Daniel L. Mazula
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 5%
- Telomeres, Telomerase, and Senescence
- Adipose Tissue and Metabolism
- Nutrition and Health in Aging
Papers in
-
- Diet and metabolism studies 2
- Telomeres, Telomerase, and Senescence 2
- Dietary Effects on Health 2
- Aging 4
- Genetics, Aging, and Longevity in Model Organisms 4
- Co-authors
- Marissa Schafer (6 shared papers)Nathan K. LeBrasseur (6 shared papers)Thomas A. White (5 shared papers)Ashley K. Brown (3 shared papers)Elizabeth J. Atkinson (2 shared papers)Zaira Aversa (3 shared papers)Yi Zhu (1 shared paper)Xu Zhang (1 shared paper)
- Journals
- Innovation in Aging (2 papers)Protein Science (1 paper)The Journals of Gerontology Series A (1 paper)Aging Cell (1 paper)JCI Insight (1 paper)
- Partner nations
- United StatesBelarusUnited Arab Emirates
In The Last Decade
Daniel L. Mazula
7 papers receiving 515 citations
Daniel L. Mazula's Hit Papers
Peers
Comparison fields: 5 of 69
- Aging 75
- Physiology 321
- Geriatrics and Gerontology 31
- Biological Psychiatry 11
- Immunology 96
Countries citing papers authored by Daniel L. Mazula
This map shows the geographic impact of Daniel L. Mazula'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 L. Mazula with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel L. Mazula more than expected).
Fields of papers citing papers by Daniel L. Mazula
This network shows the impact of papers produced by Daniel L. Mazula. 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 L. Mazula. The network helps show where Daniel L. Mazula may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel L. Mazula, 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 | The senescence-associated secretome as an indicator of age and medical risk Hit paper breakdown → | 2020 | 274 |
| 2 | 2016 | 209 | |
| 3 | 2019 | 18 | |
| 4 | 2015 | 10 | |
| 5 | 2023 | 2 | |
| 6 | 2017 | 2 | |
| 7 | 2019 | 1 |
About Daniel L. Mazula
Daniel L. Mazula is a scholar working on Physiology, Aging, Molecular Biology, Endocrine and Autonomic Systems and Pulmonary and Respiratory Medicine, having authored 7 papers that have together received 516 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (4 papers), Diet and metabolism studies (2 papers), Circadian rhythm and melatonin (2 papers), Telomeres, Telomerase, and Senescence (2 papers), Dietary Effects on Health (2 papers), Pharmacogenetics and Drug Metabolism (1 paper), Computational Drug Discovery Methods (1 paper) and Mitochondrial Function and Pathology (1 paper). The work is most often cited by research in Aging (75 citations), Physiology (321 citations), Geriatrics and Gerontology (31 citations), Biological Psychiatry (11 citations) and Immunology (96 citations). Daniel L. Mazula has collaborated with scholars based in United States, Belarus and United Arab Emirates. Frequent co-authors include Marissa Schafer, Nathan K. LeBrasseur, Thomas A. White, Ashley K. Brown, Elizabeth J. Atkinson, Zaira Aversa, Yi Zhu, Xu Zhang, Kevin L. Greason and Michelle J. Berning. Their work appears in journals such as Innovation in Aging, Protein Science, The Journals of Gerontology Series A, Aging Cell and JCI Insight.
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.