Daniel Pulliam
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 10%
- Adipose Tissue and Metabolism
Papers in
-
- Mitochondrial Function and Pathology 13
- Redox biology and oxidative stress 2
- Muscle Physiology and Disorders 2
- Physiology 15
- Adipose Tissue and Metabolism 10
- Spaceflight effects on biology 2
- Co-authors
- Holly Van Remmen (14 shared papers)Yun Shi (6 shared papers)Arunabh Bhattacharya (6 shared papers)Shauna Hill (6 shared papers)Sathyaseelan S. Deepa (6 shared papers)Yuhong Liu (5 shared papers)Lauren Sloane (3 shared papers)Carlo Viscomi (4 shared papers)
- Journals
- The FASEB Journal (2 papers)Redox Biology (2 papers)Aging Cell (2 papers)Experimental Gerontology (1 paper)Integrative and Comparative Biology (1 paper)
- Partner nations
- United StatesItalyMexico
In The Last Decade
Daniel Pulliam
16 papers receiving 534 citations
Peers
Comparison fields: 5 of 79
- Aging 108
- Physiology 233
- Rehabilitation 41
- Geriatrics and Gerontology 22
- Molecular Biology 372
Countries citing papers authored by Daniel Pulliam
This map shows the geographic impact of Daniel Pulliam'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 Pulliam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Pulliam more than expected).
Fields of papers citing papers by Daniel Pulliam
This network shows the impact of papers produced by Daniel Pulliam. 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 Pulliam. The network helps show where Daniel Pulliam may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Pulliam, 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 | 2013 | 96 | |
| 2 | 2014 | 90 | |
| 3 | 2013 | 66 | |
| 4 | 2010 | 38 | |
| 5 | 2013 | 37 | |
| 6 | 2012 | 32 | |
| 7 | 2012 | 29 | |
| 8 | 2013 | 28 | |
| 9 | Rapamycin Modulates Markers of Mitochondrial Biogenesis and Fatty Acid Oxidation in the Adipose Tissue of db/db Mice. | 2013 | 28 |
| 10 | 2010 | 22 | |
| 11 | 2016 | 21 | |
| 12 | 2015 | 20 | |
| 13 | 2018 | 14 | |
| 14 | 2017 | 10 | |
| 15 | 2017 | 5 | |
| 16 | 2020 | 1 | |
| 17 | 2009 | 1 | |
| 18 | 2013 | 0 |
About Daniel Pulliam
Daniel Pulliam is a scholar working on Molecular Biology, Physiology, Aging, Epidemiology and Critical Care and Intensive Care Medicine, having authored 18 papers that have together received 538 indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (13 papers), Adipose Tissue and Metabolism (10 papers), Genetics, Aging, and Longevity in Model Organisms (5 papers), Redox biology and oxidative stress (2 papers), Spaceflight effects on biology (2 papers), Muscle Physiology and Disorders (2 papers), Metabolism and Genetic Disorders (1 paper) and Child Development and Digital Technology (1 paper). The work is most often cited by research in Aging (108 citations), Physiology (233 citations), Rehabilitation (41 citations), Geriatrics and Gerontology (22 citations) and Molecular Biology (372 citations). Daniel Pulliam has collaborated with scholars based in United States, Italy and Mexico. Frequent co-authors include Holly Van Remmen, Yun Shi, Arunabh Bhattacharya, Shauna Hill, Sathyaseelan S. Deepa, Yuhong Liu, Lauren Sloane, Carlo Viscomi, Christian Sell and Massimo Zeviani. Their work appears in journals such as The FASEB Journal, Redox Biology, Aging Cell, Experimental Gerontology and Integrative and Comparative 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.