M. Gunnell

800 citations
12 papers · 727 · h-index 9

Impact in

    • Protein Kinase Regulation and GTPase Signaling
    • Melanoma and MAPK Pathways
    • Ubiquitin and proteasome pathways
    • RNA and protein synthesis mechanisms
    • Cancer-related Molecular Pathways

Papers in

    • Virus-based gene therapy research 4
    • Immunotherapy and Immune Responses 2

M. Gunnell

12 papers receiving 673 citations

Peers

M. Gunnell
Comparison fields: 5 of 66
  • Molecular Biology 585
  • Oncology 135
  • Aging 9
  • Cell Biology 75
  • Cancer Research 60
Replace Eva Bekesi with:
Eva Bekesi United States
Richard J. Austin United States
Nicole Comtesse Germany
Neil R. Michaud United States
Sara M. Kantrow United States
Yingzi Yue United States
Tuyen T. L. Nguyen United States
Sabine Rottmann Germany
James T. Lynch United Kingdom
Greg Hinkle United States
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Citations per field
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Citations per year

Countries citing papers authored by M. Gunnell

Since Specialization
Citations

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

Fields of papers citing papers by M. Gunnell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M. Gunnell, 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 M. Gunnell Line = papers co-authored together M. Gunnell links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 1986205
2 1985170
3 1987126
4 198695
5 198442
6
Genomic dispersal of the ets gene family during metazoan evolution.
199233
7 197613
8 198312
9 198511
10 19839
11 19819
12 19782

About M. Gunnell

M. Gunnell is a scholar working on Genetics, Immunology, Animal Science and Zoology, Molecular Biology and Oncology, having authored 12 papers that have together received 727 indexed citations. Recurring topics across this work include Virus-based gene therapy research (4 papers), Protein Degradation and Inhibitors (3 papers), Polyomavirus and related diseases (3 papers), Animal Virus Infections Studies (2 papers), Immunotherapy and Immune Responses (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Receptor Mechanisms and Signaling (2 papers) and Pancreatic function and diabetes (1 paper). The work is most often cited by research in Molecular Biology (585 citations), Oncology (135 citations), Aging (9 citations), Cell Biology (75 citations) and Cancer Research (60 citations). M. Gunnell has collaborated with scholars based in United States and Czechia. Frequent co-authors include Ulf Rüdiger Rapp, Tom I. Bonner, Stephen Kerby, Mahmoud Huleihel, Pramod Sutrave, Alice C. Young, PETER H. SEEBURG, Herman Oppermann, G E Mark and Thomas W. Beck. Their work appears in journals such as Molecular and Cellular Biology, Nucleic Acids Research, Journal of Virology, Archives of Virology and Human Genetics.

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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