Dennis Gee

1.3k total citations · 1 hit paper
9 papers, 1.0k citations indexed

About

Dennis Gee is a scholar working on Epidemiology, Physiology and Molecular Biology. According to data from OpenAlex, Dennis Gee has authored 9 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Epidemiology, 6 papers in Physiology and 2 papers in Molecular Biology. Recurrent topics in Dennis Gee's work include Telomeres, Telomerase, and Senescence (6 papers), Cytomegalovirus and herpesvirus research (6 papers) and HIV Research and Treatment (2 papers). Dennis Gee is often cited by papers focused on Telomeres, Telomerase, and Senescence (6 papers), Cytomegalovirus and herpesvirus research (6 papers) and HIV Research and Treatment (2 papers). Dennis Gee collaborates with scholars based in United States, Australia and India. Dennis Gee's co-authors include Dimiter S. Dimitrov, Yanru Feng, Steven L. Zeichner, Robert J. Biggar, Richard A. Lempicki, Xiaodong Xiao, Richard T. Davey, Christian Yoder, Niranjan Bhat and Maureen M. Goodenow and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and Information Sciences.

In The Last Decade

Dennis Gee

9 papers receiving 988 citations

Hit Papers

HIV-1 and T cell dynamics after interruption of highly ac... 1999 2026 2008 2017 1999 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
Dennis Gee United States 8 614 411 280 270 169 9 1.0k
Hwee L. Ng United States 21 609 1.0× 190 0.5× 96 0.3× 722 2.7× 294 1.7× 49 1.2k
Eric Lee United States 13 303 0.5× 215 0.5× 59 0.2× 208 0.8× 249 1.5× 16 713
Sher L. Hendrickson United States 15 129 0.2× 95 0.2× 32 0.1× 60 0.2× 192 1.1× 23 619
Julie Sullivan United States 11 665 1.1× 401 1.0× 18 0.1× 338 1.3× 109 0.6× 13 795
Yelina Alvarez United States 9 99 0.2× 86 0.2× 49 0.2× 275 1.0× 150 0.9× 16 491
L M Baca United States 8 616 1.0× 260 0.6× 27 0.1× 415 1.5× 79 0.5× 9 813
Judith Delmar United States 9 377 0.6× 239 0.6× 23 0.1× 204 0.8× 57 0.3× 10 533
Lisa LaFranco-Scheuch United States 8 342 0.6× 178 0.4× 24 0.1× 206 0.8× 49 0.3× 13 510
Joann Cutilli United States 10 389 0.6× 209 0.5× 9 0.0× 253 0.9× 82 0.5× 12 553
Allyson Guimarães Costa Brazil 17 153 0.2× 107 0.3× 30 0.1× 161 0.6× 150 0.9× 85 787

Countries citing papers authored by Dennis Gee

Since Specialization
Citations

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

Fields of papers citing papers by Dennis Gee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dennis Gee

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

All Works

9 of 9 papers shown
1.
Sidorov, Igor A., Dennis Gee, & Dimiter S. Dimitrov. (2003). A kinetic model of telomere shortening in infants and adults. Journal of Theoretical Biology. 226(2). 169–175. 15 indexed citations
2.
Hosack, Douglas A, et al.. (2002). Oligonucleotide microarray data distribution and normalization. Information Sciences. 146(1-4). 67–73. 23 indexed citations
3.
Feng, Yanru, Robert J. Biggar, Dennis Gee, et al.. (1999). Long-Term Telomere Dynamics: Modest Increase of Cell Turnover in HIV-Infected Individuals Followed for up to 14 Years. Pathobiology. 67(1). 34–38. 16 indexed citations
4.
Shibata, Riri, Yanru Feng, Dennis Gee, et al.. (1999). Telomere dynamics in monkeys: Increased cell turnover in macaques infected with chimeric simian‐human immunodeficiency viruses. Journal of Medical Primatology. 28(1). 1–10. 7 indexed citations
5.
Davey, Richard T., Niranjan Bhat, Christian Yoder, et al.. (1999). HIV-1 and T cell dynamics after interruption of highly active antiretroviral therapy (HAART) in patients with a history of sustained viral suppression. Proceedings of the National Academy of Sciences. 96(26). 15109–15114. 639 indexed citations breakdown →
6.
Zeichner, Steven L., Paul Palumbo, Yanru Feng, et al.. (1999). Rapid Telomere Shortening in Children. Blood. 93(9). 2824–2830. 155 indexed citations
7.
Zeichner, Steven L., Paul Palumbo, Yanru Feng, et al.. (1999). Rapid Telomere Shortening in Children. Blood. 93(9). 2824–2830. 137 indexed citations
8.
Feng, Yanru, David Norwood, Riri Shibata, et al.. (1998). Telomere dynamics in HIV‐1 infected and uninfected chimpanzees measured by an improved method based on high‐resolution two‐dimensional calibration of DNA sizes. Journal of Medical Primatology. 27(5). 258–265. 9 indexed citations
9.
Wigney, D. I., Dennis Gee, & Paul J. Canfield. (1989). Pyogranulomatous Pneumonias Due to Nocardia asteroides and Staphylococcus epidermidis in Two Koalas (Phascolarctos cinereus). Journal of Wildlife Diseases. 25(4). 592–596. 3 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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