Han Sang Yoo

6.1k total citations
256 papers, 4.5k citations indexed

About

Han Sang Yoo is a scholar working on Infectious Diseases, Molecular Biology and Microbiology. According to data from OpenAlex, Han Sang Yoo has authored 256 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Infectious Diseases, 66 papers in Molecular Biology and 55 papers in Microbiology. Recurrent topics in Han Sang Yoo's work include Microbial infections and disease research (39 papers), Mycobacterium research and diagnosis (36 papers) and Bacteriophages and microbial interactions (32 papers). Han Sang Yoo is often cited by papers focused on Microbial infections and disease research (39 papers), Mycobacterium research and diagnosis (36 papers) and Bacteriophages and microbial interactions (32 papers). Han Sang Yoo collaborates with scholars based in South Korea, Ethiopia and Puerto Rico. Han Sang Yoo's co-authors include Mi Lan Kang, Sang Gyun Kang, Myunghwan Jung, Sung Jae Shin, Soojin Shim, Min‐Kyoung Shin, Hong-Tae Park, Nabin Rayamajhi, Deog Yong Lee and Seung Won Shin and has published in prestigious journals such as PLoS ONE, Biomaterials and Applied and Environmental Microbiology.

In The Last Decade

Han Sang Yoo

244 papers receiving 4.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Han Sang Yoo South Korea 34 1.1k 1.1k 828 741 602 256 4.5k
John Hwa Lee South Korea 32 1.7k 1.5× 831 0.8× 724 0.9× 462 0.6× 1.5k 2.4× 224 4.2k
Yung‐Fu Chang United States 42 2.2k 2.0× 1.0k 0.9× 574 0.7× 676 0.9× 325 0.5× 229 5.6k
Shigeru Kamiya Japan 40 1.2k 1.1× 1.3k 1.2× 919 1.1× 1.0k 1.4× 657 1.1× 203 5.3k
Mary Barton Australia 38 1.1k 1.0× 901 0.8× 629 0.8× 282 0.4× 999 1.7× 120 4.4k
Paolo Pasquali Italy 30 725 0.6× 628 0.6× 367 0.4× 618 0.8× 627 1.0× 89 2.9k
Karsten Tedin Germany 31 764 0.7× 1.8k 1.6× 1.1k 1.4× 403 0.5× 994 1.7× 74 4.3k
Michael J. Wannemuehler United States 43 939 0.8× 1.9k 1.7× 2.0k 2.4× 872 1.2× 381 0.6× 177 5.4k
Sara D. Lawhon United States 32 1.4k 1.2× 1.8k 1.7× 419 0.5× 541 0.7× 1.6k 2.7× 163 4.7k
Charles W. Penn United Kingdom 37 708 0.6× 1.7k 1.5× 504 0.6× 442 0.6× 996 1.7× 121 4.7k
Robert J. Yancey United States 34 657 0.6× 571 0.5× 414 0.5× 570 0.8× 645 1.1× 74 3.0k

Countries citing papers authored by Han Sang Yoo

Since Specialization
Citations

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

Fields of papers citing papers by Han Sang Yoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Han Sang Yoo. 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 Han Sang Yoo. The network helps show where Han Sang Yoo may publish in the future.

Co-authorship network of co-authors of Han Sang Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Han Sang Yoo. A scholar is included among the top collaborators of Han Sang Yoo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Han Sang Yoo. Han Sang Yoo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jang, Ji Young, et al.. (2025). Co-infections with Bordetella bronchiseptica in canine: A systematic review and meta-analysis. Veterinary Immunology and Immunopathology. 280. 110886–110886.
2.
Jang, Ji Young, et al.. (2025). Safety and efficacy of a Bordetella bronchiseptica outer membrane proteins (OMPs) subunit vaccine in a murine model. Journal of Veterinary Science. 26(3). e39–e39.
3.
Lee, Jun Ho, et al.. (2024). Emergence and genomic characterization of Proteus mirabilis harboring blaNDM-1 in Korean companion dogs. Veterinary Research. 55(1). 50–50. 3 indexed citations
4.
Lee, Sang‐Mok, et al.. (2023). A Machine Learning Approach Reveals a Microbiota Signature for Infection with Mycobacterium avium subsp. paratuberculosis in Cattle. Microbiology Spectrum. 11(1). e0313422–e0313422. 8 indexed citations
5.
Cho, Yun Sang, Ji-Hyuk Park, Jong Wan Kim, et al.. (2023). Current Status of Q Fever and the Challenge of Outbreak Preparedness in Korea: One Health Approach to Zoonoses. Journal of Korean Medical Science. 38(24). e197–e197. 5 indexed citations
6.
Lee, Jun Ho, et al.. (2023). Whole genome structure and resistance genes in carbapenemase-producing multidrug resistant ST378 Klebsiella pneumoniae. BMC Microbiology. 23(1). 323–323. 5 indexed citations
7.
Jung, Woo Kyung, Sook Shin, Young Kyung Park, et al.. (2020). Distribution and antimicrobial resistance profiles of bacterial species in stray dogs, hospital-admitted dogs, and veterinary staff in South Korea. Preventive Veterinary Medicine. 184. 105151–105151. 18 indexed citations
8.
9.
10.
Shin, Seung Won, et al.. (2018). Genetic Analysis of p17S-208 Plasmid Encoding the Colistin Resistance mcr-3 Gene in Escherichia coli Isolated from Swine in South Korea. Microbial Drug Resistance. 25(3). 457–461. 1 indexed citations
11.
Shin, Min‐Kyoung, Hong-Tae Park, Hong-Tae Park, et al.. (2016). Gene expression profiles of putative biomarker candidates inMycobacterium aviumsubsp.paratuberculosis-infected cattle. Pathogens and Disease. 74(4). ftw022–ftw022. 20 indexed citations
12.
Lau, Agnes, David Westaway, Debbie McKenzie, et al.. (2011). Establishment and characterization ofPrnpknockdown neuroblastoma cells using dual microRNA-mediated RNA interference. Prion. 5(2). 93–102. 12 indexed citations
13.
Rayamajhi, Nabin, et al.. (2010). Evaluation of in vitro and in vivo bacteriophage efficacy against Salmonella enterica serovar Enteritidis infection. 50(3). 213–220.
14.
Shin, Nari, Deog‐Yong Lee, & Han Sang Yoo. (2008). Analysis of Gene Expression in Mouse Alveolar Macrophages Stimulated with Quorum-Sensing Mutants of <i>Vibrio vulnificus</i>. Japanese Journal of Infectious Diseases. 61(5). 402–406. 2 indexed citations
15.
Lim, Hyun‐Sul, Young Goo Song, Han Sang Yoo, Mi Yeoun Park, & Jong Wan Kim. (2005). Brucellosis: An Overview. 27(1). 26–36. 7 indexed citations
16.
Lim, Hyun‐Sul, et al.. (2005). Anthrax: An Overview. Epidemiology and Health. 27(1). 12–25. 1 indexed citations
17.
Shin, Nari, Deog‐Yong Lee, Young‐Wook Cho, et al.. (2005). luxS and smcR quorum-sensing system of Vibrio vulnificus as an important factor for In Vivo survival. Journal of Microbiology and Biotechnology. 15(6). 1197–1206. 3 indexed citations
18.
Yoo, Han Sang, et al.. (2004). Analysis of biological hazards and control points in layer houses. 44(4). 593–605. 3 indexed citations
19.
Yoo, Byung Woo, Sohyun Kim, Soo Jin Yang, et al.. (2002). Immunostimulatory effects of an anionic alkali mineral complex solution (Barodon®) on porcine lymphocytes. Journal of Swine Health and Production. 10(6). 265–270. 5 indexed citations
20.
Leite, Fábio Pereira Leivas, et al.. (1999). Use of TUNEL staining to detect apoptotic cells in the lungs of cattle experimentally infected with Pasteurella haemolytica. Microbial Pathogenesis. 27(3). 179–185. 8 indexed citations

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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