Chan-Ki Min

890 citations
16 papers · 679 · h-index 11

Impact in

    • Vector-borne infectious diseases
    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • Viral Infections and Vectors
    • Viral gastroenteritis research and epidemiology

Papers in

    • Immune Cell Function and Interaction 2
    • Immune Response and Inflammation 2
    • Invertebrate Immune Response Mechanisms 1
    • Vector-borne infectious diseases 7

Chan-Ki Min

16 papers receiving 669 citations

Peers

Chan-Ki Min
Comparison fields: 5 of 76
  • Parasitology 164
  • Infectious Diseases 347
  • Modeling and Simulation 31
  • Neurology 82
  • Animal Science and Zoology 45
Replace Carl Shaia with:
Carl Shaia United States
Jolien Van Cleemput Belgium
Shelley P. Honnold United States
Eric C. Mossel United States
Yogesh K. Gurav India
Dimpal A. Nyayanit India
Krishanthi Subramaniam United Kingdom
Edward JD Greenwood United Kingdom
Mark Anthony B. Casel South Korea
Jonas N. Conde United States
Chan-Ki Min relative to Carl Shaia United States Carl Shaia's profile →
Citations per field
00.5×4.2×
Carl Shaia · 1×
Citations per year

Countries citing papers authored by Chan-Ki Min

Since Specialization
Citations

This map shows the geographic impact of Chan-Ki Min'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 Chan-Ki Min with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chan-Ki Min more than expected).

Fields of papers citing papers by Chan-Ki Min

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chan-Ki Min. 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 Chan-Ki Min. The network helps show where Chan-Ki Min may publish in the future.

Co-authors

The 25 scholars most cited alongside Chan-Ki Min, 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 Chan-Ki Min Line = papers co-authored together Chan-Ki Min links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2016292
2 201675
3 201762
4 201547
5 200843
6 202029
7 201426
8 201825
9 201723
10 201918
11 202111
12 20169
13 20166
14 20146
15 20205
16 20172

About Chan-Ki Min

Chan-Ki Min is a scholar working on Immunology, Parasitology, Molecular Biology, Epidemiology and Plant Science, having authored 16 papers that have together received 679 indexed citations. Recurring topics across this work include Vector-borne infectious diseases (7 papers), Cytomegalovirus and herpesvirus research (2 papers), Plant Virus Research Studies (2 papers), Herpesvirus Infections and Treatments (2 papers), Immune Cell Function and Interaction (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Immune Response and Inflammation (2 papers) and Invertebrate Immune Response Mechanisms (1 paper). The work is most often cited by research in Parasitology (164 citations), Infectious Diseases (347 citations), Modeling and Simulation (31 citations), Neurology (82 citations) and Animal Science and Zoology (45 citations). Chan-Ki Min has collaborated with scholars based in South Korea, Ethiopia and United States. Frequent co-authors include Nam‐Hyuk Cho, Myung‐Sik Choi, Yuri Kim, Na‐Young Ha, Kim Ys, Abdimadiyeva Aigerim, Kyung Mok Sohn, Shinhye Cheon, Hyun Mu Shin and Ik-Sang Kim. Their work appears in journals such as Emerging Microbes & Infections, PLoS ONE, PLoS neglected tropical diseases, Frontiers in Plant Science and The 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.

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