Simon Tuck
Impact in
- Aging top 0.2%
- Genetics, Aging, and Longevity in Model Organisms
-
- Circadian rhythm and melatonin
Papers in
- Aging 25
- Genetics, Aging, and Longevity in Model Organisms 25
-
- Mitochondrial Function and Pathology 4
- CRISPR and Genetic Engineering 4
- Co-authors
- Iva Greenwald (4 shared papers)Peter Lamb (2 shared papers)D. Pim (2 shared papers)Greg Matlashewski (2 shared papers)L.V. Crawford (2 shared papers)Johannes Schneider (2 shared papers)L. Crawford (2 shared papers)Andeŕs S. Byström (1 shared paper)
- Journals
- Molecular and Cellular Biology (4 papers)Development (4 papers)Genetics (3 papers)Molecular Biology of the Cell (3 papers)Proceedings of the National Academy of Sciences (3 papers)
- Partner nations
- SwedenUnited StatesUnited Kingdom
In The Last Decade
Simon Tuck
42 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 113
- Aging 890
- Endocrine and Autonomic Systems 283
- Endocrinology 129
- Oncology 506
- Molecular Biology 1.3k
Countries citing papers authored by Simon Tuck
This map shows the geographic impact of Simon Tuck'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 Simon Tuck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Tuck more than expected).
Fields of papers citing papers by Simon Tuck
This network shows the impact of papers produced by Simon Tuck. 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 Simon Tuck. The network helps show where Simon Tuck may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Tuck, 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 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1987 | 423 | |
| 2 | 2004 | 154 | |
| 3 | 1995 | 141 | |
| 4 | 1999 | 134 | |
| 5 | 2006 | 130 | |
| 6 | 2009 | 112 | |
| 7 | 2000 | 108 | |
| 8 | 2007 | 102 | |
| 9 | 2002 | 100 | |
| 10 | 1989 | 97 | |
| 11 | 2005 | 94 | |
| 12 | 2012 | 80 | |
| 13 | 2010 | 71 | |
| 14 | 2011 | 66 | |
| 15 | 1987 | 58 | |
| 16 | 2002 | 56 | |
| 17 | 2008 | 54 | |
| 18 | 1995 | 54 | |
| 19 | 2018 | 45 | |
| 20 | 2004 | 45 |
About Simon Tuck
Simon Tuck is a scholar working on Aging, Molecular Biology, Endocrine and Autonomic Systems, Cell Biology and Physiology, having authored 42 papers that have together received 2.5k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (25 papers), Circadian rhythm and melatonin (7 papers), Cellular transport and secretion (4 papers), Cancer-related Molecular Pathways (4 papers), Selenium in Biological Systems (4 papers), Mitochondrial Function and Pathology (4 papers), CRISPR and Genetic Engineering (4 papers) and Virus-based gene therapy research (4 papers). The work is most often cited by research in Aging (890 citations), Endocrine and Autonomic Systems (283 citations), Endocrinology (129 citations), Oncology (506 citations) and Molecular Biology (1.3k citations). Simon Tuck has collaborated with scholars based in Sweden, United States and United Kingdom. Frequent co-authors include Iva Greenwald, Peter Lamb, D. Pim, Greg Matlashewski, L.V. Crawford, Johannes Schneider, L. Crawford, Andeŕs S. Byström, Changchun Chen and Greg J. Beitel. Their work appears in journals such as Molecular and Cellular Biology, Development, Genetics, Molecular Biology of the Cell and Proceedings of the National Academy of Sciences.
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.