Seungyoon Nam

2.2k total citations
89 papers, 1.6k citations indexed

About

Seungyoon Nam is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Seungyoon Nam has authored 89 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 31 papers in Cancer Research and 24 papers in Oncology. Recurrent topics in Seungyoon Nam's work include MicroRNA in disease regulation (14 papers), Cancer-related molecular mechanisms research (11 papers) and RNA modifications and cancer (9 papers). Seungyoon Nam is often cited by papers focused on MicroRNA in disease regulation (14 papers), Cancer-related molecular mechanisms research (11 papers) and RNA modifications and cancer (9 papers). Seungyoon Nam collaborates with scholars based in South Korea, United States and China. Seungyoon Nam's co-authors include Kenneth P. Nephew, Dae Ho Lee, Sungjin Park, Yon Hui Kim, Sun Kim, Jinhyuk Lee, Jung Ho Kim, Kwangmin Choi, Curtis Balch and Meng Li and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Seungyoon Nam

82 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seungyoon Nam South Korea	24	1.0k	538	309	214	122	89	1.6k
Zheng Liu China	25	983 0.9×	448 0.8×	423 1.4×	238 1.1×	141 1.2×	75	1.6k
Jia Song China	25	1.2k 1.1×	718 1.3×	275 0.9×	215 1.0×	115 0.9×	99	1.8k
Adriane Feijó Evangelista Brazil	22	834 0.8×	622 1.2×	265 0.9×	128 0.6×	90 0.7×	75	1.4k
Li Su Taiwan	24	1.1k 1.1×	358 0.7×	388 1.3×	264 1.2×	120 1.0×	66	1.7k
Eunah Shin South Korea	24	784 0.8×	343 0.6×	353 1.1×	155 0.7×	143 1.2×	82	1.5k
Rong Ma China	25	1.0k 1.0×	798 1.5×	305 1.0×	125 0.6×	87 0.7×	71	1.6k
Qi Zhou China	21	1.0k 1.0×	649 1.2×	306 1.0×	119 0.6×	115 0.9×	91	1.5k
Kai‐Wen Hsu Taiwan	23	1.1k 1.1×	533 1.0×	280 0.9×	109 0.5×	74 0.6×	49	1.5k
Ming-Ming Tsai Taiwan	24	796 0.8×	558 1.0×	299 1.0×	133 0.6×	118 1.0×	41	1.4k
Shu Okamura Japan	16	1.2k 1.2×	433 0.8×	600 1.9×	158 0.7×	140 1.1×	72	1.8k

Countries citing papers authored by Seungyoon Nam

Since Specialization

Citations

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

Fields of papers citing papers by Seungyoon Nam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seungyoon Nam

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

All Works

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20 of 20 papers shown

Park, Il‐Kyu, et al.. (2025). Integrating E-cadherin expression levels with TNM staging for enhanced prognostic prediction in colorectal cancer patients. BMC Cancer. 25(1). 150–150. 2 indexed citations

Kim, Sung-Yeon, Soyeon Jeong, Kyoung Oh Kim, et al.. (2025). Elucidating prognostic significance of purine metabolism in colorectal cancer through integrating data from transcriptomic, immunohistochemical, and single‐cell RNA sequencing analysis. Molecular Oncology. 19(8). 2310–2329. 1 indexed citations

Wei, Shibo, Mi-Ju Park, Seungyoon Nam, et al.. (2024). CDKN2 expression is a potential biomarker for T cell exhaustion in hepatocellular carcinoma. BMB Reports. 57(6). 287–292.

Kwak, Sojung, et al.. (2024). Development of pluripotent stem cell-derived epidermal organoids that generate effective extracellular vesicles in skin regeneration. Biomaterials. 307. 122522–122522. 29 indexed citations

You, Ji Young, Kyong Hwa Park, Eun Sook Lee, et al.. (2023). Determining the Factors Predicting the Response to Anti-HER2 Therapy in HER2-Positive Breast Cancer Patients. Cancer Control. 30. 2905559720–2905559720.

Nam, Seungyoon, et al.. (2023). Network and Computational Drug Repurposing Analysis for c-Myc Inhibition in Burkitt Lymphoma. Cancer Genomics & Proteomics. 20(6suppl). 712–722.

Lee, Seung Hyeun, et al.. (2023). Urban dust particles disrupt mitotic progression by dysregulating Aurora kinase B-related functions. Journal of Hazardous Materials. 459. 132238–132238. 4 indexed citations

Jeong, Soyeon, Jungsuk An, Sungjin Park, et al.. (2023). Clinicopathologic Significance of Heat Shock Protein 60 as a Survival Predictor in Colorectal Cancer. Cancers. 15(16). 4052–4052. 5 indexed citations

Shin, Seung Kak, Seungyoon Nam, Seung Yeon Ha, et al.. (2023). Clinical Significance of Combined Epithelial–Mesenchymal Transition Markers Expression and Role of Rac1 in Hepatocellular Carcinoma. International Journal of Molecular Sciences. 24(2). 1765–1765. 4 indexed citations

10.

Jeong, Soyeon, Sungjin Park, Seungyoon Nam, et al.. (2023). Significance of 8-OHdG Expression as a Predictor of Survival in Colorectal Cancer. Cancers. 15(18). 4613–4613. 6 indexed citations

11.

Nam, Seungyoon, et al.. (2023). miRDM-rfGA: Genetic algorithm-based identification of a miRNA set for detecting type 2 diabetes. BMC Medical Genomics. 16(1). 195–195. 3 indexed citations

12.

Nam, Seungyoon, et al.. (2023). Review of Current Treatment Intensification Strategies for Prostate Cancer Patients. Cancers. 15(23). 5615–5615. 9 indexed citations

13.

Park, Sungjin, Jungsuk An, Seung Yeon Ha, Seungyoon Nam, & Jung Ho Kim. (2022). Immune signature as a potential marker for predicting response to immunotherapy in obesity‐associated colorectal cancer. Journal of Gastroenterology and Hepatology. 37(8). 1579–1587. 2 indexed citations

14.

Nam, Seungyoon, Sungyoung Lee, Sungjin Park, et al.. (2021). PATHOME-Drug: a subpathway-based polypharmacology drug-repositioning method. Bioinformatics. 38(2). 444–452. 7 indexed citations

15.

Son, Won‐Joon, Hyo Sug Lee, Gyutae Lim, et al.. (2019). A Deep Learning Model for Cell Growth Inhibition IC50 Prediction and Its Application for Gastric Cancer Patients. International Journal of Molecular Sciences. 20(24). 6276–6276. 34 indexed citations

16.

An, Jungsuk, Jun-Young Yang, Jun‐Won Chung, et al.. (2019). Sex-specific differences in risk factors of lymph node metastasis in patients with early gastric cancer. PLoS ONE. 14(10). e0224019–e0224019. 10 indexed citations

17.

Lee, Jin Sook, et al.. (2018). Comparison of Microbiota Variation in Korean Healthy Adolescents with Adults Suggests Notable Maturity Differences. OMICS A Journal of Integrative Biology. 22(12). 770–778. 4 indexed citations

18.

Chang, Hae Ryung, Seungyoon Nam, Hae Rim Jung, et al.. (2016). Improving gastric cancer preclinical studies using diverse in vitro and in vivo model systems. BMC Cancer. 16(1). 200–200. 12 indexed citations

19.

Nam, Seungyoon, Hong Chang, Kyong‐Tai Kim, et al.. (2014). PATHOME: an algorithm for accurately detecting differentially expressed subpathways. Oncogene. 33(41). 4941–4951. 51 indexed citations

20.

Kim, Bumjin, Hyun Joo Lee, Hye Young Choi, et al.. (2007). Clinical Validity of the Lung Cancer Biomarkers Identified by Bioinformatics Analysis of Public Expression Data. Cancer Research. 67(15). 7431–7438. 78 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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