Young‐Kook Kim

2.2k total citations · 1 hit paper
69 papers, 1.4k citations indexed

About

Young‐Kook Kim is a scholar working on Molecular Biology, Cancer Research and Surgery. According to data from OpenAlex, Young‐Kook Kim has authored 69 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Molecular Biology, 34 papers in Cancer Research and 8 papers in Surgery. Recurrent topics in Young‐Kook Kim's work include MicroRNA in disease regulation (24 papers), Cancer-related molecular mechanisms research (22 papers) and Circular RNAs in diseases (17 papers). Young‐Kook Kim is often cited by papers focused on MicroRNA in disease regulation (24 papers), Cancer-related molecular mechanisms research (22 papers) and Circular RNAs in diseases (17 papers). Young‐Kook Kim collaborates with scholars based in South Korea, Australia and Puerto Rico. Young‐Kook Kim's co-authors include Juhyun Song, Hyun Kook, Gwangho Yoon, Juhee Ryu, Duk‐Hwa Kwon, Oh Yoen Kim, Youngkeun Ahn, Woo Jin Park, Kwang Il Nam and Byoung‐Mog Kwon and has published in prestigious journals such as Nature Communications, The Journal of Immunology and PLoS ONE.

In The Last Decade

Young‐Kook Kim

68 papers receiving 1.4k citations

Hit Papers

RNA therapy: rich history, various applications and unlim... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Young‐Kook Kim South Korea 23 851 450 114 112 95 69 1.4k
Haijun Li China 18 844 1.0× 393 0.9× 160 1.4× 111 1.0× 57 0.6× 62 1.3k
Xiaoyan Zhou China 23 799 0.9× 312 0.7× 152 1.3× 53 0.5× 94 1.0× 55 1.5k
Yue Du China 24 1.0k 1.2× 574 1.3× 58 0.5× 150 1.3× 72 0.8× 80 1.6k
Zhengrong Zhang China 23 720 0.8× 204 0.5× 107 0.9× 121 1.1× 128 1.3× 80 1.5k
Lihua Yang China 18 648 0.8× 349 0.8× 163 1.4× 220 2.0× 54 0.6× 62 1.5k
Kemal Uğur Tüfekçi Türkiye 17 1.3k 1.5× 663 1.5× 187 1.6× 211 1.9× 86 0.9× 32 2.1k
Shuo Li China 20 597 0.7× 219 0.5× 313 2.7× 89 0.8× 83 0.9× 109 1.4k
Giovanni Vanni Frajese Italy 18 1.2k 1.4× 743 1.7× 119 1.0× 84 0.8× 72 0.8× 33 2.0k
Mariasole Perrone Italy 18 1.3k 1.5× 230 0.5× 268 2.4× 203 1.8× 95 1.0× 34 1.9k
Yiming Zhou China 25 1.3k 1.5× 395 0.9× 260 2.3× 194 1.7× 89 0.9× 67 2.5k

Countries citing papers authored by Young‐Kook Kim

Since Specialization
Citations

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

Fields of papers citing papers by Young‐Kook Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Young‐Kook Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Young‐Kook Kim. A scholar is included among the top collaborators of Young‐Kook 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 Young‐Kook Kim. Young‐Kook 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.
Kim, Young‐Kook, et al.. (2025). High-fat diet triggers transcriptomic changes in the olfactory bulb. Heliyon. 11(3). e42196–e42196. 1 indexed citations
2.
Kwon, Duk‐Hwa, Sera Shin, Nakwon Choe, et al.. (2024). CBL-b E3 ligase-mediated neddylation and activation of PARP-1 induce vascular calcification. Experimental & Molecular Medicine. 56(10). 2246–2259. 2 indexed citations
3.
Park, Mi‐Ra, Kyung Hyun Yoo, Young‐Kook Kim, et al.. (2024). NRXN1 as a Prognostic Biomarker: Linking Copy Number Variation to EMT and Survival in Colon Cancer. International Journal of Molecular Sciences. 25(21). 11423–11423.
4.
Kim, Young‐Kook, et al.. (2024). Identification of IGF-1 Effects on White Adipose Tissue and Hippocampus in Alzheimer’s Disease Mice via Transcriptomic and Cellular Analysis. International Journal of Molecular Sciences. 25(5). 2567–2567. 5 indexed citations
6.
Yoon, Gwangho, Juhyun Song, Yong Sook Kim, et al.. (2023). Human lncRNA SUGCT-AS1 Regulates the Proinflammatory Response of Macrophage. International Journal of Molecular Sciences. 24(17). 13315–13315. 6 indexed citations
7.
Kim, Young‐Kook, et al.. (2023). Roles of non-coding RNAs in intercellular crosstalk in cardiovascular diseases. Korean Journal of Physiology and Pharmacology. 27(4). 289–298. 3 indexed citations
8.
Jo, Danbi, et al.. (2023). Profiling and Cellular Analyses of Obesity-Related circRNAs in Neurons and Glia under Obesity-like In Vitro Conditions. International Journal of Molecular Sciences. 24(7). 6235–6235. 2 indexed citations
9.
Kim, Boseon, et al.. (2023). H19X-encoded microRNAs induced by IL-4 in adipocyte precursors regulate proliferation to facilitate differentiation. Biology Direct. 18(1). 32–32. 1 indexed citations
10.
Kim, Young‐Kook, Yoon Seok Jung, & Juhyun Song. (2022). Transcriptome Profile in the Mouse Brain of Hepatic Encephalopathy and Alzheimer’s Disease. International Journal of Molecular Sciences. 24(1). 675–675. 5 indexed citations
11.
Cheon, So Yeong, Danbi Jo, Young‐Kook Kim, & Juhyun Song. (2022). Long Noncoding RNAs Regulate Hyperammonemia‐Induced Neuronal Damage in Hepatic Encephalopathy. Oxidative Medicine and Cellular Longevity. 2022(1). 7628522–7628522. 11 indexed citations
12.
Kim, Young‐Kook. (2022). RNA therapy: rich history, various applications and unlimited future prospects. Experimental & Molecular Medicine. 54(4). 455–465. 157 indexed citations breakdown →
13.
Kim, Sukjun, Soyoung Kim, Doyeon Kim, et al.. (2021). The regulatory impact of RNA-binding proteins on microRNA targeting. Nature Communications. 12(1). 5057–5057. 55 indexed citations
14.
Ryu, Juhee, Nakwon Choe, Duk‐Hwa Kwon, et al.. (2021). Circular RNA circSmoc1-2 regulates vascular calcification by acting as a miR-874-3p sponge in vascular smooth muscle cells. Molecular Therapy — Nucleic Acids. 27. 645–655. 17 indexed citations
15.
Mun, Seog‐Kyun, et al.. (2020). MicroRNAs Related to Cognitive Impairment After Hearing Loss. Clinical and Experimental Otorhinolaryngology. 14(1). 76–81. 8 indexed citations
16.
Nam, Kwang Il, Gwangho Yoon, Young‐Kook Kim, & Juhyun Song. (2020). Transcriptome Analysis of Pineal Glands in the Mouse Model of Alzheimer’s Disease. Frontiers in Molecular Neuroscience. 12. 318–318. 7 indexed citations
17.
Jeong, Geon, Duk‐Hwa Kwon, Sera Shin, et al.. (2019). Long noncoding RNAs in vascular smooth muscle cells regulate vascular calcification. Scientific Reports. 9(1). 5848–5848. 33 indexed citations
18.
Kim, Young‐Kook & Hyun Kook. (2019). Diverse roles of noncoding RNAs in vascular calcification. Archives of Pharmacal Research. 42(3). 244–251. 21 indexed citations
19.
Kim, Young‐Kook, Kwang Il Nam, & Juhyun Song. (2018). The Glymphatic System in Diabetes-Induced Dementia. Frontiers in Neurology. 9. 867–867. 33 indexed citations
20.
Kwon, Byoung‐Mog, Mi-Kyoung Kim, Jiyoun Nam, et al.. (1997). Polyacetylene Analogs, Isolated from Hairy Roots ofPanax ginseng, Inhibit Acyl-CoA : Cholesterol Acyltransferase. Planta Medica. 63(6). 552–553. 31 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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