Eva Bekesi

793 citations
15 papers · 691 · h-index 10

Impact in

    • Protein Kinase Regulation and GTPase Signaling
    • PI3K/AKT/mTOR signaling in cancer
    • RNA and protein synthesis mechanisms
    • Cancer-related Molecular Pathways

Papers in

    • Protein Kinase Regulation and GTPase Signaling 5
    • Glycosylation and Glycoproteins Research 2
    • Protein purification and stability 2
    • Cell death mechanisms and regulation 2
    • Receptor Mechanisms and Signaling 2
    • Monoclonal and Polyclonal Antibodies Research 7

Eva Bekesi

15 papers receiving 614 citations

Peers

Eva Bekesi
Comparison fields: 5 of 65
  • Molecular Biology 554
  • Oncology 183
  • Cell Biology 118
  • Radiology, Nuclear Medicine and Imaging 75
  • Genetics 95
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Citations per field
00.5×3.2×
Donna M. Gadbois · 1×
Citations per year

Countries citing papers authored by Eva Bekesi

Since Specialization
Citations

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

Fields of papers citing papers by Eva Bekesi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 1986180
2 1985165
3 196965
4 199454
5 198652
6 198542
7 198634
8 198628
9 198625
10 198416
11 19869
12 19918
13 19896
14
Mutational Analysis ofarasCatalytic Domain
19864
15 19953

About Eva Bekesi

Eva Bekesi is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Oncology, Genetics and Cell Biology, having authored 15 papers that have together received 691 indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (7 papers), Protein Kinase Regulation and GTPase Signaling (5 papers), Glycosylation and Glycoproteins Research (2 papers), Protein purification and stability (2 papers), Cell death mechanisms and regulation (2 papers), Cancer-related Molecular Pathways (2 papers), Cellular transport and secretion (2 papers) and Receptor Mechanisms and Signaling (2 papers). The work is most often cited by research in Molecular Biology (554 citations), Oncology (183 citations), Cell Biology (118 citations), Radiology, Nuclear Medicine and Imaging (75 citations) and Genetics (95 citations). Eva Bekesi has collaborated with scholars based in United States, Denmark and Cameroon. Frequent co-authors include Veeraswamy Manne, H F Kung, Alex G. Papageorge, Douglas R. Lowy, Berthe M. Willumsen, Morten Johnsen, William C. Vass, Hsiang‐Fu Kung, H F Kung and T. Robins. Their work appears in journals such as Journal of Biological Chemistry, Methods in enzymology on CD-ROM/Methods in enzymology, Molecular and Cellular Biology, Molecular Pharmacology and Proceedings of the National Academy of Sciences.

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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