Thomas Widmann
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 5%
- Telomeres, Telomerase, and Senescence
Papers in
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- Folate and B Vitamins Research 7
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- Telomeres, Telomerase, and Senescence 6
- Co-authors
- Markus Herrmann (11 shared papers)Michael Pfreundschuh (9 shared papers)Wolfgang Herrmann (8 shared papers)Stefan Schönland (2 shared papers)Cornelia M. Weyand (2 shared papers)Julia Zimmer (2 shared papers)Jörg J. Goronzy (2 shared papers)Graziana Colaianni (6 shared papers)
- Journals
- Experimental Hematology (3 papers)Clinical Chemistry and Laboratory Medicine (CCLM) (3 papers)European Journal of Nutrition (2 papers)PLoS ONE (2 papers)European Urology (1 paper)
- Partner nations
- GermanyItalyUnited States
In The Last Decade
Thomas Widmann
30 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 113
- Aging 162
- Physiology 573
- Rheumatology 304
- Immunology 323
- Orthopedics and Sports Medicine 122
Countries citing papers authored by Thomas Widmann
This map shows the geographic impact of Thomas Widmann'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 Thomas Widmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Widmann more than expected).
Fields of papers citing papers by Thomas Widmann
This network shows the impact of papers produced by Thomas Widmann. 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 Thomas Widmann. The network helps show where Thomas Widmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Widmann, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 282 | |
| 2 | 2011 | 234 | |
| 3 | 2008 | 197 | |
| 4 | 2003 | 174 | |
| 5 | 2003 | 137 | |
| 6 | 2005 | 100 | |
| 7 | 2007 | 96 | |
| 8 | 2009 | 91 | |
| 9 | 2005 | 75 | |
| 10 | 2008 | 69 | |
| 11 | 2007 | 53 | |
| 12 | 2007 | 50 | |
| 13 | 2008 | 41 | |
| 14 | 2016 | 28 | |
| 15 | 2013 | 22 | |
| 16 | 2020 | 22 | |
| 17 | 2007 | 17 | |
| 18 | 2018 | 17 | |
| 19 | 2007 | 13 | |
| 20 | 2014 | 12 |
About Thomas Widmann
Thomas Widmann is a scholar working on Rheumatology, Physiology, Epidemiology, Molecular Biology and Immunology, having authored 31 papers that have together received 1.8k indexed citations. Recurring topics across this work include Folate and B Vitamins Research (7 papers), Telomeres, Telomerase, and Senescence (6 papers), Cytomegalovirus and herpesvirus research (4 papers), Immunotherapy and Immune Responses (3 papers), T-cell and B-cell Immunology (2 papers), Bone health and osteoporosis research (2 papers), Natural Language Processing Techniques (2 papers) and Immune Cell Function and Interaction (2 papers). The work is most often cited by research in Aging (162 citations), Physiology (573 citations), Rheumatology (304 citations), Immunology (323 citations) and Orthopedics and Sports Medicine (122 citations). Thomas Widmann has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Markus Herrmann, Michael Pfreundschuh, Wolfgang Herrmann, Stefan Schönland, Cornelia M. Weyand, Julia Zimmer, Jörg J. Goronzy, Graziana Colaianni, Ulrich Laufs and Judith Haendeler. Their work appears in journals such as Experimental Hematology, Clinical Chemistry and Laboratory Medicine (CCLM), European Journal of Nutrition, PLoS ONE and European Urology.
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.