Sang Won Kang

14.0k total citations · 4 hit papers
116 papers, 11.6k citations indexed

About

Sang Won Kang is a scholar working on Molecular Biology, Immunology and Biochemistry. According to data from OpenAlex, Sang Won Kang has authored 116 papers receiving a total of 11.6k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Molecular Biology, 25 papers in Immunology and 17 papers in Biochemistry. Recurrent topics in Sang Won Kang's work include Redox biology and oxidative stress (54 papers), Heat shock proteins research (20 papers) and Glutathione Transferases and Polymorphisms (17 papers). Sang Won Kang is often cited by papers focused on Redox biology and oxidative stress (54 papers), Heat shock proteins research (20 papers) and Glutathione Transferases and Polymorphisms (17 papers). Sang Won Kang collaborates with scholars based in South Korea, United States and Finland. Sang Won Kang's co-authors include Sue Goo Rhee, Ivan Baines, Kanghwa Kim, Ho Zoon Chae, Min Seok Seo, Hyun Ae Woo, Woojin Jeong, Kap-Seok Yang, Yun Soo Bae and Tong-Shin Chang and has published in prestigious journals such as Nature, Science and Journal of Biological Chemistry.

In The Last Decade

Sang Won Kang

114 papers receiving 11.4k citations

Hit Papers

Epidermal Growth Factor (... 1997 2026 2006 2016 1997 1998 2005 2001 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sang Won Kang South Korea 46 8.9k 1.6k 1.5k 1.3k 1.1k 116 11.6k
Michel B. Tolédano France 44 8.4k 0.9× 946 0.6× 1.4k 0.9× 811 0.6× 944 0.8× 87 11.8k
Hiroshi Masutani Japan 52 6.4k 0.7× 991 0.6× 932 0.6× 1.0k 0.8× 599 0.5× 144 8.4k
Junji Yodoi Japan 62 7.2k 0.8× 3.6k 2.3× 1.1k 0.8× 1.3k 1.0× 1.1k 0.9× 209 12.1k
Ichiro Kudo Japan 62 6.9k 0.8× 1.9k 1.2× 1.5k 1.0× 1.7k 1.3× 766 0.7× 206 13.2k
Jesús Balsinde Spain 59 6.1k 0.7× 1.3k 0.9× 2.0k 1.4× 1.3k 1.0× 774 0.7× 147 9.1k
Ryo Taguchi Japan 56 6.1k 0.7× 968 0.6× 1.8k 1.2× 1.5k 1.1× 871 0.8× 212 10.0k
Junji Yodoi Japan 69 11.9k 1.3× 4.7k 3.0× 2.0k 1.4× 2.1k 1.5× 1.4k 1.3× 271 19.2k
Ho Zoon Chae South Korea 32 7.0k 0.8× 775 0.5× 1.3k 0.9× 773 0.6× 968 0.9× 51 8.7k
Emile Van Schaftingen Belgium 68 9.8k 1.1× 914 0.6× 1.9k 1.3× 2.3k 1.7× 759 0.7× 263 15.6k
Tobias P. Dick Germany 47 6.4k 0.7× 1.7k 1.1× 1.9k 1.3× 796 0.6× 432 0.4× 97 9.5k

Countries citing papers authored by Sang Won Kang

Since Specialization
Citations

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

Fields of papers citing papers by Sang Won Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sang Won Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Sang Won Kang. A scholar is included among the top collaborators of Sang Won Kang 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 Sang Won Kang. Sang Won Kang 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.
Kang, Dong Hoon, et al.. (2025). The small molecule peroxiredoxin mimetics restore growth factor signalings and reverse vascular remodeling. Free Radical Biology and Medicine. 229. 300–311.
2.
Kim, Yerin, Ka Young Chung, In‐Jeoung Baek, et al.. (2023). Blood flow patterns switch VEGFR2 activity through differential S-nitrosylation and S-oxidation. Cell Reports. 42(11). 113361–113361. 4 indexed citations
3.
Kim, Ji Yeon, Hyo Min Cho, Sujin Park, et al.. (2022). Heat shock protein 60 couples an oxidative stress-responsive p38/MK2 signaling and NF-κB survival machinery in cancer cells. Redox Biology. 51. 102293–102293. 15 indexed citations
4.
Lee, Sunmi, et al.. (2022). RIP3-Dependent Accumulation of Mitochondrial Superoxide Anions in TNF-α-Induced Necroptosis. Molecules and Cells. 45(4). 193–201. 9 indexed citations
6.
Jeong, Daun, et al.. (2021). CHIP and BAP1 Act in Concert to Regulate INO80 Ubiquitination and Stability for DNA Replication. Molecules and Cells. 44(2). 101–115. 12 indexed citations
8.
Kim, Hee Yeon, et al.. (2020). SEZ6L2 Is an Important Regulator of Drug-Resistant Cells and Tumor Spheroid Cells in Lung Adenocarcinoma. Biomedicines. 8(11). 500–500. 7 indexed citations
9.
Han, Suji, Hee Yeon Kim, Seon-Hyeong Lee, et al.. (2020). Phosphorylation of OCT4 Serine 236 Inhibits Germ Cell Tumor Growth by Inducing Differentiation. Cancers. 12(9). 2601–2601. 7 indexed citations
10.
Kim, Hee Yeon, Byung Il Lee, Ji Hoon Jeon, et al.. (2019). Gossypol Suppresses Growth of Temozolomide-Resistant Glioblastoma Tumor Spheres. Biomolecules. 9(10). 595–595. 20 indexed citations
11.
Shin, Jihoon, Hee Yeon Kim, Jong-Kwang Kim, et al.. (2018). OCT4 directly regulates stemness and extracellular matrix-related genes in human germ cell tumours. Biochemical and Biophysical Research Communications. 503(3). 1980–1986. 18 indexed citations
12.
Joo, Jung Hee, Myung‐Jin Kim, Eun Jung An, et al.. (2016). NADPH Oxidase 1 Activity and ROS Generation Are Regulated by Grb2/Cbl-Mediated Proteasomal Degradation of NoxO1 in Colon Cancer Cells. Cancer Research. 76(4). 855–865. 43 indexed citations
13.
Jang, Seung Pil, Jae Gyun Oh, Dong Hoon Kang, et al.. (2016). A Decoy Peptide Targeted to Protein Phosphatase 1 Attenuates Degradation of SERCA2a in Vascular Smooth Muscle Cells. PLoS ONE. 11(10). e0165569–e0165569. 2 indexed citations
14.
Lee, Doo Jae, et al.. (2013). Peroxiredoxin-2 Represses Melanoma Metastasis by Increasing E-Cadherin/β-Catenin Complexes in Adherens Junctions. Cancer Research. 73(15). 4744–4757. 57 indexed citations
15.
Kim, Sun‐Uk, Young‐Ho Park, Ying‐Hao Han, et al.. (2013). Peroxiredoxin I is a ROS/p38 MAPK-dependent inducible antioxidant that regulates NF-κB-mediated iNOS induction and microglial activation. Journal of Neuroimmunology. 259(1-2). 26–36. 80 indexed citations
16.
Schmid, Michael C., Christie J. Avraamides, Philippe Foubert, et al.. (2011). Combined Blockade of Integrin-α4β1 Plus Cytokines SDF-1α or IL-1β Potently Inhibits Tumor Inflammation and Growth. Cancer Research. 71(22). 6965–6975. 96 indexed citations
17.
Kim, Sun Young, Phil Young Lee, Hye–Jun Shin, et al.. (2009). Proteomic analysis of liver tissue from HBx‐transgenic mice at early stages of hepatocarcinogenesis. PROTEOMICS. 9(22). 5056–5066. 27 indexed citations
18.
Kang, Sang Won, et al.. (2004). Cytosolic Peroxiredoxin Attenuates The Activation Of Jnk And P38 But Potentiates That Of Erk In Hela Cells Stimulated With Tumor Necrosis Factor-α. Journal of Biological Chemistry. 279(4). 2535–2543. 76 indexed citations
19.
Lee, Tae‐Hoon, Sun Jung Kim, Sang Won Kang, et al.. (2000). Molecular Cloning and Characterization of the Mouse Peroxiredoxin V Gene. Biochemical and Biophysical Research Communications. 270(2). 356–362. 25 indexed citations
20.
Choi, Hee-Jeong, et al.. (1998). Crystal structure of a novel human peroxidase enzyme at 2.0 Å resolution. Nature Structural Biology. 5(5). 400–406. 323 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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