John Kay

1.7k citations
50 papers · 1.3k · h-index 20

Impact in

Papers in

    • Protein Hydrolysis and Bioactive Peptides 5
    • Glycosylation and Glycoproteins Research 3
    • Molecular Biology Techniques and Applications 3
    • RNA and protein synthesis mechanisms 3
    • Peptidase Inhibition and Analysis 11

John Kay

46 papers receiving 1.2k citations

Peers

John Kay
Comparison fields: 5 of 136
  • Biotechnology 152
  • Cancer Research 214
  • Molecular Biology 550
  • Virology 35
  • Cell Biology 118
Replace David Stevenson with:
David Stevenson United States
Richard O. Roblin United States
Gerd Steffens Germany
Karen M. Young United States
Michael Courtney France
Fred D. Ledley United States
Richard Harris United States
Kevin J. Scanlon United States
Andrew S. Turnell United Kingdom
Jane McGregor United Kingdom
John Kay relative to David Stevenson United States David Stevenson's profile →
Citations per field
00.5×1.7×
David Stevenson · 1×
Citations per year

Countries citing papers authored by John Kay

Since Specialization
Citations

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

Fields of papers citing papers by John Kay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1986148
2 1986111
3 198787
4 200080
5 198870
6 199863
7 199763
8
Obliquity: Why Our Goals Are Best Achieved Indirectly
201062
9 199056
10 198851
11 198741
12 198436
13 199236
14 199034
15 199034
16 199034
17 199128
18 198927
19 198526
20 199022

About John Kay

John Kay is a scholar working on Molecular Biology, Oncology, Biotechnology, Cancer Research and Hematology, having authored 50 papers that have together received 1.3k indexed citations. Recurring topics across this work include Peptidase Inhibition and Analysis (11 papers), Enzyme Production and Characterization (7 papers), Protein Hydrolysis and Bioactive Peptides (5 papers), Protease and Inhibitor Mechanisms (5 papers), Glycosylation and Glycoproteins Research (3 papers), Trace Elements in Health (3 papers), Molecular Biology Techniques and Applications (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Biotechnology (152 citations), Cancer Research (214 citations), Molecular Biology (550 citations), Virology (35 citations) and Cell Biology (118 citations). John Kay has collaborated with scholars based in United Kingdom, United States and Japan. Frequent co-authors include Martin J. Valler, Ben M. Dunn, William A. Reid, Carole E. Rolph, Wendy E. Lees, Peter J. Tatnell, I. Michael Samloff, Anthony Cryer, R A Jupp and Peter Kille. Their work appears in journals such as FEBS Letters, Biochemical Journal, The Political Quarterly, Journal of Clinical Pathology and Advances in experimental medicine and biology.

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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