Dae Joon Kim

3.7k total citations
87 papers, 2.4k citations indexed

About

Dae Joon Kim is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Dae Joon Kim has authored 87 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Molecular Biology, 25 papers in Oncology and 13 papers in Cancer Research. Recurrent topics in Dae Joon Kim's work include Cytokine Signaling Pathways and Interactions (14 papers), Protein Tyrosine Phosphatases (13 papers) and PI3K/AKT/mTOR signaling in cancer (12 papers). Dae Joon Kim is often cited by papers focused on Cytokine Signaling Pathways and Interactions (14 papers), Protein Tyrosine Phosphatases (13 papers) and PI3K/AKT/mTOR signaling in cancer (12 papers). Dae Joon Kim collaborates with scholars based in United States, South Korea and United Kingdom. Dae Joon Kim's co-authors include John DiGiovanni, Jeffrey M. Peters, Mihwa Kim, Frank J. Gonzalez, Liza D. Morales, Ik‐Soon Jang, Yong‐Yeon Cho, Shigetoshi Sano, Thomas J. Slaga and Minwoo Baek and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Dae Joon Kim

83 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dae Joon Kim United States 28 1.5k 681 551 372 240 87 2.4k
Haibin Wang China 27 1.5k 1.0× 329 0.5× 471 0.9× 165 0.4× 123 0.5× 130 2.5k
Joyce E. Rundhaug United States 22 1.1k 0.8× 451 0.7× 599 1.1× 231 0.6× 121 0.5× 41 2.3k
Katiuscia Dallaglio Italy 21 1.0k 0.7× 644 0.9× 395 0.7× 300 0.8× 164 0.7× 31 1.8k
Gang Huang China 31 1.4k 1.0× 572 0.8× 1.0k 1.9× 559 1.5× 351 1.5× 86 2.8k
Monica Morini Italy 29 1.2k 0.8× 635 0.9× 510 0.9× 481 1.3× 182 0.8× 46 2.8k
Christian Ploner Austria 27 1.3k 0.9× 473 0.7× 436 0.8× 407 1.1× 185 0.8× 59 2.5k
Zheng Wu China 30 1.8k 1.2× 505 0.7× 1.1k 1.9× 258 0.7× 198 0.8× 102 3.1k
Yuko Ito Japan 28 1.4k 0.9× 226 0.3× 756 1.4× 281 0.8× 426 1.8× 103 2.3k
Rainer Zenz Austria 16 1.3k 0.8× 758 1.1× 370 0.7× 733 2.0× 227 0.9× 20 2.6k

Countries citing papers authored by Dae Joon Kim

Since Specialization
Citations

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

Fields of papers citing papers by Dae Joon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae Joon 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 Dae Joon Kim. The network helps show where Dae Joon Kim may publish in the future.

Co-authorship network of co-authors of Dae Joon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Dae Joon Kim. A scholar is included among the top collaborators of Dae Joon 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 Dae Joon Kim. Dae Joon 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.
Alvi, Sahir Sultan, Anupam Dhasmana, Murali M. Yallapu, et al.. (2025). Mitochondrial ribosomal protein L3 (MRPL3): An early diagnostic biomarker and potential molecular target in pancreatic cancer. Translational Oncology. 58. 102432–102432.
2.
Alvi, Sahir Sultan, Andrew E. Massey, Vivek K. Kashyap, et al.. (2025). Ubiquitination of Oncogenic Mutant p53 via Attenuation of Ribosome Biogenesis Machinery Effectively Inhibits Pancreatic Tumor Growth. Molecular Cancer Therapeutics. 25(2). 257–271.
3.
Kim, Bo Hyun, Dae Joon Kim, Bu Gyeom Kim, et al.. (2024). Daunorubicin induces GLI1‑dependent apoptosis in colorectal cancer cell lines. International Journal of Oncology. 64(6). 1 indexed citations
4.
Lee, Ga-Eun, Geul Bang, Cheol‐Jung Lee, et al.. (2024). Dysregulated CREB3 cleavage at the nuclear membrane induces karyoptosis-mediated cell death. Experimental & Molecular Medicine. 56(3). 686–699. 6 indexed citations
5.
Alvi, Sahir Sultan, et al.. (2024). Honey Targets Ribosome Biogenesis Components to Suppress the Growth of Human Pancreatic Cancer Cells. Cancers. 16(19). 3431–3431. 4 indexed citations
6.
Bergerhoff, Katharina, Shane Foo, Emmanuel C. Patin, et al.. (2020). Combining BRAF inhibition with oncolytic herpes simplex virus enhances the immune-mediated antitumor therapy of BRAF-mutant thyroid cancer. Journal for ImmunoTherapy of Cancer. 8(2). e000698–e000698. 24 indexed citations
7.
Fleming, Jason C., Jeongmin Woo, Karwan Moutasim, et al.. (2020). CTEN Induces Tumour Cell Invasion and Survival and Is Prognostic in Radiotherapy-Treated Head and Neck Cancer. Cancers. 12(10). 2963–2963. 8 indexed citations
8.
Park, Soo-Jung, Eunbi Jo, Kyung‐Bok Lee, et al.. (2018). Cordycepin induces apoptosis of human ovarian cancer cells by inhibiting CCL5-mediated Akt/NF-κB signaling pathway. Cell Death Discovery. 4(1). 62–62. 44 indexed citations
9.
Kim, Mihwa, Seungho Choi, Hyunseung Lee, et al.. (2016). GFRA1 promotes cisplatin-induced chemoresistance in osteosarcoma by inducing autophagy. Autophagy. 13(1). 149–168. 132 indexed citations
10.
Zhang, Yinghao, Jianjun Huang, Shivani Kaushal Maffi, et al.. (2014). DSSylation, a novel protein modification targets proteins induced by oxidative stress, and facilitates their degradation in cells. Protein & Cell. 5(2). 124–140. 9 indexed citations
11.
Kim, Hye Ryun, Byoung Chul Cho, Hyo Sup Shim, et al.. (2014). Prediction for response duration to epidermal growth factor receptor-tyrosine kinase inhibitors in EGFR mutated never smoker lung adenocarcinoma. Lung Cancer. 83(3). 374–382. 35 indexed citations
12.
Zloza, Andrew, Dae Joon Kim, Seunghee Kim‐Schulze, et al.. (2014). Immunoglobulin-like transcript 2 (ILT2) is a biomarker of therapeutic response to oncolytic immunotherapy with vaccinia viruses. Journal for ImmunoTherapy of Cancer. 2(1). 1–1. 38 indexed citations
13.
Malik, Gunjan, et al.. (2013). Resveratrol and P-glycoprotein Inhibitors Enhance the Anti-Skin Cancer Effects of Ursolic Acid. Molecular Cancer Research. 11(12). 1521–1529. 26 indexed citations
14.
Cho, Kyu-Won, Jung‐Hyun Park, Dae Joon Kim, et al.. (2012). Identification of a pivotal endocytosis motif in c-Met and selective modulation of HGF-dependent aggressiveness of cancer using the 16-mer endocytic peptide. Oncogene. 32(8). 1018–1029. 10 indexed citations
15.
Rho, Okkyung, et al.. (2010). Growth factor signaling pathways as targets for prevention of epithelial carcinogenesis. Molecular Carcinogenesis. 50(4). 264–279. 66 indexed citations
16.
Kim, Dae Joon, Ken Kataoka, Shigetoshi Sano, et al.. (2009). Targeted disruption of Bcl‐xL in mouse keratinocytes inhibits both UVB‐ and chemically induced skin carcinogenesis. Molecular Carcinogenesis. 48(10). 873–885. 30 indexed citations
17.
18.
Kim, Dae Joon, et al.. (2007). 골육종 환자의 반복적 폐전이 절제술. The Korean Journal of Thoracic and Cardiovascular Surgery. 40(9). 607–612.
19.
Kim, Dae Joon, Taro E. Akiyama, F. S. Harman, et al.. (2004). Peroxisome Proliferator-activated Receptor β (δ)-dependent Regulation of Ubiquitin C Expression Contributes to Attenuation of Skin Carcinogenesis. Journal of Biological Chemistry. 279(22). 23719–23727. 82 indexed citations
20.
Ryu, Hyun, Hwan Kim, Kug Sun Hong, et al.. (2003). Characterization of CaO-SiO<sub>2</sub>-B<sub>2</sub>O<sub>3</sub> Glass-Ceramics and Effect of Composition on Bioactivity. Key engineering materials. 240-242. 261–264. 4 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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