Michael Reedijk

4.8k total citations · 1 hit paper
50 papers, 3.7k citations indexed

About

Michael Reedijk is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Michael Reedijk has authored 50 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 24 papers in Oncology and 15 papers in Immunology. Recurrent topics in Michael Reedijk's work include Developmental Biology and Gene Regulation (10 papers), Cancer Cells and Metastasis (9 papers) and Breast Cancer Treatment Studies (6 papers). Michael Reedijk is often cited by papers focused on Developmental Biology and Gene Regulation (10 papers), Cancer Cells and Metastasis (9 papers) and Breast Cancer Treatment Studies (6 papers). Michael Reedijk collaborates with scholars based in Canada, United States and United Kingdom. Michael Reedijk's co-authors include Tony Pawson, David R. McCready, Hui Zhang, Sean E. Egan, Gina Lockwood, Naomi Miller, X. Johné Liu, Lynn Chang, Silvia Odorcic and Alan Bernstein and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Michael Reedijk

49 papers receiving 3.7k citations

Hit Papers

High-level Coexpression of JAG1 and NOTCH1 Is Observed in... 2005 2026 2012 2019 2005 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Reedijk Canada 33 2.4k 1.4k 731 634 313 50 3.7k
Yoshinori Ino Japan 34 1.7k 0.7× 1.3k 1.0× 517 0.7× 660 1.0× 514 1.6× 63 3.5k
Tilman Brummer Germany 35 2.9k 1.2× 1.2k 0.9× 547 0.7× 897 1.4× 468 1.5× 98 4.3k
Regina S. Whitaker United States 34 2.2k 0.9× 1.7k 1.2× 877 1.2× 673 1.1× 209 0.7× 72 4.3k
Vladimir Bezrookove United States 28 2.1k 0.9× 1.0k 0.7× 724 1.0× 464 0.7× 405 1.3× 48 3.3k
Sandra E. Dunn Canada 43 3.5k 1.4× 1.5k 1.1× 1.1k 1.5× 339 0.5× 441 1.4× 99 5.1k
Laura Soucek Spain 32 3.7k 1.5× 1.7k 1.3× 858 1.2× 855 1.3× 256 0.8× 54 5.0k
Jérôme Moreaux France 40 2.9k 1.2× 1.5k 1.1× 690 0.9× 1.1k 1.8× 328 1.0× 170 4.9k
Anushka Dongre United States 11 2.0k 0.8× 1.8k 1.3× 1.2k 1.6× 764 1.2× 336 1.1× 15 3.8k
Salvatore Pece Italy 27 3.0k 1.2× 1.7k 1.2× 803 1.1× 392 0.6× 716 2.3× 75 4.5k
Nicholas Bertos Canada 27 3.0k 1.2× 1.5k 1.1× 1.0k 1.4× 624 1.0× 238 0.8× 57 4.4k

Countries citing papers authored by Michael Reedijk

Since Specialization
Citations

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

Fields of papers citing papers by Michael Reedijk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Reedijk. 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 Michael Reedijk. The network helps show where Michael Reedijk may publish in the future.

Co-authorship network of co-authors of Michael Reedijk

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Reedijk. A scholar is included among the top collaborators of Michael Reedijk 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 Michael Reedijk. Michael Reedijk 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.
Murakami, Kiichi, et al.. (2024). Inhibition of Notch enhances efficacy of immune checkpoint blockade in triple-negative breast cancer. Science Advances. 10(44). eado8275–eado8275. 3 indexed citations
2.
Murakami, Kiichi, Valentin Sotov, Marcus O. Butler, et al.. (2024). Caspase-1-dependent spatiality in triple-negative breast cancer and response to immunotherapy. Nature Communications. 15(1). 8514–8514. 3 indexed citations
4.
Wilson, Brooke E., et al.. (2022). Targeting Notch-Driven Cytokine Secretion: Novel Therapies for Triple Negative Breast Cancer. DNA and Cell Biology. 42(2). 73–81. 4 indexed citations
5.
Murakami, Kiichi, Andrew Elia, Yukiko Shibahara, et al.. (2021). Therapeutic inhibition of USP9x-mediated Notch signaling in triple-negative breast cancer. Proceedings of the National Academy of Sciences. 118(38). 49 indexed citations
6.
Toker, Aras, Linh T. Nguyen, Simone C. Stone, et al.. (2018). Regulatory T Cells in Ovarian Cancer Are Characterized by a Highly Activated Phenotype Distinct from that in Melanoma. Clinical Cancer Research. 24(22). 5685–5696. 85 indexed citations
7.
Shen, Qiang, Brenda Cohen, Ramtin Rahbar, et al.. (2017). Notch Shapes the Innate Immunophenotype in Breast Cancer. Cancer Discovery. 7(11). 1320–1335. 92 indexed citations
8.
Moran, Michael F., et al.. (2016). Cellular stress induces TRB3/USP9x-dependent Notch activation in cancer. Oncogene. 36(8). 1048–1057. 52 indexed citations
9.
Cornacchi, Sylvie D., Michael Reedijk, Nicole Hodgson, et al.. (2016). Breast cancer recurrence following radioguided seed localization and standard wire localization of nonpalpable invasive and in situ breast cancers: 5-Year follow-up from a randomized controlled trial. The American Journal of Surgery. 213(4). 798–804. 10 indexed citations
11.
Rahbar, Ramtin, Albert Lin, Magar Ghazarian, et al.. (2014). B7-H4 Expression by Nonhematopoietic Cells in the Tumor Microenvironment Promotes Antitumor Immunity. Cancer Immunology Research. 3(2). 184–195. 38 indexed citations
12.
Reedijk, Michael, Jeroen P. G. van Leuken, & Wim van der Hoek. (2013). Particulate matter strongly associated with human Q fever in The Netherlands: an ecological study. Epidemiology and Infection. 141(12). 2623–2633. 19 indexed citations
13.
Reedijk, Michael. (2012). Notch Signaling and Breast Cancer. Advances in experimental medicine and biology. 727. 241–257. 73 indexed citations
14.
Shimizu, Mamiko, et al.. (2011). Plasminogen Activator uPA Is a Direct Transcriptional Target of the JAG1-Notch Receptor Signaling Pathway in Breast Cancer. Cancer Research. 71(1). 277–286. 53 indexed citations
15.
Cohen, Brenda, et al.. (2009). Cyclin D1 is a direct target of JAG1-mediated Notch signaling in breast cancer. Breast Cancer Research and Treatment. 123(1). 113–124. 131 indexed citations
16.
Connolly, Elizabeth, et al.. (2009). Mammary ductoscopy in the evaluation and treatment of pathologic nipple discharge: a Canadian experience.. PubMed. 52(6). E245–8. 21 indexed citations
17.
Reedijk, Michael, Dushanthi Pinnaduwage, Brendan C. Dickson, et al.. (2007). JAG1 expression is associated with a basal phenotype and recurrence in lymph node-negative breast cancer. Breast Cancer Research and Treatment. 111(3). 439–448. 119 indexed citations
18.
Reedijk, Michael, Silvia Odorcic, Lynn Chang, et al.. (2005). High-level Coexpression of JAG1 and NOTCH1 Is Observed in Human Breast Cancer and Is Associated with Poor Overall Survival. Cancer Research. 65(18). 8530–8537. 615 indexed citations breakdown →
19.
Reedijk, Michael, Scott Boerner, Danny Ghazarian, & David R. McCready. (2005). A case of axillary web syndrome with subcutaneous nodules following axillary surgery. The Breast. 15(3). 410–412. 35 indexed citations
20.
Reedijk, Michael, et al.. (1990). Interactions of Phosphatidylinositol Kinase, GTPase-Activating Protein (GAP), and GAP-Associated Proteins with the Colony-Stimulating Factor 1 Receptor. Molecular and Cellular Biology. 10(11). 5601–5608. 39 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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