Myeon Woo Chung

612 total citations
27 papers, 493 citations indexed

About

Myeon Woo Chung is a scholar working on Molecular Biology, Pharmacology and Pharmacology. According to data from OpenAlex, Myeon Woo Chung has authored 27 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 12 papers in Pharmacology and 6 papers in Pharmacology. Recurrent topics in Myeon Woo Chung's work include Pharmacogenetics and Drug Metabolism (9 papers), Metabolomics and Mass Spectrometry Studies (6 papers) and Drug Transport and Resistance Mechanisms (5 papers). Myeon Woo Chung is often cited by papers focused on Pharmacogenetics and Drug Metabolism (9 papers), Metabolomics and Mass Spectrometry Studies (6 papers) and Drug Transport and Resistance Mechanisms (5 papers). Myeon Woo Chung collaborates with scholars based in South Korea and United States. Myeon Woo Chung's co-authors include Ki Hwan Choi, Kyu‐Bong Kim, Seon Hwa Kim, Hwa Kyung Lim, Hyun Sub Cheong, Hyoung Doo Shin, Kyung Rak Min, Hack-Seang Kim, Young‐Soo Kim and Ji Seon Oh and has published in prestigious journals such as Analytical Chemistry, Analytica Chimica Acta and Journal of Ethnopharmacology.

In The Last Decade

Myeon Woo Chung

26 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Myeon Woo Chung South Korea 12 219 157 102 67 46 27 493
Omar Abdulhameed Almazroo United States 4 153 0.7× 174 1.1× 42 0.4× 87 1.3× 40 0.9× 6 505
Liping Ma China 18 229 1.0× 136 0.9× 43 0.4× 145 2.2× 46 1.0× 41 682
Sook Jin Seong South Korea 15 351 1.6× 145 0.9× 76 0.7× 86 1.3× 27 0.6× 59 668
P. F. Coville New Zealand 14 139 0.6× 207 1.3× 71 0.7× 94 1.4× 32 0.7× 21 512
Anna Vuorinen Switzerland 15 281 1.3× 153 1.0× 93 0.9× 43 0.6× 20 0.4× 25 686
Hong-Hao Zhou China 15 281 1.3× 238 1.5× 96 0.9× 181 2.7× 51 1.1× 52 735
Ahmed A. El-Sherbeni Canada 17 165 0.8× 223 1.4× 59 0.6× 52 0.8× 11 0.2× 34 689
Sylvie Lepage France 15 177 0.8× 157 1.0× 50 0.5× 55 0.8× 14 0.3× 38 698
Lynda Letzig United States 18 164 0.7× 497 3.2× 141 1.4× 152 2.3× 66 1.4× 24 916

Countries citing papers authored by Myeon Woo Chung

Since Specialization
Citations

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

Fields of papers citing papers by Myeon Woo Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Myeon Woo Chung. 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 Myeon Woo Chung. The network helps show where Myeon Woo Chung may publish in the future.

Co-authorship network of co-authors of Myeon Woo Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Myeon Woo Chung. A scholar is included among the top collaborators of Myeon Woo Chung 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 Myeon Woo Chung. Myeon Woo Chung 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, Jung Hyun, et al.. (2016). 1 H-Nuclear magnetic resonance-based metabolic profiling of nonsteroidal anti-inflammatory drug-induced adverse effects in rats. Journal of Pharmaceutical and Biomedical Analysis. 129. 492–501. 3 indexed citations
2.
Kim, Jung-Ryul, Shinn‐Won Lim, Myeon Woo Chung, et al.. (2015). Exposure–outcome analysis in depressed patients treated with paroxetine using population pharmacokinetics. Drug Design Development and Therapy. 9. 5247–5247. 5 indexed citations
3.
Cheong, Hyun Sub, et al.. (2015). Comparison of genetic variations of the SLCO1B1, SLCO1B3, and SLCO2B1 genes among five ethnic groups. Environmental Toxicology and Pharmacology. 40(3). 692–697. 10 indexed citations
4.
Kang, Tae Sun, et al.. (2014). Determination of DPYD Enzyme Activity in Korean Population. Therapeutic Drug Monitoring. 37(2). 147–151. 3 indexed citations
5.
Kim, Minju, et al.. (2014). Tobacco smoking-response genes in blood and buccal cells. Toxicology Letters. 232(2). 429–437. 17 indexed citations
6.
Kim, Jeong‐Hyun, Hyun Sub Cheong, Byung Lae Park, et al.. (2014). Direct sequencing and comprehensive screening of genetic polymorphisms on CYP2 family genes (CYP2A6, CYP2B6, CYP2C8, and CYP2E1) in five ethnic populations. Archives of Pharmacal Research. 38(1). 115–128. 10 indexed citations
7.
Shin, Hee Jung, et al.. (2014). Functional Study of Haplotypes in UGT1A1 Promoter to Find a Novel Genetic Variant Leading to Reduced Gene Expression. Therapeutic Drug Monitoring. 37(3). 369–374. 10 indexed citations
8.
Kim, Jason Yongha, et al.. (2014). Screening for 392 polymorphisms in 141 pharmacogenes. Biomedical Reports. 2(4). 463–476. 9 indexed citations
9.
Lee, Jin Sol, Hyun Sub Cheong, Lyoung Hyo Kim, et al.. (2013). Screening of Genetic Polymorphisms ofCYP3A4andCYP3A5Genes. Korean Journal of Physiology and Pharmacology. 17(6). 479–479. 48 indexed citations
10.
Kim, Jason Yongha, Hyun Sub Cheong, Byung Lae Park, et al.. (2013). Comprehensive Variant Screening of the UGT Gene Family. Yonsei Medical Journal. 55(1). 232–232. 29 indexed citations
11.
Han, Song‐Hee, Young‐Jin Chun, Chul‐Ho Yun, et al.. (2012). Functional Characterization of Allelic Variants of Polymorphic Human Cytochrome P450 2A6 (CYP2A6*5, *7, *8, *18, *19, and *35). Biological and Pharmaceutical Bulletin. 35(3). 394–399. 28 indexed citations
12.
Park, Jung Hyun, Myeon Woo Chung, Kyu‐Bong Kim, et al.. (2012). Nuclear magnetic resonance-based metabolomics for prediction of gastric damage induced by indomethacin in rats. Analytica Chimica Acta. 722. 87–94. 20 indexed citations
13.
Hwang, Myung-Sil, et al.. (2011). Signal detection of methylphenidate by comparing a spontaneous reporting database with a claims database. Regulatory Toxicology and Pharmacology. 61(2). 154–160. 11 indexed citations
14.
Cheong, Hyun Sub, Lyoung Hyo Kim, Seung Hee Kim, et al.. (2011). Screening of genetic variations of SLC15A2, SLC22A1, SLC22A2 and SLC22A6 genes. Journal of Human Genetics. 56(9). 666–670. 9 indexed citations
15.
Kim, Donghak, et al.. (2011). Expression of CYP2A6, CYP2D6 and CYP4A11 Polymorphisms in COS7 Mammalian Cell Line. Toxicological Research. 27(1). 25–29. 1 indexed citations
16.
Kang, Dae Ryong, Xianghua Zhang, Young-Pil Wang, et al.. (2011). Proposal of pharmacogenetics-based warfarin dosing algorithm in Korean patients. Journal of Human Genetics. 56(4). 290–295. 29 indexed citations
17.
Chung, Myeon Woo, et al.. (2010). Simple determination of azasetron in rat plasma by column‐switching high‐performance liquid chromatography. Journal of Separation Science. 33(23-24). 3638–3643. 4 indexed citations
18.
Kang, Tae Sun, et al.. (2009). The Korean Pharmacogenomic Database at NIFDS: 2008 Update. Genomics & Informatics. 7(3). 163–167.
19.
Kang, Ju-Hee, Sung Yong Lee, Myeon Woo Chung, et al.. (2002). Aroclor 1254-induced cytotoxicity in catecholaminergic CATH.a cells related to the inhibition of NO production. Toxicology. 177(2-3). 157–166. 20 indexed citations
20.
Kim, Hack-Seang, et al.. (2000). Anti-inflammatory effects of fangchinoline and tetrandrine. Journal of Ethnopharmacology. 69(2). 173–179. 98 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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