David J. Pagliarini
- Molecular Biology top 1%
- Physiology top 2%
- Clinical Biochemistry top 0.2%
- Spectroscopy top 1%
- Epidemiology top 5%
- Co-authors
- Vamsi K. MoothaSarah E. CalvoJoshua J. CoonJack E. DixonJonathan A. StefelySteven A. CarrShao‐En OngCanny Sugiana
- Topics
- Mitochondrial Function and Pathology (35 papers)ATP Synthase and ATPases Research (17 papers)Coenzyme Q10 studies and effects (16 papers)
- Journals
- CellProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- United StatesSwitzerlandAustralia
In The Last Decade
David J. Pagliarini
69 papers receiving 6.5k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Molecular Biology 5.1k
- Physiology 887
- Clinical Biochemistry 797
- Spectroscopy 601
- Epidemiology 595
Countries citing papers authored by David J. Pagliarini
This map shows the geographic impact of David J. Pagliarini'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 David J. Pagliarini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Pagliarini more than expected).
Fields of papers citing papers by David J. Pagliarini
This network shows the impact of papers produced by David J. Pagliarini. 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 David J. Pagliarini. The network helps show where David J. Pagliarini may publish in the future.
Co-authorship network of co-authors of David J. Pagliarini
This figure shows the co-authorship network connecting the top 25 collaborators of David J. Pagliarini. A scholar is included among the top collaborators of David J. Pagliarini based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David J. Pagliarini. David J. Pagliarini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 18 | |
| 5 | 32 | |
| 6 | 20 | |
| 7 | 25 | |
| 8 | 13 | |
| 9 | 34 | |
| 10 | 60 | |
| 11 | 42 | |
| 12 | 39 | |
| 13 | 33 | |
| 14 | 168 | |
| 15 | 247 | |
| 16 | 151 | |
| 17 | 89 | |
| 18 | 126 | |
| 19 | 51 | |
| 20 | Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humansbreakdown → | 664 |
About David J. Pagliarini
David J. Pagliarini is a scholar working on Biochemistry, Clinical Biochemistry and Molecular Biology, having authored 72 papers that have together received 6.5k indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (35 papers), ATP Synthase and ATPases Research (17 papers) and Coenzyme Q10 studies and effects (16 papers). The work is most often cited by research in Geriatrics and Gerontology (462 citations), Clinical Biochemistry (797 citations) and Molecular Biology (5.1k citations). David J. Pagliarini has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Vamsi K. Mootha, Sarah E. Calvo, Joshua J. Coon, Jack E. Dixon, Jonathan A. Stefely, Steven A. Carr, Shao‐En Ong, Canny Sugiana, David R. Thorburn and Michael S. Westphall. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.