Jan Karlseder
- Aging top 0.1%
- Genetics, Aging, and Longevity in Model Organisms 14
- Physiology top 0.1%
- Telomeres, Telomerase, and Senescence 50
- Molecular Biology top 0.5%
- DNA Repair Mechanisms 34
- CRISPR and Genetic Engineering 9
- Mitochondrial Function and Pathology 6
- Advanced biosensing and bioanalysis techniques 6
- Genomics and Chromatin Dynamics 6
- Biotechnology top 1%
- Cancer Research top 5%
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- Chromosomal and Genetic Variations 6
- Co-authors
- Titia de LangeRoderick J. O’SullivanRamiro E. VerdúnAgata SmogorzewskaLaure CrabbéCandy HaggblomDominique BroccoliYumin Dai
- Cited by
- AgingPhysiologyMolecular Biology
- Journals
- Nature (6 papers)Nature Structural & Molecular Biology (6 papers)Nature Communications (4 papers)
- Partner nations
- United StatesAustriaJapan
In The Last Decade
Jan Karlseder
67 papers receiving 9.3k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Aging 1.1k
- Physiology 5.6k
- Molecular Biology 7.3k
- Biotechnology 386
- Cancer Research 613
Countries citing papers authored by Jan Karlseder
This map shows the geographic impact of Jan Karlseder'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 Jan Karlseder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Karlseder more than expected).
Fields of papers citing papers by Jan Karlseder
This network shows the impact of papers produced by Jan Karlseder. 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 Jan Karlseder. The network helps show where Jan Karlseder may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jan Karlseder, 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 | 2025 | 1 | |
| 2 | 2024 | 29 | |
| 3 | 2023 | 97 | |
| 4 | 2017 | 119 | |
| 5 | 2017 | 185 | |
| 6 | 2016 | 80 | |
| 7 | 2014 | 39 | |
| 8 | 2014 | 197 | |
| 9 | 2013 | 22 | |
| 10 | 2013 | 119 | |
| 11 | 2012 | 23 | |
| 12 | 2012 | 77 | |
| 13 | 2010 | 131 | |
| 14 | Mammalian Telomeres Resemble Fragile Sites and Require TRF1 for Efficient Replicationbreakdown → | 2009 | 788 |
| 15 | 2005 | 226 | |
| 16 | 2004 | 290 | |
| 17 | 2003 | 59 | |
| 18 | 2002 | 310 | |
| 19 | 1998 | 23 | |
| 20 | 1996 | 84 |
About Jan Karlseder
Jan Karlseder is a scholar working on Aging, Physiology and Molecular Biology, having authored 67 papers that have together received 9.4k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (50 papers), DNA Repair Mechanisms (34 papers), Genetics, Aging, and Longevity in Model Organisms (14 papers), CRISPR and Genetic Engineering (9 papers), Mitochondrial Function and Pathology (6 papers), Advanced biosensing and bioanalysis techniques (6 papers), Chromosomal and Genetic Variations (6 papers) and Genomics and Chromatin Dynamics (6 papers). The work is most often cited by research in Aging (1.1k citations), Physiology (5.6k citations) and Molecular Biology (7.3k citations). Jan Karlseder has collaborated with scholars based in United States, Austria and Japan. Frequent co-authors include Titia de Lange, Roderick J. O’Sullivan, Ramiro E. Verdún, Agata Smogorzewska, Laure Crabbé, Candy Haggblom, Dominique Broccoli, Yumin Dai, Stephen Hardy and Makoto Hayashi. Their work appears in journals such as Nature, Nature Structural & Molecular Biology, Nature Communications, Science and Cell.
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.