Green Kim

438 citations
23 papers · 241 · h-index 9

Impact in

Papers in

    • SARS-CoV-2 and COVID-19 Research 7
    • COVID-19 Clinical Research Studies 6
    • Clostridium difficile and Clostridium perfringens research 3
    • Viral Infections and Vectors 3
    • Gut microbiota and health 3

Green Kim

20 papers receiving 237 citations

Peers

Green Kim
Comparison fields: 5 of 72
  • Complementary and alternative medicine 36
  • Infectious Diseases 79
  • Food Science 47
  • Immunology 40
  • Animal Science and Zoology 14
Replace Sang-Gu Yeo with:
Sang-Gu Yeo South Korea
Jakarwan Yostawonkul Thailand
Chandramathi Samudi Raju Malaysia
Ritsuko Koketsu Japan
Marius B. Tincho South Africa
Ryoko Kawabata Japan
Esther Lee South Korea
Sangeeta Jaiswal United States
Dayakar Alti India
Jisang Park South Korea
Green Kim relative to Sang-Gu Yeo South Korea Sang-Gu Yeo's profile →
Citations per field
00.5×2.8×
Sang-Gu Yeo · 1×
Citations per year

Countries citing papers authored by Green Kim

Since Specialization
Citations

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

Fields of papers citing papers by Green Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Green 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 Green Kim. The network helps show where Green Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201654
2 201732
3 202025
4 201717
5 201917
6 201515
7 202411
8 201710
9 20208
10 20218
11 20197
12 20206
13 20236
14 20226
15 20225
16 20215
17 20234
18 20243
19 20231
20 20211

About Green Kim

Green Kim is a scholar working on Infectious Diseases, Molecular Biology, Immunology, Surgery and Epidemiology, having authored 23 papers that have together received 241 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), COVID-19 Clinical Research Studies (6 papers), Gut microbiota and health (3 papers), Clostridium difficile and Clostridium perfringens research (3 papers), Viral Infections and Vectors (3 papers), Mosquito-borne diseases and control (3 papers), Phytochemicals and Medicinal Plants (2 papers) and Gastrointestinal motility and disorders (2 papers). The work is most often cited by research in Complementary and alternative medicine (36 citations), Infectious Diseases (79 citations), Food Science (47 citations), Immunology (40 citations) and Animal Science and Zoology (14 citations). Green Kim has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include Jong‐Hwan Park, Jung Joo Hong, Eunha Hwang, Bon‐Sang Koo, Hanseul Oh, Kyu‐Tae Chang, JooHee Choi, Tae‐Hyoun Kim, Jae‐Hak Park and Sanggyu Yim. Their work appears in journals such as Journal of Medical Primatology, Frontiers in Microbiology, The Journal of Infectious Diseases, Archives of Virology and Immune Network.

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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