Jeong‐Seok Nam

5.3k total citations
88 papers, 4.2k citations indexed

About

Jeong‐Seok Nam is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Jeong‐Seok Nam has authored 88 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Molecular Biology, 40 papers in Oncology and 16 papers in Cancer Research. Recurrent topics in Jeong‐Seok Nam's work include Cancer Cells and Metastasis (29 papers), Wnt/β-catenin signaling in development and cancer (14 papers) and TGF-β signaling in diseases (12 papers). Jeong‐Seok Nam is often cited by papers focused on Cancer Cells and Metastasis (29 papers), Wnt/β-catenin signaling in development and cancer (14 papers) and TGF-β signaling in diseases (12 papers). Jeong‐Seok Nam collaborates with scholars based in South Korea, United States and Malaysia. Jeong‐Seok Nam's co-authors include So‐Yeon Park, Ji‐Youn Jung, Ran‐Ju Kim, In‐Sun Hong, Hwa‐Yong Lee, Setsuo Hirohashi, Sung‐Dae Cho, Yhun Yhong Sheen, Gyu-Beom Jang and Lalage M. Wakefield and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jeong‐Seok Nam

82 papers receiving 4.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeong‐Seok Nam South Korea 37 2.5k 1.9k 869 586 343 88 4.2k
Daniela Trisciuoglio Italy 35 2.9k 1.1× 1.1k 0.6× 951 1.1× 496 0.8× 307 0.9× 88 4.4k
Donatella Del Bufalo Italy 42 3.0k 1.2× 1.4k 0.8× 1.0k 1.2× 650 1.1× 350 1.0× 133 4.7k
Akeila Bellahcène Belgium 37 2.4k 1.0× 1.7k 0.9× 851 1.0× 412 0.7× 495 1.4× 67 4.5k
George G. Chen Hong Kong 31 2.2k 0.9× 862 0.5× 1.1k 1.3× 397 0.7× 421 1.2× 119 3.6k
Xian‐Jun Qu China 37 2.1k 0.8× 943 0.5× 987 1.1× 550 0.9× 229 0.7× 133 3.9k
Kangdong Liu China 33 2.4k 0.9× 1.0k 0.5× 769 0.9× 401 0.7× 483 1.4× 202 3.9k
Kuen‐Feng Chen Taiwan 43 3.1k 1.2× 1.6k 0.8× 975 1.1× 560 1.0× 582 1.7× 100 4.9k
Wen‐Chun Hung Taiwan 45 3.1k 1.2× 1.5k 0.8× 1.2k 1.4× 487 0.8× 367 1.1× 143 5.3k
Jörg Bäsecke Germany 22 3.0k 1.2× 1.2k 0.6× 669 0.8× 395 0.7× 338 1.0× 34 4.4k
Xiao‐Feng Zhu China 36 3.0k 1.2× 1.0k 0.5× 1.2k 1.4× 538 0.9× 346 1.0× 145 5.1k

Countries citing papers authored by Jeong‐Seok Nam

Since Specialization
Citations

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

Fields of papers citing papers by Jeong‐Seok Nam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeong‐Seok Nam. 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 Jeong‐Seok Nam. The network helps show where Jeong‐Seok Nam may publish in the future.

Co-authorship network of co-authors of Jeong‐Seok Nam

This figure shows the co-authorship network connecting the top 25 collaborators of Jeong‐Seok Nam. A scholar is included among the top collaborators of Jeong‐Seok Nam 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 Jeong‐Seok Nam. Jeong‐Seok Nam 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.
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.
2.
Kim, Jee‐Heun, et al.. (2024). The dysadherin/FAK axis promotes individual cell migration in colon cancer. International Journal of Biological Sciences. 20(7). 2356–2369.
3.
Choi, Jang-Hyun, So‐Yeon Park, Won‐Jae Lee, et al.. (2023). SEC22B inhibition attenuates colorectal cancer aggressiveness and autophagic flux under unfavorable environment. Biochemical and Biophysical Research Communications. 665. 10–18. 2 indexed citations
4.
Park, So‐Yeon, Kim J, Jee‐Heun Kim, et al.. (2018). Inhibition of LEF1-Mediated DCLK1 by Niclosamide Attenuates Colorectal Cancer Stemness. Clinical Cancer Research. 25(4). 1415–1429. 58 indexed citations
5.
Lee, Hwa‐Yong, et al.. (2016). HIF2α/EFEMP1 cascade mediates hypoxic effects on breast cancer stem cell hierarchy. Oncotarget. 7(28). 43518–43533. 13 indexed citations
6.
Jang, Gyu-Beom, In‐Sun Hong, Ran‐Ju Kim, et al.. (2015). Wnt/β-Catenin Small-Molecule Inhibitor CWP232228 Preferentially Inhibits the Growth of Breast Cancer Stem-like Cells. Cancer Research. 75(8). 1691–1702. 145 indexed citations
7.
An, Seong Soo A., Gyu-Beom Jang, Hwa‐Yong Lee, In‐Sun Hong, & Jeong‐Seok Nam. (2015). Targeting cancer stem cells by using the nanoparticles. International Journal of Nanomedicine. 10(Spec Iss). 251–251. 55 indexed citations
8.
Son, Ji Yeon, So-Yeon Park, Sang-A Park, et al.. (2014). EW-7197, a Novel ALK-5 Kinase Inhibitor, Potently Inhibits Breast to Lung Metastasis. Molecular Cancer Therapeutics. 13(7). 1704–1716. 91 indexed citations
9.
Choi, Eun‐Sun, Jeong‐Seok Nam, Ji‐Youn Jung, Nam‐Pyo Cho, & Sung‐Dae Cho. (2014). Modulation of specificity protein 1 by mithramycin A as a novel therapeutic strategy for cervical cancer. Scientific Reports. 4(1). 7162–7162. 76 indexed citations
10.
Sheen, Yhun Yhong, et al.. (2013). Targeting the Transforming Growth Factor-β Signaling in Cancer Therapy. Biomolecules & Therapeutics. 21(5). 323–331. 86 indexed citations
11.
Lee, Yoo‐Kyung, et al.. (2012). Dysadherin expression promotes the motility and survival of human breast cancer cells by AKT activation. Cancer Science. 103(7). 1280–1289. 30 indexed citations
12.
Nam, Jeong‐Seok, Masaki Terabe, Mizuko Mamura, et al.. (2008). An Anti–Transforming Growth Factor β Antibody Suppresses Metastasis via Cooperative Effects on Multiple Cell Compartments. Cancer Research. 68(10). 3835–3843. 187 indexed citations
13.
Nam, Jeong‐Seok, Masaki Terabe, Mi‐Jin Kang, et al.. (2008). Transforming Growth Factor β Subverts the Immune System into Directly Promoting Tumor Growth through Interleukin-17. Cancer Research. 68(10). 3915–3923. 198 indexed citations
14.
15.
Nam, Jeong‐Seok, Mi‐Jin Kang, Christina H. Stuelten, et al.. (2006). Bone Sialoprotein Mediates the Tumor Cell–Targeted Prometastatic Activity of Transforming Growth Factor β in a Mouse Model of Breast Cancer. Cancer Research. 66(12). 6327–6335. 72 indexed citations
16.
Nam, Jeong‐Seok, Mi‐Jin Kang, Takeshi Shimamura, et al.. (2006). Chemokine (C-C Motif) Ligand 2 Mediates the Prometastatic Effect of Dysadherin in Human Breast Cancer Cells. Cancer Research. 66(14). 7176–7184. 89 indexed citations
17.
Nam, Jeong‐Seok, et al.. (2004). Significance of dysadherin expression in breast cancer metastasis. Cancer Research. 64. 1163–1163.
18.
Nam, Jeong‐Seok, Yoshinori Ino, Michiie Sakamoto, & Setsuo Hirohashi. (2002). Ras Farnesylation Inhibitor FTI‐277 Restores the E‐Cadherin/Catenin Cell Adhesion System in Human Cancer Cells and Reduces Cancer Metastasis. Japanese Journal of Cancer Research. 93(9). 1020–1028. 25 indexed citations
19.
Lee, Yong‐Soon, et al.. (1996). Acute toxicity test with the Ginkgo biloba extract (EGb 761) in rats and rabbits. Laboratory Animal Research. 12(1). 131–134.
20.
Nam, Jeong‐Seok, et al.. (1995). 토끼에서의 Erythropoietin 정맥내 반복투여 독성에 관한 연구. Laboratory Animal Research. 11(2). 175–182.

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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