Jun‐Sik Lim

26 papers receiving 462 citations

Peers

Jun‐Sik Lim
Comparison fields: 5 of 94
  • Modeling and Simulation 106
  • Agronomy and Crop Science 114
  • Infectious Diseases 147
  • Parasitology 25
  • Biomaterials 51
Replace Yassir Adam Shuaib with:
Yassir Adam Shuaib Sudan
Hanwu Ma China
Simona Iannetti Italy
Sonia T. Hegde United States
Babasola Oluseyi Olugasa Nigeria
Laurence Thirion France
Bijon Kumar Sil Bangladesh
Norma Padilla United States
Emma C. Hobbs Australia
Jun‐Sik Lim relative to Yassir Adam Shuaib Sudan Yassir Adam Shuaib's profile →
Citations per field
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Yassir Adam Shuaib · 1×
Citations per year

Countries citing papers authored by Jun‐Sik Lim

Since Specialization
Citations

This map shows the geographic impact of Jun‐Sik Lim'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 Jun‐Sik Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun‐Sik Lim more than expected).

Fields of papers citing papers by Jun‐Sik Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐Sik Lim. 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 Jun‐Sik Lim. The network helps show where Jun‐Sik Lim may publish in the future.

Co-authors

The 25 scholars most cited alongside Jun‐Sik Lim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun‐Sik Lim Line = papers co-authored together Jun‐Sik Lim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201766
2 202257
3 201152
4 202145
5 202131
6 202127
7 202024
8 202123
9 202321
10 202016
11 202115
12 201914
13 202113
14 202013
15 202112
16 202110
17 20199
18 20177
19 20135
20 20214

About Jun‐Sik Lim

Jun‐Sik Lim is a scholar working on Agronomy and Crop Science, Infectious Diseases, Ecology, Evolution, Behavior and Systematics, Epidemiology and Modeling and Simulation, having authored 27 papers that have together received 474 indexed citations. Recurring topics across this work include Animal Disease Management and Epidemiology (13 papers), Vector-Borne Animal Diseases (6 papers), COVID-19 epidemiological studies (5 papers), Influenza Virus Research Studies (5 papers), Zoonotic diseases and public health (4 papers), Agriculture and Farm Safety (3 papers), Viral Infections and Immunology Research (3 papers) and Viral gastroenteritis research and epidemiology (2 papers). The work is most often cited by research in Modeling and Simulation (106 citations), Agronomy and Crop Science (114 citations), Infectious Diseases (147 citations), Parasitology (25 citations) and Biomaterials (51 citations). Jun‐Sik Lim has collaborated with scholars based in South Korea, France and Hong Kong. Frequent co-authors include Sukhyun Ryu, Byung Chul Chun, Sheikh Taslim Ali, Bryan Kim, Son‐Il Pak, Timothée Vergne, Benjamin J. Cowling, Sunmi ‍Lee, Chang‐Seok Ki and Chiara Achangwa. Their work appears in journals such as Emerging infectious diseases, Transboundary and Emerging Diseases, Journal of Veterinary Science, Animals and Influenza and Other Respiratory Viruses.

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.

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