Curtis H. Kugel

2.1k total citations
8 papers, 461 citations indexed

About

Curtis H. Kugel is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Curtis H. Kugel has authored 8 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Oncology and 4 papers in Computational Theory and Mathematics. Recurrent topics in Curtis H. Kugel's work include Melanoma and MAPK Pathways (5 papers), Computational Drug Discovery Methods (4 papers) and Immunotherapy and Immune Responses (3 papers). Curtis H. Kugel is often cited by papers focused on Melanoma and MAPK Pathways (5 papers), Computational Drug Discovery Methods (4 papers) and Immunotherapy and Immune Responses (3 papers). Curtis H. Kugel collaborates with scholars based in United States and Japan. Curtis H. Kugel's co-authors include Andrew E. Aplin, Ethan V. Abel, Ashani T. Weeraratna, Marie R. Webster, Xiaowei Xu, Edward J. Hartsough, Giorgos C. Karakousis, Adam Ertel, Kevin J. Basile and Agnieszka K. Witkiewicz and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Cancer Research.

In The Last Decade

Curtis H. Kugel

8 papers receiving 460 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Curtis H. Kugel United States 8 382 239 69 57 54 8 461
Aida Shahrabi Netherlands 6 308 0.8× 239 1.0× 118 1.7× 94 1.6× 42 0.8× 7 463
Andrew E. Aplin United States 15 604 1.6× 363 1.5× 106 1.5× 64 1.1× 104 1.9× 22 722
Samar Alanazi United States 8 347 0.9× 271 1.1× 58 0.8× 66 1.2× 29 0.5× 13 575
Jong Wook Kim United States 5 389 1.0× 254 1.1× 119 1.7× 89 1.6× 43 0.8× 5 555
Hanne Puntervoll Norway 7 321 0.8× 228 1.0× 57 0.8× 78 1.4× 19 0.4× 11 431
Marina Chan United States 10 331 0.9× 200 0.8× 46 0.7× 77 1.4× 18 0.3× 16 534
Timothy L. Helms United States 5 289 0.8× 275 1.2× 37 0.5× 54 0.9× 51 0.9× 6 452
Katja Muehlethaler Switzerland 6 422 1.1× 231 1.0× 87 1.3× 88 1.5× 55 1.0× 6 554
Shakuntala Tiwari United States 6 324 0.8× 367 1.5× 93 1.3× 132 2.3× 30 0.6× 6 561
Heidi Simmons United States 4 446 1.2× 296 1.2× 25 0.4× 57 1.0× 50 0.9× 11 596

Countries citing papers authored by Curtis H. Kugel

Since Specialization
Citations

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

Fields of papers citing papers by Curtis H. Kugel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Curtis H. Kugel. 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 Curtis H. Kugel. The network helps show where Curtis H. Kugel may publish in the future.

Co-authorship network of co-authors of Curtis H. Kugel

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

All Works

8 of 8 papers shown
1.
Douglass, Stephen M., Mitchell E. Fane, Emilio Sanseviero, et al.. (2020). Myeloid-Derived Suppressor Cells Are a Major Source of Wnt5A in the Melanoma Microenvironment and Depend on Wnt5A for Full Suppressive Activity. Cancer Research. 81(3). 658–670. 24 indexed citations
2.
Hartsough, Edward J., Michele B. Weiss, Timothy J. Purwin, et al.. (2019). CADM1 is a TWIST1-regulated suppressor of invasion and survival. Cell Death and Disease. 10(4). 281–281. 36 indexed citations
3.
Hartsough, Edward J., Curtis H. Kugel, Adam C. Berger, et al.. (2017). Response and Resistance to Paradox-Breaking BRAF Inhibitor in Melanomas In Vivo and Ex Vivo. Molecular Cancer Therapeutics. 17(1). 84–95. 20 indexed citations
4.
Webster, Marie R., Curtis H. Kugel, & Ashani T. Weeraratna. (2015). The Wnts of change: How Wnts regulate phenotype switching in melanoma. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1856(2). 244–251. 56 indexed citations
5.
Kugel, Curtis H., Edward J. Hartsough, Michael A. Davies, Yulius Y. Setiady, & Andrew E. Aplin. (2014). Function-Blocking ERBB3 Antibody Inhibits the Adaptive Response to RAF Inhibitor. Cancer Research. 74(15). 4122–4132. 45 indexed citations
6.
Kugel, Curtis H. & Andrew E. Aplin. (2014). Adaptive resistance to RAF inhibitors in melanoma. Pigment Cell & Melanoma Research. 27(6). 1032–1038. 44 indexed citations
7.
Abel, Ethan V., Kevin J. Basile, Curtis H. Kugel, et al.. (2013). Melanoma adapts to RAF/MEK inhibitors through FOXD3-mediated upregulation of ERBB3. Journal of Clinical Investigation. 123(5). 2155–2168. 189 indexed citations
8.
Kaplan, Fred M., et al.. (2012). SHOC2 and CRAF Mediate ERK1/2 Reactivation in Mutant NRAS-mediated Resistance to RAF Inhibitor. Journal of Biological Chemistry. 287(50). 41797–41807. 47 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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