Daniel T. Utzschneider
- Immunology top 1%
- Oncology top 2%
- Molecular Biology
- Epidemiology top 10%
- Cancer Research top 10%
- Co-authors
- Dietmar ZehnAxel KalliesRobert ThimmeFrancesca AlfeiMaike HofmannDaniel E. SpeiserWerner HeldVijaykumar Chennupati
- Topics
- Immune Cell Function and Interaction (16 papers)T-cell and B-cell Immunology (15 papers)Immunotherapy and Immune Responses (6 papers)
- Cited by
- ImmunologyOncologyVirology
- Partner nations
- SwitzerlandAustraliaGermany
In The Last Decade
Daniel T. Utzschneider
22 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Immunology 2.3k
- Oncology 1.6k
- Molecular Biology 605
- Epidemiology 306
- Cancer Research 257
Countries citing papers authored by Daniel T. Utzschneider
This map shows the geographic impact of Daniel T. Utzschneider'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 Daniel T. Utzschneider with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Utzschneider more than expected).
Fields of papers citing papers by Daniel T. Utzschneider
This network shows the impact of papers produced by Daniel T. Utzschneider. 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 Daniel T. Utzschneider. The network helps show where Daniel T. Utzschneider may publish in the future.
Co-authorship network of co-authors of Daniel T. Utzschneider
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel T. Utzschneider. A scholar is included among the top collaborators of Daniel T. Utzschneider 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 Daniel T. Utzschneider. Daniel T. Utzschneider 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 | 1 | |
| 3 | 3 | |
| 4 | 62 | |
| 5 | 110 | |
| 6 | 169 | |
| 7 | 272 | |
| 8 | TOX reinforces the phenotype and longevity of exhausted T cells in chronic viral infectionbreakdown → | 546 |
| 9 | 65 | |
| 10 | 75 | |
| 11 | 63 | |
| 12 | 44 | |
| 13 | T Cell Factor 1-Expressing Memory-like CD8+ T Cells Sustain the Immune Response to Chronic Viral Infectionsbreakdown → | 668 |
| 14 | 28 | |
| 15 | 28 | |
| 16 | 226 | |
| 17 | 252 | |
| 18 | 203 | |
| 19 | 83 | |
| 20 | 42 |
About Daniel T. Utzschneider
Daniel T. Utzschneider is a scholar working on Immunology, Virology and Genetics, having authored 23 papers that have together received 3.1k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (16 papers), T-cell and B-cell Immunology (15 papers) and Immunotherapy and Immune Responses (6 papers). The work is most often cited by research in Immunology (2.3k citations), Oncology (1.6k citations) and Virology (87 citations). Daniel T. Utzschneider has collaborated with scholars based in Switzerland, Australia and Germany. Frequent co-authors include Dietmar Zehn, Axel Kallies, Robert Thimme, Francesca Alfei, Maike Hofmann, Daniel E. Speiser, Werner Held, Vijaykumar Chennupati, Dominik Wieland and Pedro Romero. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.