Ken Dawson‐Scully
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
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- Neurobiology and Insect Physiology Research
- Neuroscience and Neuropharmacology Research
Papers in
- Aging 16
- Genetics, Aging, and Longevity in Model Organisms 16
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- Neurobiology and Insect Physiology Research 19
- Neuroscience and Neuropharmacology Research 6
- Co-authors
- R. Meldrum RobertsonKonrad E. ZinsmaierHarold L. AtwoodPeter BronkMarla B. SokolowskiSarah MiltonGary A.B. ArmstrongR. David Andrew
- Journals
- PLoS ONE (8 papers)Journal of Experimental Biology (4 papers)Scientific Reports (2 papers)Journal of Neurogenetics (2 papers)Journal of Neurophysiology (2 papers)
- Partner nations
- United StatesCanadaHungary
In The Last Decade
Ken Dawson‐Scully
39 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 99
- Aging 137
- Cellular and Molecular Neuroscience 494
- Endocrine and Autonomic Systems 84
- Cell Biology 174
- Ecology 220
Countries citing papers authored by Ken Dawson‐Scully
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
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-authorship network
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2022 | 59 | |
| 3 | 2022 | 6 | |
| 4 | 2022 | 33 | |
| 5 | 2021 | 6 | |
| 6 | 2020 | 0 | |
| 7 | 2019 | 9 | |
| 8 | 2018 | 3 | |
| 9 | 2016 | 71 | |
| 10 | 2016 | 8 | |
| 11 | 2016 | 19 | |
| 12 | 2014 | 14 | |
| 13 | 2012 | 48 | |
| 14 | 2011 | 31 | |
| 15 | 2011 | 10 | |
| 16 | 2009 | 18 | |
| 17 | 2007 | 50 | |
| 18 | 2006 | 24 | |
| 19 | 2005 | 48 | |
| 20 | 1996 | 37 |
About Ken Dawson‐Scully
Ken Dawson‐Scully is a scholar working on Aging, Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems, Ecology and Developmental Neuroscience, 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 (6 papers), Circadian rhythm and melatonin (5 papers), Ion channel regulation and function (4 papers) and Heat shock proteins research (4 papers). The work is most often cited by research in Aging (137 citations), Cellular and Molecular Neuroscience (494 citations), Endocrine and Autonomic Systems (84 citations), Cell Biology (174 citations) and Ecology (220 citations). Ken Dawson‐Scully has collaborated with scholars based in United States, Canada and Hungary. Frequent co-authors include R. Meldrum Robertson, Konrad E. Zinsmaier, Harold L. Atwood, Peter Bronk, Marla B. Sokolowski, Sarah Milton, Gary A.B. Armstrong, R. David Andrew, Xiufang Guo and Herbert Weissbach. Their work appears in journals such as PLoS ONE, Journal of Experimental Biology, Scientific Reports, Journal of Neurogenetics and Journal of Neurophysiology.
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.