Ethan A. Kohn

950 total citations
10 papers, 803 citations indexed

About

Ethan A. Kohn is a scholar working on Oncology, Molecular Biology and Surgery. According to data from OpenAlex, Ethan A. Kohn has authored 10 papers receiving a total of 803 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Oncology, 7 papers in Molecular Biology and 1 paper in Surgery. Recurrent topics in Ethan A. Kohn's work include Cancer Cells and Metastasis (5 papers), Cancer-related Molecular Pathways (4 papers) and DNA Repair Mechanisms (3 papers). Ethan A. Kohn is often cited by papers focused on Cancer Cells and Metastasis (5 papers), Cancer-related Molecular Pathways (4 papers) and DNA Repair Mechanisms (3 papers). Ethan A. Kohn collaborates with scholars based in United States, South Korea and Malaysia. Ethan A. Kohn's co-authors include Alan Eastman, P. Bagavandoss, Max S. Wicha, Lalage M. Wakefield, Jeong‐Seok Nam, Mark Livingstone, Mi‐Jin Kang, Binwu Tang, Christina H. Stuelten and Mizuko Mamura and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Cancer Research.

In The Last Decade

Ethan A. Kohn

10 papers receiving 765 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ethan A. Kohn United States 9 516 402 119 98 88 10 803
Jeou-Yuan Chen Taiwan 15 606 1.2× 265 0.7× 164 1.4× 115 1.2× 139 1.6× 26 986
Florence A. Scholl Switzerland 16 826 1.6× 249 0.6× 178 1.5× 168 1.7× 148 1.7× 20 1.2k
Cheryl McFarlane United Kingdom 14 460 0.9× 246 0.6× 132 1.1× 102 1.0× 128 1.5× 19 680
Lorena Benedetti Argentina 14 473 0.9× 303 0.8× 71 0.6× 62 0.6× 187 2.1× 16 865
Yamina Hamma‐Kourbali France 17 600 1.2× 215 0.5× 192 1.6× 83 0.8× 186 2.1× 25 966
Jennifer L. Brockman United States 11 432 0.8× 251 0.6× 178 1.5× 46 0.5× 63 0.7× 13 683
Thomas W. Owens United Kingdom 14 542 1.1× 199 0.5× 93 0.8× 97 1.0× 98 1.1× 18 742
Quanhong Sun United States 16 599 1.2× 264 0.7× 65 0.5× 109 1.1× 164 1.9× 28 936
Chantal Vercamer France 19 550 1.1× 170 0.4× 170 1.4× 163 1.7× 171 1.9× 22 978
Isere Kuiatse United States 16 682 1.3× 268 0.7× 85 0.7× 52 0.5× 172 2.0× 36 946

Countries citing papers authored by Ethan A. Kohn

Since Specialization
Citations

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

Fields of papers citing papers by Ethan A. Kohn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ethan A. Kohn. 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 Ethan A. Kohn. The network helps show where Ethan A. Kohn may publish in the future.

Co-authorship network of co-authors of Ethan A. Kohn

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

All Works

10 of 10 papers shown
1.
Kohn, Ethan A., Yu-an Yang, Zhijun Du, et al.. (2012). Biological Responses to TGF-β in the Mammary Epithelium Show a Complex Dependency on Smad3 Gene Dosage with Important Implications for Tumor Progression. Molecular Cancer Research. 10(10). 1389–1399. 20 indexed citations
2.
Kohn, Ethan A., Zhijun Du, Misako Sato, et al.. (2010). A novel approach for the generation of genetically modified mammary epithelial cell cultures yields new insights into TGFβ signaling in the mammary gland. Breast Cancer Research. 12(5). 22 indexed citations
3.
Kim, Ran‐Ju, Soo‐Rim Kim, Sang‐Bum Park, et al.. (2009). Ras activation contributes to the maintenance and expansion of Sca-1pos cells in a mouse model of breast cancer. Cancer Letters. 287(2). 172–181. 30 indexed citations
4.
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
5.
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
6.
Kohn, Ethan A., et al.. (2004). The Cellular Microenvironment. Nova Science Publishers (Nova Science Publishers, Inc.). 1 indexed citations
7.
Kohn, Ethan A., et al.. (2003). The protein kinase C inhibitor Gö6976 is a potent inhibitor of DNA damage-induced S and G2 cell cycle checkpoints.. PubMed. 63(1). 31–5. 114 indexed citations
9.
Eastman, Alan, et al.. (2002). A novel indolocarbazole, ICP-1, abrogates DNA damage-induced cell cycle arrest and enhances cytotoxicity: similarities and differences to the cell cycle checkpoint abrogator UCN-01.. PubMed. 1(12). 1067–78. 34 indexed citations
10.
Wicha, Max S., et al.. (1982). Extracellular matrix promotes mammary epithelial growth and differentiation in vitro.. Proceedings of the National Academy of Sciences. 79(10). 3213–3217. 216 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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