Daniel S. Evans
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
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- Circadian rhythm and melatonin
Papers in
-
- Bone Metabolism and Diseases 5
- Muscle Physiology and Disorders 4
- Physiology 11
- Adipose Tissue and Metabolism 5
- Co-authors
- Sonia Ancoli‐Israel (5 shared papers)Wen‐Chi Hsueh (4 shared papers)Gregory J. Tranah (13 shared papers)Pankaj Kapahi (1 shared paper)Lutz Kockel (1 shared paper)Terri Blackwell (2 shared papers)Steven R. Cummings (12 shared papers)Katie L Stone (1 shared paper)
- Journals
- The Journals of Gerontology Series A (4 papers)Aging Cell (4 papers)PLoS ONE (4 papers)Innovation in Aging (3 papers)SLEEP (3 papers)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Daniel S. Evans
54 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 129
- Aging 125
- Endocrine and Autonomic Systems 184
- Experimental and Cognitive Psychology 215
- Orthopedics and Sports Medicine 113
- Physiology 247
Countries citing papers authored by Daniel S. Evans
This map shows the geographic impact of Daniel S. Evans'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 Daniel S. Evans with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel S. Evans more than expected).
Fields of papers citing papers by Daniel S. Evans
This network shows the impact of papers produced by Daniel S. Evans. 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 Daniel S. Evans. The network helps show where Daniel S. Evans may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel S. Evans, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 142 | |
| 2 | 2017 | 131 | |
| 3 | 2010 | 97 | |
| 4 | 2010 | 62 | |
| 5 | 2016 | 60 | |
| 6 | 2019 | 53 | |
| 7 | 2016 | 53 | |
| 8 | 2007 | 49 | |
| 9 | 2011 | 49 | |
| 10 | 2020 | 44 | |
| 11 | 2013 | 43 | |
| 12 | 1991 | 40 | |
| 13 | 2014 | 38 | |
| 14 | 2011 | 35 | |
| 15 | 2023 | 34 | |
| 16 | 1997 | 31 | |
| 17 | 2016 | 29 | |
| 18 | 2013 | 28 | |
| 19 | 2014 | 25 | |
| 20 | 2015 | 24 |
About Daniel S. Evans
Daniel S. Evans is a scholar working on Molecular Biology, Physiology, Rheumatology, Genetics and Aging, having authored 56 papers that have together received 1.4k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (6 papers), Bone health and osteoporosis research (5 papers), Adipose Tissue and Metabolism (5 papers), Bone Metabolism and Diseases (5 papers), Muscle Physiology and Disorders (4 papers), GDF15 and Related Biomarkers (4 papers), Sleep and related disorders (4 papers) and Genetic Associations and Epidemiology (3 papers). The work is most often cited by research in Aging (125 citations), Endocrine and Autonomic Systems (184 citations), Experimental and Cognitive Psychology (215 citations), Orthopedics and Sports Medicine (113 citations) and Physiology (247 citations). Daniel S. Evans has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Sonia Ancoli‐Israel, Wen‐Chi Hsueh, Gregory J. Tranah, Pankaj Kapahi, Lutz Kockel, Terri Blackwell, Steven R. Cummings, Katie L Stone, Sanjay R. Patel and Yun Kwok Wing. Their work appears in journals such as The Journals of Gerontology Series A, Aging Cell, PLoS ONE, Innovation in Aging and SLEEP.
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.