Young‐Ok Son

7.0k total citations · 1 hit paper
140 papers, 5.5k citations indexed

About

Young‐Ok Son is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Young‐Ok Son has authored 140 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Molecular Biology, 21 papers in Immunology and 20 papers in Cancer Research. Recurrent topics in Young‐Ok Son's work include Phytochemicals and Antioxidant Activities (13 papers), Genomics, phytochemicals, and oxidative stress (12 papers) and Chromium effects and bioremediation (12 papers). Young‐Ok Son is often cited by papers focused on Phytochemicals and Antioxidant Activities (13 papers), Genomics, phytochemicals, and oxidative stress (12 papers) and Chromium effects and bioremediation (12 papers). Young‐Ok Son collaborates with scholars based in South Korea, United States and India. Young‐Ok Son's co-authors include Jeong‐Chae Lee, Xianglin Shi, Zhuo Zhang, Poyil Pratheeshkumar, Amit Budhraja, John Andrew Hitron, Donghern Kim, Jia Luo, Yong‐Suk Jang and Sung‐Ho Kook and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Young‐Ok Son

136 papers receiving 5.3k citations

Hit Papers

The CH25H–CYP7B1–RORα axis of cholesterol metabolism regu... 2019 2026 2021 2023 2019 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Young‐Ok Son South Korea 44 2.4k 733 662 603 591 140 5.5k
Ling Zhao China 32 1.8k 0.8× 469 0.6× 624 0.9× 390 0.6× 865 1.5× 91 6.0k
Jeong‐Chae Lee South Korea 37 2.3k 1.0× 397 0.5× 796 1.2× 455 0.8× 298 0.5× 147 4.9k
Ying‐Jan Wang Taiwan 48 3.2k 1.4× 495 0.7× 481 0.7× 593 1.0× 532 0.9× 129 7.1k
Yinglun Li China 28 1.6k 0.7× 404 0.6× 490 0.7× 308 0.5× 762 1.3× 65 5.2k
Haseeb Ahsan India 30 2.7k 1.1× 207 0.3× 467 0.7× 531 0.9× 548 0.9× 122 6.2k
Peramaiyan Rajendran India 39 2.6k 1.1× 394 0.5× 565 0.9× 646 1.1× 497 0.8× 105 6.1k
Xin Wang China 48 3.8k 1.6× 242 0.3× 702 1.1× 782 1.3× 546 0.9× 281 7.7k
María Celeste Lopes Portugal 42 1.7k 0.7× 346 0.5× 823 1.2× 587 1.0× 665 1.1× 116 4.9k
Madan M. Chaturvedi United States 31 3.7k 1.6× 249 0.3× 813 1.2× 1.1k 1.8× 1.1k 1.8× 54 8.2k
Whasun Lim South Korea 39 2.4k 1.0× 763 1.0× 1.0k 1.5× 890 1.5× 747 1.3× 303 6.2k

Countries citing papers authored by Young‐Ok Son

Since Specialization
Citations

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

Fields of papers citing papers by Young‐Ok Son

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young‐Ok Son. 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 Young‐Ok Son. The network helps show where Young‐Ok Son may publish in the future.

Co-authorship network of co-authors of Young‐Ok Son

This figure shows the co-authorship network connecting the top 25 collaborators of Young‐Ok Son. A scholar is included among the top collaborators of Young‐Ok Son 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 Young‐Ok Son. Young‐Ok Son 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.
Sakla, Rahul, Ajay Kumar, Md. Meraj Ansari, et al.. (2024). Sinapic acid-pullulan based inflammation responsive nanomicelles for the local treatment of experimental inflammatory arthritis. International Journal of Biological Macromolecules. 278(Pt 3). 134903–134903. 5 indexed citations
2.
Kim, Jin-Ho, et al.. (2024). Comprehensive in vitro and in vivo investigations of the therapeutic potential of Jeju lava seawater salt in osteoarthritis. Applied Biological Chemistry. 67(1). 2 indexed citations
3.
Ghosh, Mrinmoy, et al.. (2024). CARBONIC ANHYDRASES CAUSE ALTERATION OF ANABOLIC AND CATABOLIC FACTORS THROUGH INCREASING METABOLIC SHIFT IN OA PATHOGENESIS. Osteoarthritis and Cartilage. 32(6). 812–813. 1 indexed citations
5.
Ghosh, Mrinmoy, et al.. (2023). Metal-Based Nanoparticles and Their Relevant Consequences on Cytotoxicity Cascade and Induced Oxidative Stress. Antioxidants. 12(3). 703–703. 55 indexed citations
6.
Ahn, Dohyun, et al.. (2022). Excessive sucrose exacerbates high fat diet-induced hepatic inflammation and fibrosis promoting osteoarthritis in mice model. The Journal of Nutritional Biochemistry. 112. 109223–109223. 7 indexed citations
8.
Patra, Anupam, et al.. (2022). Marine Antimicrobial Peptides-Based Strategies for Tackling Bacterial Biofilm and Biofouling Challenges. Molecules. 27(21). 7546–7546. 22 indexed citations
9.
Zhao, Xiaosu, et al.. (2021). Therapeutic Single Compounds for Osteoarthritis Treatment. Pharmaceuticals. 14(2). 131–131. 18 indexed citations
11.
Chatterjee, Rahul, Soumya Ranjan Mahapatra, Jyotirmayee Dey, et al.. (2021). Development of a Conserved Chimeric Vaccine for Induction of Strong Immune Response against Staphylococcus aureus Using Immunoinformatics Approaches. Vaccines. 9(9). 1038–1038. 42 indexed citations
12.
Chatterjee, Rahul, Mrinmoy Ghosh, Santwana Padhi, et al.. (2021). Next-Generation Bioinformatics Approaches and Resources for Coronavirus Vaccine Discovery and Development—A Perspective Review. Vaccines. 9(8). 812–812. 17 indexed citations
13.
Kim, Dahye, et al.. (2020). GSK5182, 4-Hydroxytamoxifen Analog, a New Potential Therapeutic Drug for Osteoarthritis. Pharmaceuticals. 13(12). 429–429. 6 indexed citations
14.
Wang, Yuting, Ardhendu Mandal, Young‐Ok Son, et al.. (2018). Roles of ROS, Nrf2, and autophagy in cadmium-carcinogenesis and its prevention by sulforaphane. Toxicology and Applied Pharmacology. 353. 23–30. 127 indexed citations
15.
Park, Sangheon, Jinseol Rhee, Jung‐Ah Kang, et al.. (2018). BATF regulates collagen-induced arthritis by regulating T helper cell differentiation. Arthritis Research & Therapy. 20(1). 161–161. 14 indexed citations
16.
Divya, Sasidharan Padmaja, Xin Wang, Poyil Pratheeshkumar, et al.. (2015). Blackberry extract inhibits UVB-induced oxidative damage and inflammation through MAP kinases and NF-κB signaling pathways in SKH-1 mice skin. Toxicology and Applied Pharmacology. 284(1). 92–99. 77 indexed citations
17.
Zhang, Zhuo, Poyil Pratheeshkumar, Amit Budhraja, et al.. (2014). Role of reactive oxygen species in arsenic-induced transformation of human lung bronchial epithelial (BEAS-2B) cells. Biochemical and Biophysical Research Communications. 456(2). 643–648. 58 indexed citations
18.
Budhraja, Amit, Ning Gao, Zhuo Zhang, et al.. (2011). Apigenin Induces Apoptosis in Human Leukemia Cells and Exhibits Anti-Leukemic Activity In Vivo. Molecular Cancer Therapeutics. 11(1). 132–142. 82 indexed citations
19.
Cheng, Senping, Ning Gao, Zhuo Zhang, et al.. (2010). Quercetin Induces Tumor-Selective Apoptosis through Downregulation of Mcl-1 and Activation of Bax. Clinical Cancer Research. 16(23). 5679–5691. 78 indexed citations
20.
Kim, Jooyoung, Young‐Ok Son, Soon‐Won Park, et al.. (2006). Increase of NKG2D ligands and sensitivity to NK cell-mediated cytotoxicity of tumor cells by heat shock and ionizing radiation. Experimental & Molecular Medicine. 38(5). 474–484. 158 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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