Sung‐Jin Kim

1.6k total citations
25 papers, 1.2k citations indexed

About

Sung‐Jin Kim is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Cell Biology. According to data from OpenAlex, Sung‐Jin Kim has authored 25 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 6 papers in Cardiology and Cardiovascular Medicine and 4 papers in Cell Biology. Recurrent topics in Sung‐Jin Kim's work include Receptor Mechanisms and Signaling (4 papers), Cholinesterase and Neurodegenerative Diseases (3 papers) and Adipose Tissue and Metabolism (3 papers). Sung‐Jin Kim is often cited by papers focused on Receptor Mechanisms and Signaling (4 papers), Cholinesterase and Neurodegenerative Diseases (3 papers) and Adipose Tissue and Metabolism (3 papers). Sung‐Jin Kim collaborates with scholars based in South Korea, United States and China. Sung‐Jin Kim's co-authors include Natesan Vijayakumar, Yang K. Xiang, David Ziring, Sheetal Desai, David W. Gjertson, Ram Raj Singh, Yael Korin, Maida Wong, Elaine F. Reed and Jonathan Braun and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Circulation.

In The Last Decade

Sung‐Jin Kim

25 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sung‐Jin Kim South Korea 17 491 271 182 169 148 25 1.2k
Yeon Jin Jang South Korea 19 346 0.7× 180 0.7× 270 1.5× 117 0.7× 116 0.8× 54 990
Yuqi Fan China 23 599 1.2× 347 1.3× 79 0.4× 138 0.8× 177 1.2× 65 1.3k
Weitao Cong China 24 1.0k 2.1× 138 0.5× 129 0.7× 163 1.0× 127 0.9× 79 1.8k
Gergő Szűcs Hungary 18 341 0.7× 222 0.8× 188 1.0× 160 0.9× 68 0.5× 32 1.0k
Meng Yuan China 21 503 1.0× 260 1.0× 101 0.6× 113 0.7× 120 0.8× 68 1.2k
Junjie Guo China 17 633 1.3× 176 0.6× 100 0.5× 114 0.7× 191 1.3× 49 1.2k
Emma Yu United Kingdom 8 674 1.4× 139 0.5× 255 1.4× 116 0.7× 277 1.9× 11 1.2k
Meilei Ma Japan 27 603 1.2× 753 2.8× 182 1.0× 144 0.9× 220 1.5× 58 1.6k
Yasuhiko Ikeda Japan 21 436 0.9× 139 0.5× 92 0.5× 147 0.9× 120 0.8× 51 1.5k
Jian Feng China 22 706 1.4× 181 0.7× 142 0.8× 184 1.1× 306 2.1× 61 1.6k

Countries citing papers authored by Sung‐Jin Kim

Since Specialization
Citations

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

Fields of papers citing papers by Sung‐Jin Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sung‐Jin Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Sung‐Jin Kim. A scholar is included among the top collaborators of Sung‐Jin 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 Sung‐Jin Kim. Sung‐Jin 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.
Selitsky, Sara R., et al.. (2023). FcεRIγ-negative NK cells and association with improved outcomes in trastuzumab-treated patients.. Journal of Clinical Oncology. 41(16_suppl). e12538–e12538. 1 indexed citations
2.
Vijayakumar, Natesan & Sung‐Jin Kim. (2022). The Trend of Organic Based Nanoparticles in the Treatment of Diabetes and Its Perspectives. Biomolecules & Therapeutics. 31(1). 16–26. 22 indexed citations
3.
Vijayakumar, Natesan & Sung‐Jin Kim. (2021). Lipid Metabolism, Disorders and Therapeutic Drugs - Review. Biomolecules & Therapeutics. 29(6). 596–604. 95 indexed citations
4.
Shi, Qian, Minghui Li, Delphine Mika, et al.. (2017). Heterologous desensitization of cardiac β-adrenergic signal via hormone-induced βAR/arrestin/PDE4 complexes. Cardiovascular Research. 113(6). 656–670. 41 indexed citations
5.
Ramalingam, Mahesh, Yong‐Dae Kwon, & Sung‐Jin Kim. (2016). Insulin as a Potent Stimulator of Akt, ERK and Inhibin-βE Signaling in Osteoblast-Like UMR-106 Cells. Biomolecules & Therapeutics. 24(6). 589–594. 6 indexed citations
6.
Ramalingam, Mahesh, et al.. (2015). Insulin stimulates integrin-linked kinase in UMR-106 cells: potential role of heparan sulfate on syndecan-1. Journal of Receptors and Signal Transduction. 35(6). 613–617. 7 indexed citations
7.
Fu, Qin, Sung‐Jin Kim, Dagoberto Soto, et al.. (2014). A Long Lasting β1 Adrenergic Receptor Stimulation of cAMP/Protein Kinase A (PKA) Signal in Cardiac Myocytes. Journal of Biological Chemistry. 289(21). 14771–14781. 27 indexed citations
8.
Lim, Ji‐Hong, Zachary Gerhart‐Hines, John E. Dominy, et al.. (2013). Oleic Acid Stimulates Complete Oxidation of Fatty Acids through Protein Kinase A-dependent Activation of SIRT1-PGC1α Complex. Journal of Biological Chemistry. 288(10). 7117–7126. 162 indexed citations
9.
Alexopoulos, Nikolaos, Chesnal Arepalli, Zhengjia Chen, et al.. (2013). Effect of Intensive Versus Moderate Lipid-Lowering Therapy on Epicardial Adipose Tissue in Hyperlipidemic Post-Menopausal Women. Journal of the American College of Cardiology. 61(19). 1956–1961. 131 indexed citations
10.
Kim, Sung‐Jin, et al.. (2012). Association of insulin receptor and syndecan-1 by insulin with activation of ERK I/II in osteoblast-like UMR-106 cells. Journal of Receptors and Signal Transduction. 33(1). 37–40. 6 indexed citations
11.
Kim, Sung‐Jin, et al.. (2010). Insulin stimulates gene expression of ferritin light chain in osteoblast cells. Journal of Cellular Biochemistry. 111(6). 1493–1500. 10 indexed citations
12.
Kim, Sung‐Jin & Keun Lee. (2008). Extracts of Liriopsis tuber protect AMPA induced brain damage and improve memory with the activation of insulin receptor and ERK I/II. Phytotherapy Research. 22(11). 1450–1457. 5 indexed citations
13.
Wong, Maida, David Ziring, Yael Korin, et al.. (2007). TNFα blockade in human diseases: Mechanisms and future directions. Clinical Immunology. 126(2). 121–136. 236 indexed citations
14.
Kim, Sung‐Jin, et al.. (2003). Nuclear matrix association of insulin receptor and IRS-1 by insulin in osteoblast-like UMR-106 cells. Biochemical and Biophysical Research Communications. 306(4). 898–904. 26 indexed citations
15.
16.
Kim, Sung‐Jin, et al.. (2003). Mechanism of anti-nociceptive effects of Asarum sieboldii Miq. Radix: potential role of bradykinin, histamine and opioid receptor-mediated pathways. Journal of Ethnopharmacology. 88(1). 5–9. 45 indexed citations
17.
18.
Kim, Sung‐Jin & Mi‐Sun Kim. (2000). Inhibitory effects of Cimicifugae rhizoma extracts on histamine, bradykinin and COX-2 mediated inflammatory actions. Phytotherapy Research. 14(8). 596–600. 26 indexed citations
19.
Lee, Young‐Mi, et al.. (2000). Water extract of 1:1 mixture of Phellodendron cortex and Aralia cortex has inhibitory effects on oxidative stress in kidney of diabetic rats. Journal of Ethnopharmacology. 73(3). 429–436. 49 indexed citations
20.
Kim, Sung‐Jin & C. Ronald Kahn. (1993). Insulin induces rapid accumulation of insulin receptors and increases tyrosine kinase activity in the nucleus of cultured adipocytes. Journal of Cellular Physiology. 157(2). 217–228. 28 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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