Ken Dawson‐Scully

1.4k citations
41 papers · 1.0k · h-index 20

Impact in

Papers in

Ken Dawson‐Scully

39 papers receiving 1.0k citations

Peers

Ken Dawson‐Scully
Comparison fields: 5 of 97
  • Aging 132
  • Cellular and Molecular Neuroscience 484
  • Endocrine and Autonomic Systems 81
  • Cell Biology 171
  • Ecology 219
Replace Carol M. Singh with:
Carol M. Singh United States
Monica Moore United States
Zhengmei Mao United States
Junjiro Horiuchi Japan
Laurent Perrin France
Marcus J. Allen United Kingdom
Michael S. Grotewiel United States
Richard Y. Hwang United States
Nigel S. Atkinson United States
Oliver Hendrich Germany
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Citations per field
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Citations per year

Countries citing papers authored by Ken Dawson‐Scully

Since Specialization
Citations

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

Fields of papers citing papers by Ken Dawson‐Scully

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ken Dawson‐Scully. 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 Ken Dawson‐Scully. The network helps show where Ken Dawson‐Scully may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001104
2 200079
3 201672
4 202262
5 200260
6 200750
7 201248
8 200548
9 201041
10 199637
11 202236
12 202034
13 200532
14 199832
15 201131
16 201726
17 201625
18 200624
19 201221
20 201619

About Ken Dawson‐Scully

Ken Dawson‐Scully is a scholar working on Cellular and Molecular Neuroscience, Aging, Ecology, Molecular Biology and Pharmacology, having authored 41 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (19 papers), Genetics, Aging, and Longevity in Model Organisms (16 papers), Physiological and biochemical adaptations (13 papers), Neuroscience and Neuropharmacology Research (6 papers), Cholinesterase and Neurodegenerative Diseases (5 papers), Circadian rhythm and melatonin (5 papers), Heat shock proteins research (4 papers) and Cellular transport and secretion (3 papers). The work is most often cited by research in Aging (132 citations), Cellular and Molecular Neuroscience (484 citations), Endocrine and Autonomic Systems (81 citations), Cell Biology (171 citations) and Ecology (219 citations). Ken Dawson‐Scully has collaborated with scholars based in United States, Canada and Hungary. Frequent co-authors include R. Meldrum Robertson, Harold L. Atwood, Konrad E. Zinsmaier, Peter Bronk, Marla B. Sokolowski, Sarah Milton, Gary A.B. Armstrong, R. David Andrew, Xiufang Guo and Kasirajan Ayyanathan. Their work appears in journals such as PLoS ONE, Journal of Experimental Biology, Journal of Neuroscience, Journal of Neurogenetics and Neurocritical Care.

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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