 3 | 2007 | 109 | |
| 4 | 2011 | 86 | |
| 5 | 2010 | 49 | |
| 6 | 2004 | 43 | |
| 7 | 2016 | 41 | |
| 8 | 2007 | 35 | |
| 9 | 2011 | 35 | |
| 10 | 2010 | 31 | |
| 11 | 2009 | 30 | |
| 12 | 2016 | 27 | |
| 13 | 2016 | 24 | |
| 14 | 2015 | 21 | |
| 15 | 2016 | 20 | |
| 16 | 2005 | 20 | |
| 17 | 2020 | 18 | |
| 18 | 2011 | 14 | |
| 19 | 2013 | 13 | |
| 20 | 2018 | 12 |
About Pan‐Jun Kim
Pan‐Jun Kim is a scholar working on Molecular Biology, Information Systems, Statistical and Nonlinear Physics, Public Health, Environmental and Occupational Health and Plant Science, having authored 51 papers that have together received 1.3k indexed citations. Recurring topics across this work include Light effects on plants (6 papers), Bioinformatics and Genomic Networks (6 papers), Complex Network Analysis Techniques (6 papers), Gene Regulatory Network Analysis (6 papers), Diverse Approaches in Healthcare and Education Studies (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers), Technology and Data Analysis (4 papers) and Plant Molecular Biology Research (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (341 citations), Aging (18 citations), Molecular Biology (572 citations), Biological Psychiatry (16 citations) and General Social Sciences (21 citations). Pan‐Jun Kim has collaborated with scholars based in South Korea, United States and Italy. Frequent co-authors include Hawoong Jeong, Sang Hoon Lee, Yong‐Su Jin, Jaeyun Sung, Nathan D. Price, Nicholas Chia, Dong‐Yup Lee, Seunghyeon Kim, Gyoo Yeol Jung and Sungho Jang. Their work appears in journals such as PLoS Computational Biology, PLoS ONE, BMC Systems Biology, Physical Review Letters and Scientific Data.
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.