Do Yoon Kwon

829 total citations
10 papers, 685 citations indexed

About

Do Yoon Kwon is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Organic Chemistry. According to data from OpenAlex, Do Yoon Kwon has authored 10 papers receiving a total of 685 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Organic Chemistry. Recurrent topics in Do Yoon Kwon's work include Medical Image Segmentation Techniques (2 papers), Advanced biosensing and bioanalysis techniques (2 papers) and Amino Acid Enzymes and Metabolism (1 paper). Do Yoon Kwon is often cited by papers focused on Medical Image Segmentation Techniques (2 papers), Advanced biosensing and bioanalysis techniques (2 papers) and Amino Acid Enzymes and Metabolism (1 paper). Do Yoon Kwon collaborates with scholars based in South Korea and United States. Do Yoon Kwon's co-authors include Taegun Kwon, Sang Sun Kang, Jaesun Chun, Jae‐Hong Kim, Régis Grailhe, Rita Song, Jaeseung Kim, Hyeyoung Park, Junwon Kim and Ji Young Ryu and has published in prestigious journals such as Journal of Biological Chemistry, Chemical Communications and Biochemical and Biophysical Research Communications.

In The Last Decade

Do Yoon Kwon

10 papers receiving 677 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Do Yoon Kwon South Korea	7	447	287	83	77	62	10	685
Hideaki Hamazaki Japan	11	271 0.6×	196 0.7×	51 0.6×	49 0.6×	85 1.4×	23	475
Joanna Boros United Kingdom	11	498 1.1×	85 0.3×	48 0.6×	102 1.3×	60 1.0×	13	622
Carina von Schantz Finland	9	339 0.8×	281 1.0×	59 0.7×	100 1.3×	225 3.6×	11	760
Andrew T. Ludlow United States	16	707 1.6×	541 1.9×	91 1.1×	81 1.1×	22 0.4×	33	1.1k
Christine Rothe Germany	9	535 1.2×	291 1.0×	95 1.1×	96 1.2×	22 0.4×	15	920
James H. Wright United States	14	416 0.9×	160 0.6×	52 0.6×	191 2.5×	29 0.5×	19	757
Zhizhuo Zhang Singapore	11	576 1.3×	206 0.7×	78 0.9×	82 1.1×	16 0.3×	12	749
Vedat O. Yilmaz United States	4	502 1.1×	159 0.6×	66 0.8×	173 2.2×	33 0.5×	4	783
Joel Otero United States	10	730 1.6×	187 0.7×	51 0.6×	46 0.6×	219 3.5×	13	901
Gabriella Forte United Kingdom	13	530 1.2×	103 0.4×	94 1.1×	145 1.9×	119 1.9×	16	741

Countries citing papers authored by Do Yoon Kwon

Since Specialization

Citations

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

Fields of papers citing papers by Do Yoon Kwon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Do Yoon 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 Do Yoon Kwon. The network helps show where Do Yoon Kwon may publish in the future.

Co-authorship network of co-authors of Do Yoon Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Do Yoon Kwon. A scholar is included among the top collaborators of Do Yoon 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 Do Yoon Kwon. Do Yoon Kwon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Oh, Sangmi, Do Yoon Kwon, Inhee Choi, et al.. (2021). Identification of Piperidine-3-carboxamide Derivatives Inducing Senescence-like Phenotype with Antimelanoma Activities. ACS Medicinal Chemistry Letters. 12(4). 563–571. 4 indexed citations

Oh, Sangmi, Inhee Choi, Arnaud Ogier, et al.. (2020). Discovery of 4H-chromeno[2,3-d]pyrimidin-4-one derivatives as senescence inducers and their senescence-associated antiproliferative activities on cancer cells using advanced phenotypic assay. European Journal of Medicinal Chemistry. 209. 112550–112550. 5 indexed citations

Dorval, Thierry, Arnaud Ogier, Auguste Genovesio, et al.. (2010). Contextual Automated 3D Analysis of Subcellular Organelles Adapted to High-Content Screening. SLAS DISCOVERY. 15(7). 847–857. 14 indexed citations

Kim, Junwon, Hyeyoung Park, Jaeseung Kim, et al.. (2008). Ni–nitrilotriacetic acid-modified quantum dots as a site-specific labeling agent of histidine-tagged proteins in live cells. Chemical Communications. 1910–1910. 49 indexed citations

Kwon, Do Yoon, et al.. (2008). Deformable 3D Volume Registration Using Efficient MRFs Model with Decomposed Nodes. 59.1–59.10. 7 indexed citations

Kwon, Do Yoon, et al.. (2008). Efficient Feature-Based Nonrigid Registration of Multiphase Liver CT Volumes. 36.1–36.10. 7 indexed citations

Chung, Il Yup, Choon‐Sik Park, Do Yoon Kwon, et al.. (2004). Eotaxin and monocyte chemotactic protein-3 use different modes of action. Biochemical and Biophysical Research Communications. 314(2). 646–653. 12 indexed citations

Kwon, Do Yoon, et al.. (2001). Monocyte Chemoattractant Protein-3. Journal of Back and Musculoskeletal Rehabilitation. 4 indexed citations

Kwon, Taegun, Do Yoon Kwon, Jaesun Chun, Jae‐Hong Kim, & Sang Sun Kang. (2000). Akt Protein Kinase Inhibits Rac1-GTP Binding through Phosphorylation at Serine 71 of Rac1. Journal of Biological Chemistry. 275(1). 423–428. 190 indexed citations

10.

Kang, Sang Sun, et al.. (1999). Akt Protein Kinase Enhances Human Telomerase Activity through Phosphorylation of Telomerase Reverse Transcriptase Subunit. Journal of Biological Chemistry. 274(19). 13085–13090. 393 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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