Wan-Ju Kim

998 total citations
26 papers, 819 citations indexed

About

Wan-Ju Kim is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Wan-Ju Kim has authored 26 papers receiving a total of 819 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 6 papers in Oncology and 6 papers in Cancer Research. Recurrent topics in Wan-Ju Kim's work include DNA Repair Mechanisms (10 papers), Epigenetics and DNA Methylation (4 papers) and Cancer-related Molecular Pathways (4 papers). Wan-Ju Kim is often cited by papers focused on DNA Repair Mechanisms (10 papers), Epigenetics and DNA Methylation (4 papers) and Cancer-related Molecular Pathways (4 papers). Wan-Ju Kim collaborates with scholars based in United States, Türkiye and Germany. Wan-Ju Kim's co-authors include Kevin D. Brown, Yehia Daaka, Quynh N. Vo, Aaron W. Adamson, Rathinasamy Baskaran, Meena Shrivastav, Lingbao Ai, David G. Ginzinger, Donald A. Boudreau and Zachary C. Gersey and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Oncogene.

In The Last Decade

Wan-Ju Kim

24 papers receiving 808 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wan-Ju Kim United States 15 559 267 209 112 107 26 819
Shashwati Basak United States 9 665 1.2× 326 1.2× 261 1.2× 78 0.7× 70 0.7× 12 873
Helge Lind Norway 9 607 1.1× 250 0.9× 233 1.1× 93 0.8× 109 1.0× 9 810
Céline Levalois France 14 577 1.0× 258 1.0× 202 1.0× 93 0.8× 82 0.8× 18 878
Colleen H. Anna United States 16 647 1.2× 208 0.8× 212 1.0× 67 0.6× 60 0.6× 20 920
Yongping Cui China 20 640 1.1× 235 0.9× 191 0.9× 89 0.8× 61 0.6× 42 891
Ramakrishna Modali United States 13 458 0.8× 272 1.0× 226 1.1× 86 0.8× 95 0.9× 20 797
Constantinos G. Broustas United States 16 630 1.1× 195 0.7× 200 1.0× 136 1.2× 58 0.5× 27 894
Ishrat Mahjabeen Pakistan 19 683 1.2× 203 0.8× 348 1.7× 59 0.5× 83 0.8× 73 948
Xiaobo Cui China 18 574 1.0× 210 0.8× 319 1.5× 66 0.6× 46 0.4× 49 864
Irit Zurer Israel 10 590 1.1× 357 1.3× 228 1.1× 54 0.5× 102 1.0× 11 951

Countries citing papers authored by Wan-Ju Kim

Since Specialization
Citations

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

Fields of papers citing papers by Wan-Ju Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wan-Ju 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 Wan-Ju Kim. The network helps show where Wan-Ju Kim may publish in the future.

Co-authorship network of co-authors of Wan-Ju Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Wan-Ju Kim. A scholar is included among the top collaborators of Wan-Ju 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 Wan-Ju Kim. Wan-Ju 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.
Morozov, Viacheslav, Alberto Riva, Wan-Ju Kim, et al.. (2023). HIRA-mediated loading of histone variant H3.3 controls androgen-induced transcription by regulation of AR/BRD4 complex assembly at enhancers. Nucleic Acids Research. 51(19). 10194–10217. 6 indexed citations
2.
Kim, Wan-Ju, et al.. (2023). The Effects of CrossFit on Body Composition, Blood Pressure, and Blood Lipids of Men in Their 30s with Metabolic Syndrome. Journal of Coaching Development. 25(1). 254–265.
3.
Kim, Wan-Ju, et al.. (2019). A Study on Maturity Model for the Assessment of Cyber Resilience Level in the Defence Information System. Information Security and Cryptology. 29(5). 1153–1165. 1 indexed citations
4.
Kim, Wan-Ju, et al.. (2018). Uropathogenic Escherichia coli invades bladder epithelial cells by activating kinase networks in host cells. Journal of Biological Chemistry. 293(42). 16518–16527. 13 indexed citations
5.
Dyer, Lisa, Lingbao Ai, Wan-Ju Kim, et al.. (2017). ATM is required for SOD2 expression and homeostasis within the mammary gland. Breast Cancer Research and Treatment. 166(3). 725–741. 6 indexed citations
6.
Alpay, Merve, et al.. (2015). Oxidative stress shapes breast cancer phenotype through chronic activation of ATM-dependent signaling. Breast Cancer Research and Treatment. 151(1). 75–87. 32 indexed citations
7.
8.
Eruslanov, Evgeniy, Taryn Stoffs, Wan-Ju Kim, et al.. (2013). Expansion of CCR8+ Inflammatory Myeloid Cells in Cancer Patients with Urothelial and Renal Carcinomas. Clinical Cancer Research. 19(7). 1670–1680. 55 indexed citations
9.
Kim, Wan-Ju, Zachary C. Gersey, & Yehia Daaka. (2012). Rap1GAP regulates renal cell carcinoma invasion. Cancer Letters. 320(1). 65–71. 42 indexed citations
10.
Ai, Lingbao, Wan-Ju Kim, Berna Demircan, et al.. (2008). The transglutaminase 2 gene ( TGM2 ), a potential molecular marker for chemotherapeutic drug sensitivity, is epigenetically silenced in breast cancer. Carcinogenesis. 29(3). 510–518. 87 indexed citations
11.
Kim, Wan-Ju, Baskaran Rajasekaran, & Kevin D. Brown. (2007). MLH1- and ATM-dependent MAPK Signaling Is Activated through c-Abl in Response to the Alkylator N-Methyl-N′-nitro-N′-nitrosoguanidine. Journal of Biological Chemistry. 282(44). 32021–32031. 30 indexed citations
12.
Vo, Quynh N., Wan-Ju Kim, Andrew J. McWhorter, et al.. (2005). The ATM/p53 pathway is commonly targeted for inactivation in squamous cell carcinoma of the head and neck (SCCHN) by multiple molecular mechanisms. Oral Oncology. 41(10). 1013–1020. 46 indexed citations
13.
Vo, Quynh N., et al.. (2004). The ATM gene is a target for epigenetic silencing in locally advanced breast cancer. Oncogene. 23(58). 9432–9437. 87 indexed citations
14.
Kim, Wan-Ju, et al.. (2004). The monofunctional alkylating agent N-methyl-N′-nitro-N-nitrosoguanidine triggers apoptosis through p53-dependent and -independent pathways. Toxicology and Applied Pharmacology. 202(1). 84–98. 25 indexed citations
15.
Wakeman, Timothy P., et al.. (2004). The ATM-SMC1 pathway is essential for activation of the chromium[VI]-induced S-phase checkpoint. Mutation research. Fundamental and molecular mechanisms of mutagenesis. 554(1-2). 241–251. 50 indexed citations
16.
Kowbel, David, et al.. (2003). Characterization of the novel amplified in breast cancer-1 (NABC1) gene product. Experimental Cell Research. 290(2). 402–413. 29 indexed citations
17.
Kim, Wan-Ju, et al.. (2002). Aberrant methylation of the ATM promoter correlates with increased radiosensitivity in a human colorectal tumor cell line. Oncogene. 21(24). 3864–3871. 78 indexed citations
18.
Adamson, Aaron W., Wan-Ju Kim, Sanjeev Shangary, Rathinasamy Baskaran, & Kevin D. Brown. (2002). ATM Is Activated in Response toN-Methyl-N′-nitro- N-nitrosoguanidine-induced DNA Alkylation. Journal of Biological Chemistry. 277(41). 38222–38229. 54 indexed citations
19.
Kim, Wan-Ju, Meredith Wernick, Son Nguyen, et al.. (2001). Evidence for alternate splicing within the mRNA transcript encoding the DNA damage response kinase ATR. Gene. 272(1-2). 35–43. 9 indexed citations
20.
Kang, Jahyo, et al.. (1984). Oxygen-Directed Functionalization of Thiophene. Bulletin of the Korean Chemical Society. 5(2). 87–88. 1 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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