Joo‐Youn Cho

7.4k total citations
289 papers, 5.8k citations indexed

About

Joo‐Youn Cho is a scholar working on Molecular Biology, Oncology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Joo‐Youn Cho has authored 289 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 93 papers in Molecular Biology, 61 papers in Oncology and 55 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Joo‐Youn Cho's work include Pharmacogenetics and Drug Metabolism (42 papers), Drug Transport and Resistance Mechanisms (40 papers) and Diabetes Treatment and Management (30 papers). Joo‐Youn Cho is often cited by papers focused on Pharmacogenetics and Drug Metabolism (42 papers), Drug Transport and Resistance Mechanisms (40 papers) and Diabetes Treatment and Management (30 papers). Joo‐Youn Cho collaborates with scholars based in South Korea, United States and Ethiopia. Joo‐Youn Cho's co-authors include In‐Jin Jang, Kyung‐Sang Yu, Jae‐Yong Chung, Seo Hyun Yoon, Kyoung Soo Lim, SeungHwan Lee, Sang‐Goo Shin, Sang-Goo Shin, SoJeong Yi and Tae‐Eun Kim and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Joo‐Youn Cho

275 papers receiving 5.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joo‐Youn Cho South Korea 40 1.6k 1.3k 1.1k 741 713 289 5.8k
Soo‐Youn Lee South Korea 41 2.4k 1.5× 890 0.7× 575 0.5× 538 0.7× 981 1.4× 396 7.3k
Wei Zhang China 44 3.1k 1.9× 1.3k 1.0× 993 0.9× 524 0.7× 594 0.8× 351 7.0k
Stephan Krähenbühl Switzerland 50 3.0k 1.9× 1.4k 1.1× 1.5k 1.4× 733 1.0× 1.0k 1.4× 227 8.6k
Kyung‐Sang Yu South Korea 32 918 0.6× 799 0.6× 704 0.7× 597 0.8× 599 0.8× 333 4.5k
Bernd Meibohm United States 44 2.0k 1.2× 1.2k 0.9× 719 0.7× 1.1k 1.5× 349 0.5× 170 7.5k
Katharina Rentsch Switzerland 46 1.4k 0.9× 699 0.5× 454 0.4× 504 0.7× 1.2k 1.7× 186 6.3k
Yong Huang China 48 1.8k 1.1× 1.7k 1.3× 565 0.5× 736 1.0× 670 0.9× 167 7.2k
Werner Siegmund Germany 42 1.1k 0.7× 2.7k 2.1× 1.0k 1.0× 1.5k 2.1× 613 0.9× 185 6.3k
Tatsuki Fukami Japan 42 2.4k 1.5× 1.3k 1.0× 2.1k 1.9× 449 0.6× 351 0.5× 225 6.4k
Kenneth C. Lasseter United States 43 978 0.6× 825 0.6× 642 0.6× 392 0.5× 956 1.3× 155 6.4k

Countries citing papers authored by Joo‐Youn Cho

Since Specialization
Citations

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

Fields of papers citing papers by Joo‐Youn Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joo‐Youn Cho. 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 Joo‐Youn Cho. The network helps show where Joo‐Youn Cho may publish in the future.

Co-authorship network of co-authors of Joo‐Youn Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Joo‐Youn Cho. A scholar is included among the top collaborators of Joo‐Youn Cho 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 Joo‐Youn Cho. Joo‐Youn Cho 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.
Park, Seo‐Young, Dong-Seok Kim, Dong Kyung Sung, et al.. (2025). Deciphering dynamic antibiotics-microbiome-metabolome interactions in preterm infants using systems biology. iScience. 28(8). 113038–113038.
2.
Sohn, Suk Ho, Jae Woong Choi, Karam Nam, et al.. (2024). Differences in Brain Metabolite Profiles Between Normothermia and Hypothermia. Journal of Korean Medical Science. 39(7). e79–e79. 1 indexed citations
3.
Kim, Jung-Eun, et al.. (2024). Metabolomic Characteristics of Nontuberculous Mycobacterial Pulmonary Disease. The Journal of Infectious Diseases. 230(4). 797–806. 4 indexed citations
4.
5.
Kang, Ji-Hyun, et al.. (2023). Quantification of OATP1B1 endogenous metabolites coproporphyrin I and III in human urine. Translational and Clinical Pharmacology. 31(3). 139–139. 1 indexed citations
6.
Jeong, Do‐Won, Jong‐Wan Park, Jiyoung Kim, et al.. (2023). Palmitoylation-driven PHF2 ubiquitination remodels lipid metabolism through the SREBP1c axis in hepatocellular carcinoma. Nature Communications. 14(1). 6370–6370. 39 indexed citations
7.
Moon, Jin Soo, et al.. (2022). Association of Metabolic Signatures with Nonalcoholic Fatty Liver Disease in Pediatric Population. Metabolites. 12(9). 881–881. 6 indexed citations
8.
9.
Lee, Soyoung, et al.. (2022). The pharmacokinetic, safety, and tolerability profiles of eslicarbazepine acetate are comparable between Korean and White subjects. Clinical and Translational Science. 15(9). 2116–2126. 5 indexed citations
10.
Lee, Yujin, et al.. (2021). Effects of vancomycin‐induced gut microbiome alteration on the pharmacodynamics of metformin in healthy male subjects. Clinical and Translational Science. 14(5). 1955–1966. 17 indexed citations
11.
Lee, Yujin, Andrew HyoungJin Kim, SeungHwan Lee, et al.. (2021). Changes in the gut microbiome influence the hypoglycemic effect of metformin through the altered metabolism of branched-chain and nonessential amino acids. Diabetes Research and Clinical Practice. 178. 108985–108985. 31 indexed citations
12.
13.
Kim, Da Jung, Eun Ju Cho, Kyung‐Sang Yu, et al.. (2019). Comprehensive Metabolomic Search for Biomarkers to Differentiate Early Stage Hepatocellular Carcinoma from Cirrhosis. Cancers. 11(10). 1497–1497. 55 indexed citations
14.
Suh, Hyeon Jeong, Seo Hyun Yoon, Kyung‐Sang Yu, et al.. (2018). The Genetic Polymorphism UGT1A4*3 Is Associated with Low Posaconazole Plasma Concentrations in Hematological Malignancy Patients Receiving the Oral Suspension. Antimicrobial Agents and Chemotherapy. 62(7). 20 indexed citations
15.
Suh, Hyeon Jeong, Inho Kim, Joo‐Youn Cho, et al.. (2017). Comparison of Plasma Concentrations of Posaconazole with the Oral Suspension and Tablet in Korean Patients with Hematologic Malignancies. Infection and Chemotherapy. 49(2). 135–135. 11 indexed citations
16.
Shin, Dongseong, SeungHwan Lee, SoJeong Yi, et al.. (2017). Pharmacokinetics and tolerability of DA-8031, a novel selective serotonin reuptake inhibitor for premature ejaculation in healthy male subjects. Drug Design Development and Therapy. Volume11. 713–723. 3 indexed citations
17.
Cho, Joo‐Youn & B. Ya. Levit. (2008). Cardinal splines in nonparametric regression. Mathematical Methods of Statistics. 17(1). 19–34. 2 indexed citations
18.
Lee, SH, Hyung Jun Kim, Sunil Bhandari, et al.. (2003). Granular Cell Tumor of the Ascending Colon: Report of a Case. Intestinal Research. 1(1). 59–63. 2 indexed citations
19.
Jang, In‐Jin, et al.. (2003). Variability in Drug Interaction According to Genetic Polymorphisms in Drug Metabolizing Enzymes. 23(4). 131–134. 1 indexed citations
20.
Cho, Joo‐Youn, et al.. (2001). Transcriptional activation of the human Cu/Zn superoxide dismutase gene by 2,3,7,8-tetrachlorodibenzo-p-dioxin through the xenobiotic-responsive element. Molecular Genetics and Genomics. 266(1). 133–141. 14 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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