David Kipling
Impact in
- Aging top 0.2%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 0.5%
- Telomeres, Telomerase, and Senescence
Papers in
-
- DNA Repair Mechanisms 30
- Physiology 53
- Telomeres, Telomerase, and Senescence 51
- Co-authors
- Howard J. Cooke (9 shared papers)Deborah K. Dunn‐Walters (20 shared papers)Terence Davis (34 shared papers)Richard Faragher (17 shared papers)Duncan M. Baird (7 shared papers)David Wynford‐Thomas (11 shared papers)Bryan Wu (13 shared papers)J M Rowson (3 shared papers)
- Journals
- Annals of the New York Academy of Sciences (7 papers)Nature (5 papers)Biogerontology (5 papers)Human Molecular Genetics (5 papers)Nature Genetics (4 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
David Kipling
124 papers receiving 7.3k citations
David Kipling's Hit Papers
Peers
Comparison fields: 5 of 139
- Aging 652
- Physiology 2.4k
- Immunology 1.6k
- Molecular Biology 3.2k
- Rehabilitation 237
Countries citing papers authored by David Kipling
This map shows the geographic impact of David Kipling'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 Kipling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Kipling more than expected).
Fields of papers citing papers by David Kipling
This network shows the impact of papers produced by David Kipling. 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 Kipling. The network helps show where David Kipling may publish in the future.
Co-authors
The 25 scholars most cited alongside David Kipling, 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 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Hypervariable ultra-long telomeres in mice Hit paper breakdown → | 1990 | 514 |
| 2 | 2003 | 442 | |
| 3 | 2008 | 340 | |
| 4 | 2000 | 278 | |
| 5 | 2010 | 225 | |
| 6 | 2011 | 194 | |
| 7 | 2014 | 184 | |
| 8 | 2008 | 183 | |
| 9 | 1997 | 182 | |
| 10 | 2004 | 148 | |
| 11 | 2005 | 139 | |
| 12 | 2011 | 139 | |
| 13 | 2004 | 137 | |
| 14 | 2015 | 133 | |
| 15 | 2018 | 124 | |
| 16 | 1999 | 119 | |
| 17 | 2007 | 112 | |
| 18 | 2011 | 111 | |
| 19 | 2009 | 109 | |
| 20 | 2006 | 106 |
About David Kipling
David Kipling is a scholar working on Molecular Biology, Physiology, Immunology, Aging and Genetics, having authored 127 papers that have together received 7.4k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (51 papers), DNA Repair Mechanisms (30 papers), Genetics, Aging, and Longevity in Model Organisms (18 papers), T-cell and B-cell Immunology (17 papers), Chromosomal and Genetic Variations (15 papers), Monoclonal and Polyclonal Antibodies Research (12 papers), Immune Cell Function and Interaction (11 papers) and Cancer-related Molecular Pathways (9 papers). The work is most often cited by research in Aging (652 citations), Physiology (2.4k citations), Immunology (1.6k citations), Molecular Biology (3.2k citations) and Rehabilitation (237 citations). David Kipling has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Howard J. Cooke, Deborah K. Dunn‐Walters, Terence Davis, Richard Faragher, Duncan M. Baird, David Wynford‐Thomas, Bryan Wu, J M Rowson, Christopher J. Jones and Victoria Martin. Their work appears in journals such as Annals of the New York Academy of Sciences, Nature, Biogerontology, Human Molecular Genetics and Nature Genetics.
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.