Hong-Gu Lee

952 total citations · 1 hit paper
10 papers, 802 citations indexed

About

Hong-Gu Lee is a scholar working on Molecular Biology, Epidemiology and Physiology. According to data from OpenAlex, Hong-Gu Lee has authored 10 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Epidemiology and 4 papers in Physiology. Recurrent topics in Hong-Gu Lee's work include Adipokines, Inflammation, and Metabolic Diseases (4 papers), Fatty Acid Research and Health (4 papers) and Adipose Tissue and Metabolism (4 papers). Hong-Gu Lee is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (4 papers), Fatty Acid Research and Health (4 papers) and Adipose Tissue and Metabolism (4 papers). Hong-Gu Lee collaborates with scholars based in South Korea, United States and Japan. Hong-Gu Lee's co-authors include Daisuke Hishikawa, Sang-Gun Roh, Shinichi Sasaki, Ki-Choon Choi, Hiroaki Tsuzuki, Dan Feng, Chen Chen, Kazuo Katoh, Chong-Su Cho and Hyun‐Seuk Moon and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Endocrinology and Nutrients.

In The Last Decade

Hong-Gu Lee

10 papers receiving 779 citations

Hit Papers

Acetate and Propionate Short Chain Fatty Acids Stimulate ... 2005 2026 2012 2019 2005 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hong-Gu Lee South Korea 9 431 352 166 124 117 10 802
Karin Berger Sweden 19 518 1.2× 349 1.0× 152 0.9× 155 1.3× 107 0.9× 28 1.1k
Noemi González‐Abuín Spain 15 356 0.8× 180 0.5× 191 1.2× 71 0.6× 188 1.6× 18 835
Sally Tandy Australia 9 261 0.6× 198 0.6× 351 2.1× 120 1.0× 160 1.4× 11 838
Motohiro Maebuchi Japan 16 353 0.8× 204 0.6× 131 0.8× 91 0.7× 74 0.6× 27 770
Masaya Shimada Japan 16 288 0.7× 167 0.5× 76 0.5× 139 1.1× 136 1.2× 53 726
Cécile Vors France 17 377 0.9× 479 1.4× 369 2.2× 213 1.7× 163 1.4× 39 1.1k
Seiichi Kasaoka Japan 14 255 0.6× 295 0.8× 393 2.4× 57 0.5× 95 0.8× 26 966
Guowei Le China 15 403 0.9× 313 0.9× 95 0.6× 84 0.7× 57 0.5× 23 853
Mikko Griinari Italy 12 193 0.4× 257 0.7× 502 3.0× 88 0.7× 213 1.8× 16 1.1k
Megan R. Ruth Canada 16 245 0.6× 280 0.8× 306 1.8× 151 1.2× 142 1.2× 19 883

Countries citing papers authored by Hong-Gu Lee

Since Specialization
Citations

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

Fields of papers citing papers by Hong-Gu Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hong-Gu Lee. 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 Hong-Gu Lee. The network helps show where Hong-Gu Lee may publish in the future.

Co-authorship network of co-authors of Hong-Gu Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Hong-Gu Lee. A scholar is included among the top collaborators of Hong-Gu Lee 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 Hong-Gu Lee. Hong-Gu Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Wang, Tao, et al.. (2014). trans-11 18:1 Vaccenic Acid (TVA) Has a Direct Anti-Carcinogenic Effect on MCF-7 Human Mammary Adenocarcinoma Cells. Nutrients. 6(2). 627–636. 49 indexed citations
2.
Jin, Yongcheng, et al.. (2012). Functional study of Villin 2 protein expressed in longissimus dorsi muscle of Korean native cattle in different growth stages. BMB Reports. 45(2). 102–107. 3 indexed citations
3.
Moon, Hyun‐Seuk, et al.. (2008). Physico-chemical modifications of conjugated linoleic acid for ruminal protection and oxidative stability. Nutrition & Metabolism. 5(1). 16–16. 24 indexed citations
5.
Moon, Hyun‐Seuk, et al.. (2008). PEGylated conjugated linoleic acid stimulation of apoptosis via a p53-mediated signaling pathway in MCF-7 breast cancer cells. European Journal of Pharmaceutics and Biopharmaceutics. 70(2). 621–626. 21 indexed citations
6.
Moon, Hyun‐Seuk, et al.. (2007). Leptin-induced matrix metalloproteinase-2 secretion is suppressed by trans-10,cis-12 conjugated linoleic acid. Biochemical and Biophysical Research Communications. 356(4). 955–960. 18 indexed citations
7.
Moon, Hyun‐Seuk, Hong-Gu Lee, Yun-Jaie Choi, Tae Gyu Kim, & Chong-Su Cho. (2007). Proposed mechanisms of (−)-epigallocatechin-3-gallate for anti-obesity. Chemico-Biological Interactions. 167(2). 85–98. 117 indexed citations
8.
Hishikawa, Daisuke, Hiroaki Tsuzuki, Ki-Choon Choi, et al.. (2005). Up-regulation of adipogenin, an adipocyte plasma transmembrane protein, during adipogenesis. Molecular and Cellular Biochemistry. 276(1-2). 133–141. 25 indexed citations
9.
Hishikawa, Daisuke, Hiroaki Tsuzuki, Ki-Choon Choi, et al.. (2005). Acetate and Propionate Short Chain Fatty Acids Stimulate Adipogenesis via GPCR43. Endocrinology. 146(12). 5092–5099. 516 indexed citations breakdown →
10.
Hishikawa, Daisuke, Hiroaki Tsuzuki, Ki-Choon Choi, et al.. (2005). Up-Regulation of the Claudin-6 Gene in Adipogenesis. Bioscience Biotechnology and Biochemistry. 69(11). 2117–2121. 8 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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