Choon‐Tak Kwon

1.4k total citations
29 papers, 1.0k citations indexed

About

Choon‐Tak Kwon is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Choon‐Tak Kwon has authored 29 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Plant Science, 18 papers in Molecular Biology and 2 papers in Genetics. Recurrent topics in Choon‐Tak Kwon's work include Plant Molecular Biology Research (11 papers), Plant Reproductive Biology (8 papers) and Plant tissue culture and regeneration (6 papers). Choon‐Tak Kwon is often cited by papers focused on Plant Molecular Biology Research (11 papers), Plant Reproductive Biology (8 papers) and Plant tissue culture and regeneration (6 papers). Choon‐Tak Kwon collaborates with scholars based in South Korea, United States and Spain. Choon‐Tak Kwon's co-authors include Nam‐Chon Paek, Soo-Cheul Yoo, Joyce Van Eck, Zachary B. Lippman, Zichao Li, Jinjie Li, Gynheung An, Zachary H. Lemmon, Zhanying Zhang and Byoung‐Doo Lee and has published in prestigious journals such as Nature Genetics, Nature Biotechnology and International Journal of Molecular Sciences.

In The Last Decade

Choon‐Tak Kwon

26 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Choon‐Tak Kwon South Korea 16 940 516 266 30 28 29 1.0k
Xiaodeng Zhan China 17 935 1.0× 487 0.9× 322 1.2× 31 1.0× 21 0.8× 64 1.0k
Daibo Chen China 19 812 0.9× 521 1.0× 190 0.7× 26 0.9× 14 0.5× 40 937
Junpeng Shi China 10 846 0.9× 486 0.9× 205 0.8× 13 0.4× 56 2.0× 16 1.1k
R. Ramamoorthy Singapore 16 912 1.0× 694 1.3× 105 0.4× 26 0.9× 37 1.3× 26 1.1k
Tim Helentjaris United States 14 1.1k 1.2× 444 0.9× 320 1.2× 33 1.1× 53 1.9× 17 1.2k
Ning Xiao China 17 853 0.9× 367 0.7× 300 1.1× 68 2.3× 12 0.4× 54 993
Xianchun Sang China 16 841 0.9× 556 1.1× 199 0.7× 22 0.7× 16 0.6× 85 945
Jafar Mammadov United States 9 639 0.7× 239 0.5× 252 0.9× 30 1.0× 41 1.5× 13 738
Liang‐Jiao Xue China 16 837 0.9× 604 1.2× 87 0.3× 41 1.4× 49 1.8× 38 1.1k
Hisaharu Kato Japan 13 935 1.0× 552 1.1× 258 1.0× 35 1.2× 16 0.6× 19 1.0k

Countries citing papers authored by Choon‐Tak Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Choon‐Tak Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Choon‐Tak Kwon. 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 Choon‐Tak Kwon. The network helps show where Choon‐Tak Kwon may publish in the future.

Co-authorship network of co-authors of Choon‐Tak Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Choon‐Tak Kwon. A scholar is included among the top collaborators of Choon‐Tak Kwon 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 Choon‐Tak Kwon. Choon‐Tak Kwon 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.
Hong, Seungpyo, Taek Sung Lee, Soo Hyun Park, et al.. (2025). Volumetric Deep Learning-Based Precision Phenotyping of Gene-Edited Tomato for Vertical Farming. Plant Phenomics. 7(3). 100095–100095.
2.
Kim, Minsoo, et al.. (2024). SERKs serve as co‐receptors for SYR1 to trigger systemin‐mediated defense responses in tomato. Journal of Integrative Plant Biology. 66(10). 2273–2287. 6 indexed citations
3.
Lee, Chanhui, et al.. (2024). Comparative yield evaluation of mini-tomato cultivar in two hydroponic systems. Horticulture Environment and Biotechnology. 65(2). 239–250. 4 indexed citations
4.
Jeong, Hayoung, Seungpyo Hong, Jiwoo Lee, et al.. (2024). Precise customization of plant architecture by combinatorial genetic modification of peptide ligands. Plant Communications. 6(2). 101175–101175. 3 indexed citations
5.
6.
Hwang, In Sun, et al.. (2023). A Putative Apoplastic Effector of Clavibacter capsici, ChpGCc as Hypersensitive Response and Virulence (Hrv) Protein in Plants. Molecular Plant-Microbe Interactions. 37(4). 370–379. 2 indexed citations
7.
Lee, Soo‐Hong, et al.. (2023). Bacteriophage cocktail for biocontrol of soft rot disease caused by Pectobacterium species in Chinese cabbage. Applied Microbiology and Biotechnology. 108(1). 11–11. 12 indexed citations
8.
Wang, Chenglei, Tania Ho‐Plágaro, Choon‐Tak Kwon, et al.. (2023). The Role of CLE Peptides in the Suppression of Mycorrhizal Colonization of Tomato. Plant and Cell Physiology. 65(1). 107–119. 17 indexed citations
9.
Kwon, Choon‐Tak, Lingli Tang, Xingang Wang, et al.. (2022). Dynamic evolution of small signalling peptide compensation in plant stem cell control. Nature Plants. 8(4). 346–355. 39 indexed citations
10.
Hwang, In Sun, et al.. (2022). Nicotianabenthamiana, a Surrogate Host to Study Novel Virulence Mechanisms of Gram-Positive Bacteria, Clavibacter michiganensis, and C. capsici in Plants. Frontiers in Plant Science. 13. 876971–876971. 3 indexed citations
11.
Wang, Chenglei, et al.. (2020). The role of CLAVATA signalling in the negative regulation of mycorrhizal colonization and nitrogen response of tomato. Journal of Experimental Botany. 72(5). 1702–1713. 21 indexed citations
12.
Rodríguez-Leal, Daniel, Xu Cao, Choon‐Tak Kwon, et al.. (2019). Evolution of buffering in a genetic circuit controlling plant stem cell proliferation. Nature Genetics. 51(5). 786–792. 135 indexed citations
13.
Kwon, Choon‐Tak, Suk‐Hwan Kim, Yejin Shim, et al.. (2019). The Rice SPOTTED LEAF4 (SPL4) Encodes a Plant Spastin That Inhibits ROS Accumulation in Leaf Development and Functions in Leaf Senescence. Frontiers in Plant Science. 9. 1925–1925. 24 indexed citations
14.
Kwon, Choon‐Tak, Jung Heo, Zachary H. Lemmon, et al.. (2019). Rapid customization of Solanaceae fruit crops for urban agriculture. Nature Biotechnology. 38(2). 182–188. 163 indexed citations
15.
Kwon, Choon‐Tak, et al.. (2017). Two NADPH: Protochlorophyllide Oxidoreductase (POR) Isoforms Play Distinct Roles in Environmental Adaptation in Rice. Rice. 10(1). 1–1. 43 indexed citations
16.
Kwon, Choon‐Tak, et al.. (2015). The Rice Floral Repressor Early flowering1 Affects Spikelet Fertility By Modulating Gibberellin Signaling. Rice. 8(1). 58–58. 34 indexed citations
17.
Kwon, Choon‐Tak, et al.. (2014). Casein Kinases I and 2α Phosphorylate Oryza Sativa Pseudo-Response Regulator 37 (OsPRR37) in Photoperiodic Flowering in Rice. Molecules and Cells. 38(1). 81–88. 36 indexed citations
18.
Kwon, Choon‐Tak, Soo‐Cheul Yoo, Sung‐Hwan Cho, et al.. (2013). Natural variation in Early flowering1 contributes to early flowering in japonica rice under long days. Plant Cell & Environment. 37(1). 101–112. 47 indexed citations
19.
Kwon, Choon‐Tak, J. B. Rasmussen, & Steven W. Meinhardt. (1998). Activity of Ptr ToxA fromPyrenophora tritici-repentisrequires host metabolism. Physiological and Molecular Plant Pathology. 52(3). 201–212. 35 indexed citations
20.
Kwon, Choon‐Tak, J. B. Rasmussen, L. J. Francl, & Steven W. Meinhardt. (1996). A quantitative bioassay for necrosis toxin from Pyrenophora tritici-repentis based on electrolyte leakage.. Phytopathology. 86(12). 1360–1363. 17 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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