É. Kun

2.0k citations
57 papers · 1.5k · h-index 24

Impact in

  • Physiology top 5%
    • Calcium signaling and nucleotide metabolism
    • Amino Acid Enzymes and Metabolism

Papers in

    • Enzyme function and inhibition 11
    • Mitochondrial Function and Pathology 6
    • Biochemical and Molecular Research 5
    • ATP Synthase and ATPases Research 4
    • PARP inhibition in cancer therapy 13

É. Kun

57 papers receiving 1.3k citations

Peers

É. Kun
Comparison fields: 5 of 100
  • Physiology 107
  • Biochemistry 155
  • Oncology 484
  • Clinical Biochemistry 114
  • Molecular Biology 858
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Ernest Kun United States
L. A. Stocken United Kingdom
B.J. Noland United States
Tushar K. Ray United States
Terence J. Scallen United States
Kay Fink United States
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Lawrence W. Anderson United States
Anna L. Shen United States
Paul D. van Poelje United States
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Citations per field
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Citations per year

Countries citing papers authored by É. Kun

Since Specialization
Citations

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

Fields of papers citing papers by É. Kun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1957123
2
Studies on the Ehrlich ascites tumor. I. The enzymic and metabolic activities of the ascitic cells and the ascitic plasma.
1951100
3 199072
4 196471
5 197560
6 197658
7 197051
8 198747
9 198347
10 198346
11 198345
12 199740
13 196938
14 198138
15 197937
16 196033
17 196532
18 196427
19 198127
20 197126

About É. Kun

É. Kun is a scholar working on Molecular Biology, Oncology, Organic Chemistry, Cell Biology and Cancer Research, having authored 57 papers that have together received 1.5k indexed citations. Recurring topics across this work include PARP inhibition in cancer therapy (13 papers), Enzyme function and inhibition (11 papers), Mitochondrial Function and Pathology (6 papers), Biochemical and Molecular Research (5 papers), Hemoglobin structure and function (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), ATP Synthase and ATPases Research (4 papers) and Metabolism and Genetic Disorders (4 papers). The work is most often cited by research in Physiology (107 citations), Biochemistry (155 citations), Oncology (484 citations), Clinical Biochemistry (114 citations) and Molecular Biology (858 citations). É. Kun has collaborated with scholars based in United States, Hungary and Japan. Frequent co-authors include D. D. Davies, D.W. Fanshier, Takeyoshi Minaga, George Jackowski, E. Kirsten, H.G. Williams-Ashman, Paul Talalay, Kálman G. Büki, Paul Bauer and Alaeddin Hakam. Their work appears in journals such as Journal of Biological Chemistry, Experimental Biology and Medicine, International Journal of Molecular Medicine, Biochemical and Biophysical Research Communications 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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