Joe S. Mymryk

6.1k total citations
152 papers, 4.3k citations indexed

About

Joe S. Mymryk is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Joe S. Mymryk has authored 152 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Molecular Biology, 84 papers in Genetics and 53 papers in Oncology. Recurrent topics in Joe S. Mymryk's work include Virus-based gene therapy research (70 papers), Viral Infectious Diseases and Gene Expression in Insects (24 papers) and Cancer-related Molecular Pathways (23 papers). Joe S. Mymryk is often cited by papers focused on Virus-based gene therapy research (70 papers), Viral Infectious Diseases and Gene Expression in Insects (24 papers) and Cancer-related Molecular Pathways (23 papers). Joe S. Mymryk collaborates with scholars based in Canada, United States and United Kingdom. Joe S. Mymryk's co-authors include Steven M. Frisch, Nikita Avvakumov, Jailal Ablack, S. T. Bayley, Anthony C. Nichols, John W. Barrett, Steven F. Gameiro, Ahmed F. Yousef, Trevor Archer and John A. Howe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Joe S. Mymryk

149 papers receiving 4.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joe S. Mymryk Canada 38 2.8k 1.8k 1.3k 732 589 152 4.3k
G W Demers United States 23 1.8k 0.7× 700 0.4× 1.7k 1.3× 357 0.5× 972 1.7× 29 3.6k
Miranda Thomas Italy 33 2.5k 0.9× 769 0.4× 2.4k 1.8× 694 0.9× 2.4k 4.1× 70 5.2k
E Harlow United States 24 4.6k 1.7× 1.4k 0.8× 4.7k 3.5× 599 0.8× 1.1k 1.8× 29 7.1k
Paola Massimi Italy 36 1.6k 0.6× 685 0.4× 1.1k 0.8× 611 0.8× 1.6k 2.8× 86 3.4k
Victor W. van Beusechem Netherlands 35 2.4k 0.9× 2.2k 1.2× 1.5k 1.1× 396 0.5× 239 0.4× 115 3.6k
David Reisman United States 37 3.8k 1.4× 585 0.3× 2.5k 1.9× 634 0.9× 1.0k 1.7× 93 5.9k
Elliot J. Androphy United States 52 5.8k 2.1× 1.9k 1.0× 1.6k 1.2× 1.1k 1.5× 3.0k 5.1× 155 9.1k
Ali Fattaey United States 22 4.6k 1.7× 2.3k 1.2× 4.0k 3.0× 439 0.6× 383 0.7× 34 6.6k
N L Hubbert United States 25 1.5k 0.5× 962 0.5× 988 0.7× 908 1.2× 2.6k 4.4× 30 4.2k
Karin Butz Germany 28 1.5k 0.5× 491 0.3× 780 0.6× 341 0.5× 825 1.4× 37 2.3k

Countries citing papers authored by Joe S. Mymryk

Since Specialization
Citations

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

Fields of papers citing papers by Joe S. Mymryk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joe S. Mymryk. 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 Joe S. Mymryk. The network helps show where Joe S. Mymryk may publish in the future.

Co-authorship network of co-authors of Joe S. Mymryk

This figure shows the co-authorship network connecting the top 25 collaborators of Joe S. Mymryk. A scholar is included among the top collaborators of Joe S. Mymryk 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 Joe S. Mymryk. Joe S. Mymryk 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
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Dawson, Alice, Mushfiq Hassan Shaikh, Peter YF. Zeng, et al.. (2024). Loss of MACROD2 drives radioresistance but not cisplatin resistance in HPV-positive head and neck cancer. Oral Oncology. 159. 107061–107061. 1 indexed citations
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Gameiro, Steven F., et al.. (2023). HPV16 Intratypic Variants in Head and Neck Cancers: A North American Perspective. Viruses. 15(12). 2411–2411. 5 indexed citations
5.
Zeng, Peter YF., Matthew J. Cecchini, Mushfiq Hassan Shaikh, et al.. (2023). HPV‐negative head and neck cancers with adverse pathological features carry specific molecular changes that are associated with survival. Head & Neck. 46(2). 353–366. 2 indexed citations
6.
Zeng, Peter YF., Mushfiq Hassan Shaikh, Danielle MacNeil, et al.. (2022). Tumor molecular differences associated with outcome disparities of Black patients with head and neck cancer. Head & Neck. 44(5). 1124–1135. 6 indexed citations
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Ziai, Hedyeh, Andrew Warner, Neil Mundi, et al.. (2021). Does HPV Subtype Predict Outcomes in Head and Neck Cancers?. SHILAP Revista de lepidopterología. 2021. 1–11. 9 indexed citations
9.
Prusinkiewicz, Martin A., Steven F. Gameiro, Farhad Ghasemi, et al.. (2020). Survival-Associated Metabolic Genes in Human Papillomavirus-Positive Head and Neck Cancers. Cancers. 12(1). 253–253. 42 indexed citations
10.
Shaikh, Mushfiq Hassan, John W. Barrett, Mohammed Imran Khan, et al.. (2020). Chromosome 3p loss in the progression and prognosis of head and neck cancer. Oral Oncology. 109. 104944–104944. 6 indexed citations
11.
Zeng, Peter YF., Mushfiq Hassan Shaikh, Neil Mundi, et al.. (2020). Analysis of the TCGA Dataset Reveals that Subsites of Laryngeal Squamous Cell Carcinoma Are Molecularly Distinct. Cancers. 13(1). 105–105. 11 indexed citations
12.
Mundi, Neil, Farhad Ghasemi, Peter YF. Zeng, et al.. (2020). Sex disparities in head & neck cancer driver genes: An analysis of the TCGA dataset. Oral Oncology. 104. 104614–104614. 20 indexed citations
13.
Gameiro, Steven F., Farhad Ghasemi, John W. Barrett, Anthony C. Nichols, & Joe S. Mymryk. (2019). High Level Expression of MHC-II in HPV+ Head and Neck Cancers Suggests that Tumor Epithelial Cells Serve an Important Role as Accessory Antigen Presenting Cells. Cancers. 11(8). 1129–1129. 21 indexed citations
14.
Ghasemi, Farhad, Stephenie D. Prokopec, Danielle MacNeil, et al.. (2019). Mutational analysis of head and neck squamous cell carcinoma stratified by smoking status. JCI Insight. 4(1). 21 indexed citations
15.
Gameiro, Steven F., Ali Zhang, Farhad Ghasemi, et al.. (2017). Analysis of Class I Major Histocompatibility Complex Gene Transcription in Human Tumors Caused by Human Papillomavirus Infection. Viruses. 9(9). 252–252. 37 indexed citations
16.
Pinto, Nicole, Krupal Patel, John Yoo, et al.. (2014). Genomically Driven Precision Medicine to Improve Outcomes in Anaplastic Thyroid Cancer. Journal of Oncology. 2014. 1–7. 15 indexed citations
17.
Nichols, Anthony C., Michelle Chan‐Seng‐Yue, John Yoo, et al.. (2012). A Pilot Study Comparing HPV-Positive and HPV-Negative Head and Neck Squamous Cell Carcinomas by Whole Exome Sequencing. ISRN Oncology. 2012. 1–9. 29 indexed citations
18.
Goulet, Brigitte, Amber Ablack, Carl O. Postenka, et al.. (2011). Nuclear localization of maspin is essential for its inhibition of tumor growth and metastasis. Laboratory Investigation. 91(8). 1181–1187. 49 indexed citations
19.
Guelen, Lars, Richard Killick, Gerry Melino, et al.. (2004). E1A Activates Transcription of p73 and Noxa to Induce Apoptosis. Journal of Biological Chemistry. 280(7). 5945–5959. 64 indexed citations
20.
Shuen, Michael, et al.. (2002). The Adenovirus E1A Protein Targets the SAGA but Not the ADA Transcriptional Regulatory Complex through Multiple Independent Domains. Journal of Biological Chemistry. 277(34). 30844–30851. 26 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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