Maya Dajee

2.8k total citations · 1 hit paper
23 papers, 2.0k citations indexed

About

Maya Dajee is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Maya Dajee has authored 23 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Oncology and 6 papers in Immunology. Recurrent topics in Maya Dajee's work include Reproductive System and Pregnancy (4 papers), NF-κB Signaling Pathways (4 papers) and Multiple Myeloma Research and Treatments (3 papers). Maya Dajee is often cited by papers focused on Reproductive System and Pregnancy (4 papers), NF-κB Signaling Pathways (4 papers) and Multiple Myeloma Research and Treatments (3 papers). Maya Dajee collaborates with scholars based in United States, Germany and Switzerland. Maya Dajee's co-authors include Ti Cai, Paul A. Khavari, Christopher J. Kirk, Cheryl L. Green, Qun Lin, Yoshiaki Kubo, Mirella Lazarov, Shiying Tao, Masahito Tarutani and Darryl L. Russell and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Medicine.

In The Last Decade

Maya Dajee

22 papers receiving 2.0k citations

Hit Papers

Antitumor Activity of PR-171, a Novel Irreversible Inhibi... 2007 2026 2013 2019 2007 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maya Dajee United States 15 1.2k 628 434 354 305 23 2.0k
Stacey J. Baker United States 18 1.3k 1.1× 615 1.0× 547 1.3× 381 1.1× 343 1.1× 34 2.3k
Luigi Scotto United States 30 1.5k 1.2× 642 1.0× 1.1k 2.4× 280 0.8× 170 0.6× 82 2.8k
Umut Şahin France 14 1.2k 1.0× 622 1.0× 280 0.6× 254 0.7× 181 0.6× 20 1.9k
Mark A. Subler United States 32 2.0k 1.6× 1.5k 2.4× 256 0.6× 412 1.2× 197 0.6× 65 3.0k
Simona Ronzoni Italy 17 2.2k 1.8× 1.3k 2.1× 328 0.8× 659 1.9× 401 1.3× 29 3.2k
Sonia Minuzzo Italy 21 824 0.7× 397 0.6× 315 0.7× 325 0.9× 210 0.7× 49 1.5k
Muthu Selvakumaran United States 22 1.3k 1.0× 745 1.2× 233 0.5× 339 1.0× 160 0.5× 31 1.9k
Adrienne A. Hilton Australia 15 1.4k 1.1× 379 0.6× 453 1.0× 162 0.5× 488 1.6× 18 2.3k
Diep Nguyen United States 19 1.4k 1.1× 638 1.0× 273 0.6× 304 0.9× 121 0.4× 31 2.0k
Peter R. Strack United States 20 2.1k 1.7× 808 1.3× 334 0.8× 518 1.5× 211 0.7× 34 2.8k

Countries citing papers authored by Maya Dajee

Since Specialization
Citations

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

Fields of papers citing papers by Maya Dajee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Dajee

This figure shows the co-authorship network connecting the top 25 collaborators of Maya Dajee. A scholar is included among the top collaborators of Maya Dajee 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 Maya Dajee. Maya Dajee 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
2.
Gettinger, Scott, Thaddeus Beck, Xinyun Yang, et al.. (2018). CheckMate 592: A phase II exploratory study of biomarkers associated with the efficacy of first-line nivolumab (nivo) plus ipilimumab (ipi) in patients (pts) with stage IV or recurrent NSCLC. Annals of Oncology. 29. viii544–viii545. 2 indexed citations
3.
Howatt, Deborah A., Maya Dajee, Xiaojie Xie, et al.. (2017). Relaxin and Matrix Metalloproteinase-9 in Angiotensin II-Induced Abdominal Aortic Aneurysms. Circulation Journal. 81(6). 888–890. 17 indexed citations
4.
Zhou, Xiaoyan, Michael J. Forrest, Gail Forrest, et al.. (2016). Chronic Inhibition of Renal Outer Medullary Potassium Channel Not Only Prevented but Also Reversed Development of Hypertension and End-Organ Damage in Dahl Salt-Sensitive Rats. Hypertension. 69(2). 332–338. 12 indexed citations
5.
Basler, Michael, Maya Dajee, Carlo Moll, Marcus Groettrup, & Christopher J. Kirk. (2010). Prevention of Experimental Colitis by a Selective Inhibitor of the Immunoproteasome. The Journal of Immunology. 185(1). 634–641. 207 indexed citations
6.
Dajee, Maya, Monette Aujay, Susan D. Demo, et al.. (2008). 238 POSTER The selective proteasome inhibitor carfilzomib in combination with chemotherapeutic agents improves anti-tumor response in solid tumor xenograft models. European Journal of Cancer Supplements. 6(12). 75–75. 1 indexed citations
7.
Muchamuel, Tony, Monette Aujay, Mark K. Bennett, et al.. (2008). Preclinical Pharmacology and in Vitro Characterization of PR-047, An Oral Inhibitor of the 20S Proteasome. Blood. 112(11). 3671–3671. 4 indexed citations
8.
Kirk, Christopher J., Jing Jiang, Tony Muchamuel, et al.. (2008). The Selective Proteasome Inhibitor Carfilzomib Is Well Tolerated in Experimental Animals with Dose Intensive Administration. Blood. 112(11). 2765–2765. 10 indexed citations
9.
Demo, Susan D., Christopher J. Kirk, Monette Aujay, et al.. (2007). Antitumor Activity of PR-171, a Novel Irreversible Inhibitor of the Proteasome. Cancer Research. 67(13). 6383–6391. 542 indexed citations breakdown →
10.
Prasad, Srinivasa R., László G. Kömüves, Carlos Lorenzana, et al.. (2006). Non-viral delivery of nuclear factor-κB decoy ameliorates murine inflammatory bowel disease and restores tissue homeostasis. Gut. 56(4). 524–533. 44 indexed citations
11.
Dajee, Maya, Tony Muchamuel, Brian Schryver, et al.. (2006). Blockade of Experimental Atopic Dermatitis via Topical NF-κB Decoy Oligonucleotide. Journal of Investigative Dermatology. 126(8). 1792–1803. 40 indexed citations
12.
Plavec, Ivan, Oksana Sirenko, Maya Dajee, et al.. (2004). Method for analyzing signaling networks in complex cellular systems. Proceedings of the National Academy of Sciences. 101(5). 1223–1228. 36 indexed citations
13.
Dajee, Maya, Mirella Lazarov, Jennifer Zhang, et al.. (2003). NF-κB blockade and oncogenic Ras trigger invasive human epidermal neoplasia. Nature. 421(6923). 639–643. 448 indexed citations
14.
Lazarov, Mirella, Yoshiaki Kubo, Ti Cai, et al.. (2002). CDK4 coexpression with Ras generates malignant human epidermal tumorigenesis. Nature Medicine. 8(10). 1105–1114. 160 indexed citations
15.
Dajee, Maya, Masahito Tarutani, Helen Deng, Ti Cai, & Paul A. Khavari. (2002). Epidermal Ras blockade demonstrates spatially localized Ras promotion of proliferation and inhibition of differentiation. Oncogene. 21(10). 1527–1538. 82 indexed citations
16.
Richards, JoAnne S., Darryl L. Russell, Rebecca L. Robker, Maya Dajee, & Tamara Alliston. (1998). Molecular mechanisms of ovulation and luteinization. Molecular and Cellular Endocrinology. 145(1-2). 47–54. 189 indexed citations
17.
Dajee, Maya, Georg H. Fey, & JoAnne S. Richards. (1998). Stat 5b and the Orphan Nuclear Receptors Regulate Expression of the α2-Macroglobulin (α2M) Gene in Rat Ovarian Granulosa Cells. Molecular Endocrinology. 12(9). 1393–1409. 28 indexed citations
19.
Dajee, Maya, A.V. Kazansky, Brian Raught, et al.. (1996). Prolactin induction of the alpha 2-Macroglobulin gene in rat ovarian granulosa cells: stat 5 activation and binding to the interleukin-6 response element.. Molecular Endocrinology. 10(2). 171–184. 53 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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