Won Kyong Cho

4.4k total citations
129 papers, 2.1k citations indexed

About

Won Kyong Cho is a scholar working on Plant Science, Endocrinology and Molecular Biology. According to data from OpenAlex, Won Kyong Cho has authored 129 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Plant Science, 64 papers in Endocrinology and 37 papers in Molecular Biology. Recurrent topics in Won Kyong Cho's work include Plant Virus Research Studies (83 papers), Plant and Fungal Interactions Research (64 papers) and Plant Disease Resistance and Genetics (33 papers). Won Kyong Cho is often cited by papers focused on Plant Virus Research Studies (83 papers), Plant and Fungal Interactions Research (64 papers) and Plant Disease Resistance and Genetics (33 papers). Won Kyong Cho collaborates with scholars based in South Korea, China and United States. Won Kyong Cho's co-authors include Yeonhwa Jo, Kook‐Hyung Kim, Hoseong Choi, Sen Lian, Hyosub Chu, Jisuk Yu, Jae‐Yean Kim, Bong Choon Lee, Sangmin Kim and Yeonggil Rim and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and PLoS ONE.

In The Last Decade

Won Kyong Cho

125 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Won Kyong Cho South Korea 28 1.7k 697 663 232 120 129 2.1k
Ivan G. Maia Brazil 22 1.1k 0.7× 152 0.2× 1.2k 1.8× 156 0.7× 70 0.6× 65 2.0k
Tessa M. Burch‐Smith United States 27 3.3k 2.0× 257 0.4× 1.7k 2.6× 193 0.8× 105 0.9× 58 3.8k
Christian Godon France 9 1.7k 1.0× 255 0.4× 2.0k 3.0× 147 0.6× 158 1.3× 11 2.9k
Jun‐Min Li China 29 2.0k 1.2× 207 0.3× 973 1.5× 1.2k 5.2× 49 0.4× 144 3.0k
Arthur G. Hunt United States 37 2.8k 1.7× 395 0.6× 2.8k 4.2× 239 1.0× 66 0.6× 112 4.4k
Bernard L. Epel Israel 29 2.8k 1.7× 154 0.2× 1.2k 1.9× 112 0.5× 93 0.8× 68 3.3k
Joachim F. Uhrig Germany 23 2.1k 1.2× 114 0.2× 2.2k 3.2× 133 0.6× 129 1.1× 36 2.9k
Alison G. Roberts United Kingdom 29 2.9k 1.7× 248 0.4× 1.4k 2.1× 118 0.5× 248 2.1× 40 3.5k
Suely Lopes Gomes Brazil 28 549 0.3× 139 0.2× 1.6k 2.5× 101 0.4× 124 1.0× 88 2.3k
Jean‐Claude Huet France 31 815 0.5× 71 0.1× 883 1.3× 463 2.0× 121 1.0× 68 2.7k

Countries citing papers authored by Won Kyong Cho

Since Specialization
Citations

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

Fields of papers citing papers by Won Kyong Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won Kyong 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 Won Kyong Cho. The network helps show where Won Kyong Cho may publish in the future.

Co-authorship network of co-authors of Won Kyong Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Won Kyong Cho. A scholar is included among the top collaborators of Won Kyong 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 Won Kyong Cho. Won Kyong 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.
Cho, Won Kyong, et al.. (2024). Exploring the Benefits of Herbal Medicine Composite 5 (HRMC5) for Skin Health Enhancement. Current Issues in Molecular Biology. 46(11). 12133–12151.
2.
Jo, Yeonhwa, et al.. (2023). Exploring Tomato Fruit Viromes through Transcriptome Data Analysis. Viruses. 15(11). 2139–2139. 1 indexed citations
3.
Choi, Hoseong, Yeonhwa Jo, & Won Kyong Cho. (2023). In Silico Virome Analysis of Chinese Narcissus Transcriptomes Reveals Diverse Virus Species and Genetic Diversity at Different Flower Development Stages. Biology. 12(8). 1094–1094. 2 indexed citations
4.
Thuỷ, Võ Thị Bích, Won Kyong Cho, Yeonhwa Jo, et al.. (2023). Transcriptional Analysis of the Differences between ToLCNDV-India and ToLCNDV-ES Leading to Contrary Symptom Development in Cucumber. International Journal of Molecular Sciences. 24(3). 2181–2181. 4 indexed citations
5.
Lee, Taek‐Kyun, et al.. (2023). Comparative Transcriptomic Analysis of Genes in the 20-Hydroxyecdysone Biosynthesis in the Fern Microsorum scolopendria towards Challenges with Foliar Application of Chitosan. International Journal of Molecular Sciences. 24(3). 2397–2397. 3 indexed citations
6.
Jo, Yeonhwa, et al.. (2022). Viromes of 15 Pepper (Capsicum annuum L.) Cultivars. International Journal of Molecular Sciences. 23(18). 10507–10507. 8 indexed citations
7.
Silva, João Marcos Fagundes, Fernando L. Melo, Santiago F. Elena, et al.. (2022). Virus classification based on in-depth sequence analyses and development of demarcation criteria using the Betaflexiviridae as a case study. Journal of General Virology. 103(11). 11 indexed citations
8.
Cho, Won Kyong, C. Hyung Keun Park, Sang Youl Rhee, et al.. (2021). Detection of Minor and Major Depression through Voice as a Biomarker Using Machine Learning. Journal of Clinical Medicine. 10(14). 3046–3046. 42 indexed citations
9.
Kim, Saet‐Byul, Lisa Van den Broeck, Shailesh Karre, et al.. (2021). Analysis of the transcriptomic, metabolomic, and gene regulatory responses to Puccinia sorghi in maize. Molecular Plant Pathology. 22(4). 465–479. 26 indexed citations
10.
Jo, Yeonhwa, et al.. (2020). First Report of Cherry Virus F Infecting Japanese Plum in Korea. Plant Disease. 105(4). 1232–1232. 1 indexed citations
11.
Chu, Hyosub, Yeonhwa Jo, Hoseong Choi, Bong Choon Lee, & Won Kyong Cho. (2018). Identification of viral domains integrated into Arabidopsis proteome. Molecular Phylogenetics and Evolution. 128. 246–257. 1 indexed citations
12.
13.
Cho, Won Kyong, Tae Kyung Hyun, Dhinesh Kumar, et al.. (2015). Proteomic Analysis to Identify Tightly-Bound Cell Wall Protein in Rice Calli. Molecules and Cells. 38(8). 685–696. 11 indexed citations
14.
Choi, Hoseong, Yeonhwa Jo, Sen Lian, et al.. (2015). Comparative analysis of chrysanthemum transcriptome in response to three RNA viruses: Cucumber mosaic virus, Tomato spotted wilt virus and Potato virus X. Plant Molecular Biology. 88(3). 233–248. 31 indexed citations
15.
Jo, Yeonhwa, et al.. (2014). Transcriptomic landscape of chrysanthemums infected by Chrysanthemum stunt viroid. Plant Omics. 7(1). 1–11. 4 indexed citations
16.
Jo, Yeonhwa, Won Kyong Cho, Yeonggil Rim, et al.. (2010). Plasmodesmal receptor-like kinases identified through analysis of rice cell wall extracted proteins. PROTOPLASMA. 248(1). 191–203. 46 indexed citations
17.
Cho, Won Kyong, Xiong‐Yan Chen, Yeonggil Rim, et al.. (2009). Comprehensive proteome analysis of lettuce latex using multidimensional protein-identification technology. Phytochemistry. 70(5). 570–578. 27 indexed citations
18.
Huang, Lijun, Xiong‐Yan Chen, Yeonggil Rim, et al.. (2008). Arabidopsis glucan synthase-like 10 functions in male gametogenesis. Journal of Plant Physiology. 166(4). 344–352. 55 indexed citations
19.
Chen, Xiong‐Yan, Sun Tae Kim, Won Kyong Cho, et al.. (2008). Proteomics of weakly bound cell wall proteins in rice calli. Journal of Plant Physiology. 166(7). 675–685. 48 indexed citations
20.
Cho, Won Kyong. (1976). The effects of prostaglandin E-1 and F-2α on maturation of mouse oocytes in vitro. Reproduction. 47(1). 1–5. 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026