Suki Kang

2.6k total citations
54 papers, 2.1k citations indexed

About

Suki Kang is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Suki Kang has authored 54 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 25 papers in Oncology and 17 papers in Cancer Research. Recurrent topics in Suki Kang's work include Cancer Cells and Metastasis (14 papers), MicroRNA in disease regulation (6 papers) and Cellular Mechanics and Interactions (6 papers). Suki Kang is often cited by papers focused on Cancer Cells and Metastasis (14 papers), MicroRNA in disease regulation (6 papers) and Cellular Mechanics and Interactions (6 papers). Suki Kang collaborates with scholars based in South Korea, Spain and China. Suki Kang's co-authors include Nam Hoon Cho, Baek Gil Kim, Yoon Pyo Choi, Ming-Qing Gao, N. H. Cho, Ju Ho Youn, Joo Hyun Lee, Yeonsue Jang, Hyun Ho Han and Dong Su Kim and has published in prestigious journals such as Cancer, Cancer Research and Oncogene.

In The Last Decade

Suki Kang

54 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Suki Kang South Korea 27 1.2k 879 666 239 230 54 2.1k
Rainer Engers Germany 30 1.6k 1.4× 842 1.0× 622 0.9× 210 0.9× 89 0.4× 67 2.8k
Ying C. Henderson United States 25 1.3k 1.1× 1.0k 1.1× 509 0.8× 205 0.9× 67 0.3× 39 2.4k
Pornchai O‐charoenrat Thailand 28 1.6k 1.3× 1.5k 1.7× 905 1.4× 129 0.5× 99 0.4× 58 2.9k
Kai‐Tai Yao China 23 1.3k 1.1× 745 0.8× 770 1.2× 112 0.5× 120 0.5× 74 2.1k
Kerstin Borgmann Germany 32 1.8k 1.5× 1.2k 1.3× 712 1.1× 131 0.5× 96 0.4× 85 2.7k
Weiren Luo China 22 947 0.8× 732 0.8× 596 0.9× 124 0.5× 73 0.3× 42 1.7k
Li Yin China 27 1.4k 1.2× 505 0.6× 877 1.3× 113 0.5× 119 0.5× 99 2.0k
Yajun Yi United States 22 969 0.8× 389 0.4× 490 0.7× 88 0.4× 108 0.5× 31 1.7k
Masashi Idogawa Japan 28 1.4k 1.2× 573 0.7× 534 0.8× 216 0.9× 82 0.4× 75 2.0k
Pinaki Bose Canada 20 1.0k 0.9× 728 0.8× 357 0.5× 115 0.5× 91 0.4× 42 1.8k

Countries citing papers authored by Suki Kang

Since Specialization
Citations

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

Fields of papers citing papers by Suki Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suki Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Suki Kang. A scholar is included among the top collaborators of Suki Kang 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 Suki Kang. Suki Kang 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, Jong-Ho, Lucas Kreiß, Kevin C. Zhou, et al.. (2025). Semi-supervised virtual staining using learned-illumination Fourier ptychography for high-speed label-free histopathology. Journal of Physics Photonics. 8(1). 15025–15025. 1 indexed citations
2.
Jang, Yeonsue, et al.. (2024). Fibrosis‐Encapsulated Tumoroid, A Solid Cancer Assembloid Model for Cancer Research and Drug Screening. Advanced Healthcare Materials. 13(31). e2402391–e2402391. 5 indexed citations
3.
Kang, Chan Woo, Suki Kang, Yeonsue Jang, et al.. (2019). ITGB4-mediated metabolic reprogramming of cancer-associated fibroblasts. Oncogene. 39(3). 664–676. 133 indexed citations
4.
Kim, Baek Gil, Ming-Qing Gao, Suki Kang, et al.. (2017). Mechanical compression induces VEGFA overexpression in breast cancer via DNMT3A-dependent miR-9 downregulation. Cell Death and Disease. 8(3). e2646–e2646. 66 indexed citations
5.
Han, Hyun Ho, Sung Hwan Lee, Baek Gil Kim, et al.. (2016). Estrogen Receptor Status Predicts Late-Onset Skeletal Recurrence in Breast Cancer Patients. Medicine. 95(8). e2909–e2909. 15 indexed citations
6.
Lee, Joo Hyun, Ji Eun Kim, Baek Gil Kim, et al.. (2016). STAT3-induced WDR1 overexpression promotes breast cancer cell migration. Cellular Signalling. 28(11). 1753–1760. 26 indexed citations
7.
Kim, Dong Su, et al.. (2013). Composite Three-Marker Assay for Early Detection of Kidney Cancer. Cancer Epidemiology Biomarkers & Prevention. 22(3). 390–398. 47 indexed citations
8.
Choi, Yoon Pyo, Ming-Qing Gao, Suki Kang, et al.. (2013). CD24+ ovary cancer cells exhibit an invasive mesenchymal phenotype. Biochemical and Biophysical Research Communications. 432(2). 333–338. 34 indexed citations
9.
Gao, Ming-Qing, Baek Gil Kim, Suki Kang, et al.. (2013). Human breast cancer-associated fibroblasts enhance cancer cell proliferation through increased TGF-α cleavage by ADAM17. Cancer Letters. 336(1). 240–246. 35 indexed citations
10.
Kim, Baek Gil, Hee Jung An, Suki Kang, et al.. (2011). Laminin-332-Rich Tumor Microenvironment for Tumor Invasion in the Interface Zone of Breast Cancer. American Journal Of Pathology. 178(1). 373–381. 77 indexed citations
11.
Choi, Yoon Pyo, Hyo Sup Shim, Ming-Qing Gao, Suki Kang, & Nam Hoon Cho. (2011). Molecular portraits of intratumoral heterogeneity in human ovarian cancer. Cancer Letters. 307(1). 62–71. 52 indexed citations
12.
Kang, Suki, et al.. (2010). CD24+ cells from hierarchically organized ovarian cancer are enriched in cancer stem cells. Oncogene. 29(18). 2672–2680. 316 indexed citations
13.
Kim, Dong‐Su, et al.. (2008). NM23 as a prognostic biomarker in ovarian serous carcinoma. Modern Pathology. 21(7). 885–892. 20 indexed citations
14.
Kim, Se‐Heon, Bon Seok Koo, Suki Kang, et al.. (2007). HPV integration begins in the tonsillar crypt and leads to the alteration of p16, EGFR and c‐myc during tumor formation. International Journal of Cancer. 120(7). 1418–1425. 176 indexed citations
15.
Cho, Nam Hoon, Yoon Pyo Choi, Haeryoung Kim, et al.. (2006). Induction of cell apoptosis in non‐small cell lung cancer cells by cyclin A1 small interfering RNA. Cancer Science. 97(10). 1082–1092. 13 indexed citations
16.
Kang, Suki, Hong Bae Kim, Hee Jung Ahn, et al.. (2006). Methylation of p16INK4a Is a Non-Rare Event in Cervical Intraepithelial Neoplasia. Diagnostic Molecular Pathology. 15(2). 74–82. 26 indexed citations
17.
Cho, Nam Hoon, et al.. (2005). Genetic aberrance of sporadic MEN 2A component tumours: analysis of RET. Pathology. 37(1). 10–13. 11 indexed citations
18.
Cho, Nam Hoon, et al.. (2005). Elevation of cyclin B1, active cdc2, and HuR in cervical neoplasia with human papillomavirus type 18 infection. Cancer Letters. 232(2). 170–178. 26 indexed citations
19.
Cho, Nam Hoon, et al.. (2003). MMP expression profiling in recurred stage IB lung cancer. Oncogene. 23(3). 845–851. 52 indexed citations
20.
Song, Yanzhi, et al.. (1994). Human papillomavirus infection and the risk for cervical cancer in Korea. KRIBB Repository. 2 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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