Gue‐Tae Chae

2.0k citations
35 papers · 1.5k · h-index 20

Impact in

Papers in

Gue‐Tae Chae

35 papers receiving 1.5k citations

Peers

Gue‐Tae Chae
Comparison fields: 5 of 111
  • Microbiology 26
  • Infectious Diseases 515
  • Small Animals 162
  • Epidemiology 659
  • Immunology 339
Replace Marcello Franco with:
Marcello Franco Brazil
Fumio Kokubu Japan
Victor D. Newcomer United States
Vernon L. Moore United States
Kiwamu Nakamura Japan
Ellen S. DeCarlo United States
C. K. Job United States
Katie R. Poch United States
Tetsuya Koga Japan
Sinéad M. Smith Ireland
Gue‐Tae Chae relative to Marcello Franco Brazil Marcello Franco's profile →
Citations per field
00.5×1.5×2.1×
Marcello Franco · 1×
Citations per year

Countries citing papers authored by Gue‐Tae Chae

Since Specialization
Citations

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

Fields of papers citing papers by Gue‐Tae Chae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gue‐Tae Chae. 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 Gue‐Tae Chae. The network helps show where Gue‐Tae Chae may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999339
2 2001209
3 2006181
4 2005143
5 200293
6 200448
7 200445
8 200842
9 200637
10 199934
11 200534
12 201130
13 201228
14 200027
15 200426
16 200325
17 200324
18 200223
19 200622
20 200421

About Gue‐Tae Chae

Gue‐Tae Chae is a scholar working on Infectious Diseases, Epidemiology, Surgery, Immunology and Genetics, having authored 35 papers that have together received 1.5k indexed citations. Recurring topics across this work include Mycobacterium research and diagnosis (18 papers), Leprosy Research and Treatment (16 papers), Tuberculosis Research and Epidemiology (9 papers), Mesenchymal stem cell research (4 papers), Immune Response and Inflammation (4 papers), Forensic and Genetic Research (2 papers), T-cell and B-cell Immunology (2 papers) and Immune Cell Function and Interaction (2 papers). The work is most often cited by research in Microbiology (26 citations), Infectious Diseases (515 citations), Small Animals (162 citations), Epidemiology (659 citations) and Immunology (339 citations). Gue‐Tae Chae has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Seong‐Beom Lee, Tae Jin Kang, Bum‐Joon Kim, Yoon‐Hoh Kook, Chang-Yong Cha, Gill‐Han Bai, Eui-Chong Kim, Mi-Ae Lyu, Sang‐Jae Kim and Seung Hyun Lee. Their work appears in journals such as Immune Network, Gene, Journal of Medical Microbiology, Journal of Tissue Engineering and Regenerative Medicine and International Journal of Gynecological Cancer.

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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