Won-Ki Kim

5.6k total citations · 1 hit paper
110 papers, 4.8k citations indexed

About

Won-Ki Kim is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Won-Ki Kim has authored 110 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 35 papers in Neurology and 31 papers in Cellular and Molecular Neuroscience. Recurrent topics in Won-Ki Kim's work include Neuroinflammation and Neurodegeneration Mechanisms (33 papers), Neuroscience and Neuropharmacology Research (24 papers) and Immune Response and Inflammation (9 papers). Won-Ki Kim is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (33 papers), Neuroscience and Neuropharmacology Research (24 papers) and Immune Response and Inflammation (9 papers). Won-Ki Kim collaborates with scholars based in South Korea, United States and Japan. Won-Ki Kim's co-authors include Hee-Sun Kim, Hyoung‐Chun Kim, Moon-Sook Woo, Jin‐Sun Park, Venkata Rayudu Posina, Yun‐Beom Choi, Jonathan S. Stamler, Stuart A. Lipton, Derrick R. Arnelle and Jae‐Chul Lee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Immunology.

In The Last Decade

Won-Ki Kim

110 papers receiving 4.7k citations

Hit Papers

Neurotoxicity associated ... 1997 2026 2006 2016 1997 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Won-Ki Kim 1.8k 918 887 579 576 110 4.8k
Dan Zhang 2.5k 1.4× 1.1k 1.2× 534 0.6× 863 1.5× 114 0.2× 201 5.6k
Ji Hoon Jeong 1.9k 1.0× 467 0.5× 819 0.9× 1.1k 1.9× 103 0.2× 260 5.7k
Maria Antonietta Panaro 1.8k 1.0× 927 1.0× 311 0.4× 692 1.2× 135 0.2× 142 4.7k
Irene Paterniti 1.9k 1.0× 709 0.8× 477 0.5× 733 1.3× 80 0.1× 191 5.1k
Dora Brites 3.9k 2.1× 1.8k 2.0× 524 0.6× 1.1k 1.9× 125 0.2× 164 7.9k
Rammohan V. Rao 3.4k 1.9× 297 0.3× 774 0.9× 774 1.3× 118 0.2× 61 6.1k
Makoto Michikawa 2.9k 1.6× 806 0.9× 865 1.0× 3.1k 5.4× 135 0.2× 155 6.2k
Huanxing Su 2.4k 1.3× 516 0.6× 989 1.1× 708 1.2× 73 0.1× 177 6.5k
Arabinda Das 1.6k 0.9× 777 0.8× 737 0.8× 373 0.6× 57 0.1× 81 4.0k
Ana Maria Oliveira Battastini 1.9k 1.1× 403 0.4× 440 0.5× 519 0.9× 117 0.2× 195 6.0k

Countries citing papers authored by Won-Ki Kim

Since Specialization
Citations

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

Fields of papers citing papers by Won-Ki Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won-Ki Kim. 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-Ki Kim. The network helps show where Won-Ki Kim may publish in the future.

Co-authorship network of co-authors of Won-Ki Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Won-Ki Kim. A scholar is included among the top collaborators of Won-Ki Kim 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-Ki Kim. Won-Ki Kim 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.
Pahk, Kisoo, Mi Jang, Kyung Won Kim, et al.. (2019). A novel CD147 inhibitor, SP-8356, reduces neointimal hyperplasia and arterial stiffness in a rat model of partial carotid artery ligation. Journal of Translational Medicine. 17(1). 274–274. 22 indexed citations
2.
Lee, Yeunkum, Hyojin Kang, Bokyoung Lee, et al.. (2017). Integrative Analysis of Brain Region-specific Shank3 Interactomes for Understanding the Heterogeneity of Neuronal Pathophysiology Related to SHANK3 Mutations. Frontiers in Molecular Neuroscience. 10. 110–110. 28 indexed citations
4.
Yun, Nuri, Chiho Kim, Hirohiko Shibayama, et al.. (2014). Anamorsin, a Novel Caspase-3 Substrate in Neurodegeneration. Journal of Biological Chemistry. 289(32). 22183–22195. 9 indexed citations
5.
Ju, Chung, Sun‐Young Hwang, Geum-Sil Cho, et al.. (2012). Differential anti-ischemic efficacy and therapeutic time window of trans- and cis-hinokiresinols: Stereo-specific antioxidant and anti-inflammatory activities. Neuropharmacology. 67. 465–475. 8 indexed citations
6.
Cho, Geum-Sil, Sun‐Young Hwang, Byung Woo Kim, et al.. (2010). Methyleugenol reduces cerebral ischemic injury by suppression of oxidative injury and inflammation. Free Radical Research. 44(8). 925–935. 67 indexed citations
7.
Lee, Jae‐Chul, Geum-Sil Cho, Byung‐Ok Choi, Hyoung‐Chun Kim, & Won-Ki Kim. (2009). Aging Exacerbates Intracerebral Hemorrhage-Induced Brain Injury. Journal of Neurotrauma. 26(9). 1567–1576. 16 indexed citations
8.
Shin, Eun‐Joo, Ji Hoon Jeong, Guoying Bing, et al.. (2008). Kainate-induced mitochondrial oxidative stress contributes to hippocampal degeneration in senescence-accelerated mice. Cellular Signalling. 20(4). 645–658. 50 indexed citations
9.
Kim, Jimyung, Namsoo Chang, Won-Ki Kim, & Hyang Sook Chun. (2006). Dietary S-Allyl-L-cysteine Reduces Mortality with Decreased Incidence of Stroke and Behavioral Changes in Stroke-Prone Spontaneously Hypertensive Rats. Bioscience Biotechnology and Biochemistry. 70(8). 1969–1971. 23 indexed citations
10.
Kim, Jimyung, Jae‐Chul Lee, Namsoo Chang, Hyang Sook Chun, & Won-Ki Kim. (2006). S-Allyl-l-cysteine attenuates cerebral ischemic injury by scavenging peroxynitrite and inhibiting the activity of extracellular signal-regulated kinase. Free Radical Research. 40(8). 827–835. 43 indexed citations
12.
Kim, Won-Ki, et al.. (2004). TGF-β1 Represses Activation and Resultant Death of Microglia via Inhibition of Phosphatidylinositol 3-Kinase Activity. The Journal of Immunology. 172(11). 7015–7023. 101 indexed citations
13.
Oh, Yu‐Kyoung, Jeong‐Sook Park, Han-Gon Choi, et al.. (2004). Enhanced mucosal and systemic immunogenicity of human papillomavirus-like particles encapsidating interleukin-2 gene adjuvant. Virology. 328(2). 266–273. 19 indexed citations
14.
Kim, Won-Ki, Moon-Sook Woo, Hua Piao, et al.. (2004). A new anti-inflammatory agent KL-1037 represses proinflammatory cytokine and inducible nitric oxide synthase (iNOS) gene expression in activated microglia. Neuropharmacology. 47(2). 243–252. 32 indexed citations
15.
Huh, Youngbuhm, Ji Wook Jung, Chan Park, et al.. (2003). Microglial activation and tyrosine hydroxylase immunoreactivity in the substantia nigral region following transient focal ischemia in rats. Neuroscience Letters. 349(1). 63–67. 33 indexed citations
17.
Kim, Hyoung‐Chun, Guoying Bing, Seong‐Jin Kim, et al.. (2002). Kainate treatment alters TGF-β3 gene expression in the rat hippocampus. Molecular Brain Research. 108(1-2). 60–70. 12 indexed citations
18.
Kim, Hyoung‐Chun, Guoying Bing, Wang-Kee Jhoo, et al.. (2002). Metabolism to dextrorphan is not essential for dextromethorphan's anticonvulsant activity against kainate in mice. Life Sciences. 72(7). 769–783. 33 indexed citations
19.
Bing, Guoying, et al.. (1999). Dextromethorphan modulates the AP-1 DNA-binding activity induced by kainic acid. Brain Research. 824(1). 125–132. 33 indexed citations
20.
Kim, Won-Ki, et al.. (1998). Potentiated glucose deprivation-induced death of astrocytes after induction of iNOS. Journal of Neuroscience Research. 54(6). 870–875. 32 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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