James E. Korkola

13.8k total citations
65 papers, 2.8k citations indexed

About

James E. Korkola is a scholar working on Molecular Biology, Surgery and Oncology. According to data from OpenAlex, James E. Korkola has authored 65 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 16 papers in Surgery and 15 papers in Oncology. Recurrent topics in James E. Korkola's work include Testicular diseases and treatments (10 papers), Cancer Genomics and Diagnostics (8 papers) and Gene expression and cancer classification (7 papers). James E. Korkola is often cited by papers focused on Testicular diseases and treatments (10 papers), Cancer Genomics and Diagnostics (8 papers) and Gene expression and cancer classification (7 papers). James E. Korkola collaborates with scholars based in United States, Canada and United Kingdom. James E. Korkola's co-authors include Joe W. Gray, Sandy DeVries, Frederic M. Waldman, George J. Bosl, R. S. K. Chaganti, Jane Houldsworth, Adam B. Olshen, Victor E. Reuter, Peter R. Carroll and Sunanda Pejavar and has published in prestigious journals such as The Journal of Experimental Medicine, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

James E. Korkola

63 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James E. Korkola United States 26 1.6k 847 764 668 447 65 2.8k
Lawrence N. Kwong United States 27 1.5k 1.0× 1.2k 1.4× 641 0.8× 376 0.6× 397 0.9× 62 2.6k
Chouhei Sakakura Japan 27 1.2k 0.8× 723 0.9× 337 0.4× 638 1.0× 458 1.0× 104 2.4k
Florence de Fraipont France 30 1.4k 0.9× 637 0.8× 877 1.1× 529 0.8× 552 1.2× 67 2.7k
Hal K. Berman Canada 25 817 0.5× 829 1.0× 726 1.0× 253 0.4× 268 0.6× 57 2.1k
Naoki Shinojima Japan 26 1.3k 0.8× 682 0.8× 602 0.8× 203 0.3× 283 0.6× 80 3.0k
Maximilian Reichert Germany 26 1.8k 1.1× 2.2k 2.6× 897 1.2× 828 1.2× 312 0.7× 58 3.6k
Alessia Ciarrocchi Italy 33 2.4k 1.5× 1.2k 1.4× 1.0k 1.4× 285 0.4× 639 1.4× 115 4.0k
Ritu Roy United States 28 1.4k 0.9× 1.1k 1.3× 665 0.9× 289 0.4× 423 0.9× 64 2.9k
Barbara Klink Germany 25 1.0k 0.7× 530 0.6× 775 1.0× 277 0.4× 370 0.8× 73 2.5k
Spyro Mousses United States 29 2.4k 1.5× 816 1.0× 744 1.0× 222 0.3× 505 1.1× 65 3.3k

Countries citing papers authored by James E. Korkola

Since Specialization
Citations

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

Fields of papers citing papers by James E. Korkola

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James E. Korkola. 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 James E. Korkola. The network helps show where James E. Korkola may publish in the future.

Co-authorship network of co-authors of James E. Korkola

This figure shows the co-authorship network connecting the top 25 collaborators of James E. Korkola. A scholar is included among the top collaborators of James E. Korkola 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 James E. Korkola. James E. Korkola 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.
Hunt, Gregory J., Mark Dane, James E. Korkola, Laura M. Heiser, & Johann A. Gagnon-Bartsch. (2022). Systematic replication enables normalization of high-throughput imaging assays. Bioinformatics. 38(21). 4934–4940. 1 indexed citations
2.
Muir, Ryan K., Adam B. Olshen, Iwei Yeh, et al.. (2021). Ferrous iron–activatable drug conjugate achieves potent MAPK blockade in KRAS -driven tumors. The Journal of Experimental Medicine. 219(4). 16 indexed citations
3.
Iizuka, Shinji, Ronald P. Leon, Ying Zhang, et al.. (2020). Crosstalk between invadopodia and the extracellular matrix. European Journal of Cell Biology. 99(7). 151122–151122. 12 indexed citations
4.
Smith, Rebecca, Kaylyn L. Devlin, David Kilburn, et al.. (2019). Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer. Journal of Visualized Experiments. 9 indexed citations
5.
Bucher, Elmar, Rebecca Smith, Kaylyn L. Devlin, et al.. (2019). Annot: a Django-based sample, reagent, and experiment metadata tracking system. BMC Bioinformatics. 20(1). 542–542. 1 indexed citations
6.
Rozanov, Dmitri V., Anton Cheltsov, Aaron Nilsen, et al.. (2019). Targeting mitochondria in cancer therapy could provide a basis for the selective anti-cancer activity. PLoS ONE. 14(3). e0205623–e0205623. 18 indexed citations
7.
Donnella, Hayley, James T. Webber, Rebecca S. Levin, et al.. (2018). Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer. Nature Chemical Biology. 14(8). 768–777. 67 indexed citations
8.
Hill, Steven M., Nicole K. Nesser, Simon E. F. Spencer, et al.. (2016). Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling. Cell Systems. 4(1). 73–83.e10. 25 indexed citations
9.
Littlepage, Laurie E., Adam S. Adler, Hosein Kouros‐Mehr, et al.. (2012). The Transcription Factor ZNF217 Is a Prognostic Biomarker and Therapeutic Target during Breast Cancer Progression. Cancer Discovery. 2(7). 638–651. 54 indexed citations
10.
Collisson, Eric A., Christy L. Trejo, Jillian M. Silva, et al.. (2012). A Central Role for RAF→MEK→ERK Signaling in the Genesis of Pancreatic Ductal Adenocarcinoma. Cancer Discovery. 2(8). 685–693. 219 indexed citations
11.
Korkola, James E. & Joe W. Gray. (2010). Breast cancer genomes — form and function. Current Opinion in Genetics & Development. 20(1). 4–14. 36 indexed citations
12.
Korkola, James E., Jane Houldsworth, George J. Bosl, & R. S. K. Chaganti. (2009). Molecular events in germ cell tumours: linking chromosome‐12 gain, acquisition of pluripotency and response to cisplatin. British Journal of Urology. 104(9b). 1334–1338. 18 indexed citations
13.
14.
Korkola, James E., Ekaterina Blaveri, Sandy DeVries, et al.. (2007). Identification of a robust gene signature that predicts breast cancer outcome in independent data sets. BMC Cancer. 7(1). 61–61. 34 indexed citations
15.
Korkola, James E., Jane Houldsworth, Rajendrakumar S.V. Chadalavada, et al.. (2006). Down-Regulation of Stem Cell Genes, Including Those in a 200-kb Gene Cluster at 12p13.31, Is Associated with In vivo Differentiation of Human Male Germ Cell Tumors. Cancer Research. 66(2). 820–827. 236 indexed citations
16.
Chadalavada, Rajendrakumar S.V., et al.. (2006). Transcriptional Program Associated with IFN- α Response of Renal Cell Carcinoma. Journal of Interferon & Cytokine Research. 26(3). 156–170. 3 indexed citations
17.
Blaveri, Ekaterini, Jeff Simko, James E. Korkola, et al.. (2005). Bladder Cancer Outcome and Subtype Classification by Gene Expression. Clinical Cancer Research. 11(11). 4044–4055. 275 indexed citations
18.
Korkola, James E., Jane Houldsworth, Adam B. Olshen, et al.. (2005). Gene expression-based classification of nonseminomatous male germ cell tumors. Oncogene. 24(32). 5101–5107. 49 indexed citations
19.
Korkola, James E.. (1999). Resistance to mammary tumorigenesis in Copenhagen rats is associated with the loss of preneoplastic lesions. Carcinogenesis. 20(2). 221–227. 33 indexed citations
20.

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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