G E Mark

2.4k citations
36 papers · 2.2k · h-index 21

Impact in

  • Virology top 5%
    • HIV Research and Treatment
    • Protein Kinase Regulation and GTPase Signaling
    • Melanoma and MAPK Pathways
    • RNA Interference and Gene Delivery

Papers in

G E Mark

36 papers receiving 1.9k citations

Peers

G E Mark
Comparison fields: 5 of 98
  • Virology 174
  • Molecular Biology 1.4k
  • Immunology 307
  • Oncology 347
  • Genetics 378
Replace Fred H. Reynolds with:
Fred H. Reynolds United States
Ramareddy V. Guntaka United States
Hidekazu Nakabayashi Japan
Yan‐Hwa Wu Lee Taiwan
Roberta K. Reynolds United States
Patrick R. Romano United States
Ronald W. Ellis United States
Joseph S. Lipsick United States
Sadaaki Kawai Japan
Nahum Sonenberg Canada
G E Mark relative to Fred H. Reynolds United States Fred H. Reynolds's profile →
Citations per field
00.5×1.7×
Fred H. Reynolds · 1×
Citations per year

Countries citing papers authored by G E Mark

Since Specialization
Citations

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

Fields of papers citing papers by G E Mark

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside G E Mark, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with G E Mark Line = papers co-authored together G E Mark links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1983420
2
Activation of the c-Raf protein kinase by protein kinase C phosphorylation.
1992272
3 1978203
4 1985170
5 1987138
6 1996115
7 199166
8 198863
9 198462
10 198756
11 198955
12 199655
13 198952
14 199450
15 198646
16 199745
17 198944
18 199536
19 198630
20 199429

About G E Mark

G E Mark is a scholar working on Radiology, Nuclear Medicine and Imaging, Virology, Oncology, Genetics and Molecular Biology, having authored 36 papers that have together received 2.2k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (8 papers), Virus-based gene therapy research (6 papers), Viral Infectious Diseases and Gene Expression in Insects (4 papers), HIV Research and Treatment (4 papers), Animal Virus Infections Studies (4 papers), Ubiquitin and proteasome pathways (4 papers), Cancer-related Molecular Pathways (3 papers) and Herpesvirus Infections and Treatments (3 papers). The work is most often cited by research in Virology (174 citations), Molecular Biology (1.4k citations), Immunology (307 citations), Oncology (347 citations) and Genetics (378 citations). G E Mark has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Ulf Rüdiger Rapp, Tom I. Bonner, John Stephenson, John Groffen, Mindy D. Goldsborough, Fred H. Reynolds, John M. Taylor, T W Hsu, Jan L. Sabran and R V Guntaka. Their work appears in journals such as Journal of Virology, Proceedings of the National Academy of Sciences, Molecular and Cellular Biology, The Journal of Immunology and Archives of Biochemistry and Biophysics.

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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